An optimal control framework for dynamic induction control of wind farms and their interaction with the atmospheric boundary layer

PubMed Central

Munters, W.

2017-01-01

Complex turbine wake interactions play an important role in overall energy extraction in large wind farms. Current control strategies optimize individual turbine power, and lead to significant energy losses in wind farms compared with lone-standing wind turbines. In recent work, an optimal coordinated control framework was introduced (Goit & Meyers 2015 J. Fluid Mech. 768, 5–50 (doi:10.1017/jfm.2015.70)). Here, we further elaborate on this framework, quantify the influence of optimization parameters and introduce new simulation results for which gains in power production of up to 21% are observed. This article is part of the themed issue ‘Wind energy in complex terrains’. PMID:28265024

Real-Time Control of an Ensemble of Heterogeneous Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernstein, Andrey; Bouman, Niek J.; Le Boudec, Jean-Yves

This paper focuses on the problem of controlling an ensemble of heterogeneous resources connected to an electrical grid at the same point of common coupling (PCC). The controller receives an aggregate power setpoint for the ensemble in real time and tracks this setpoint by issuing individual optimal setpoints to the resources. The resources can have continuous or discrete nature (e.g., heating systems consisting of a finite number of heaters that each can be either switched on or off) and/or can be highly uncertain (e.g., photovoltaic (PV) systems or residential loads). A naive approach would lead to a stochastic mixed-integer optimizationmore » problem to be solved at the controller at each time step, which might be infeasible in real time. Instead, we allow the controller to solve a continuous convex optimization problem and compensate for the errors at the resource level by using a variant of the well-known error diffusion algorithm. We give conditions guaranteeing that our algorithm tracks the power setpoint at the PCC on average while issuing optimal setpoints to individual resources. We illustrate the approach numerically by controlling a collection of batteries, PV systems, and discrete loads.« less

A simple approach to optimal control of invasive species.

PubMed

Hastings, Alan; Hall, Richard J; Taylor, Caz M

2006-12-01

The problem of invasive species and their control is one of the most pressing applied issues in ecology today. We developed simple approaches based on linear programming for determining the optimal removal strategies of different stage or age classes for control of invasive species that are still in a density-independent phase of growth. We illustrate the application of this method to the specific example of invasive Spartina alterniflora in Willapa Bay, WA. For all such systems, linear programming shows in general that the optimal strategy in any time step is to prioritize removal of a single age or stage class. The optimal strategy adjusts which class is the focus of control through time and can be much more cost effective than prioritizing removal of the same stage class each year.

Proper Orthogonal Decomposition in Optimal Control of Fluids

NASA Technical Reports Server (NTRS)

Ravindran, S. S.

1999-01-01

In this article, we present a reduced order modeling approach suitable for active control of fluid dynamical systems based on proper orthogonal decomposition (POD). The rationale behind the reduced order modeling is that numerical simulation of Navier-Stokes equations is still too costly for the purpose of optimization and control of unsteady flows. We examine the possibility of obtaining reduced order models that reduce computational complexity associated with the Navier-Stokes equations while capturing the essential dynamics by using the POD. The POD allows extraction of certain optimal set of basis functions, perhaps few, from a computational or experimental data-base through an eigenvalue analysis. The solution is then obtained as a linear combination of these optimal set of basis functions by means of Galerkin projection. This makes it attractive for optimal control and estimation of systems governed by partial differential equations. We here use it in active control of fluid flows governed by the Navier-Stokes equations. We show that the resulting reduced order model can be very efficient for the computations of optimization and control problems in unsteady flows. Finally, implementational issues and numerical experiments are presented for simulations and optimal control of fluid flow through channels.

Optimal coordinated voltage control in active distribution networks using backtracking search algorithm

PubMed Central

Tengku Hashim, Tengku Juhana; Mohamed, Azah

2017-01-01

The growing interest in distributed generation (DG) in recent years has led to a number of generators connected to a distribution system. The integration of DGs in a distribution system has resulted in a network known as active distribution network due to the existence of bidirectional power flow in the system. Voltage rise issue is one of the predominantly important technical issues to be addressed when DGs exist in an active distribution network. This paper presents the application of the backtracking search algorithm (BSA), which is relatively new optimisation technique to determine the optimal settings of coordinated voltage control in a distribution system. The coordinated voltage control considers power factor, on-load tap-changer and generation curtailment control to manage voltage rise issue. A multi-objective function is formulated to minimise total losses and voltage deviation in a distribution system. The proposed BSA is compared with that of particle swarm optimisation (PSO) so as to evaluate its effectiveness in determining the optimal settings of power factor, tap-changer and percentage active power generation to be curtailed. The load flow algorithm from MATPOWER is integrated in the MATLAB environment to solve the multi-objective optimisation problem. Both the BSA and PSO optimisation techniques have been tested on a radial 13-bus distribution system and the results show that the BSA performs better than PSO by providing better fitness value and convergence rate. PMID:28991919

Optimal coordinated voltage control in active distribution networks using backtracking search algorithm.

PubMed

Tengku Hashim, Tengku Juhana; Mohamed, Azah

2017-01-01

The growing interest in distributed generation (DG) in recent years has led to a number of generators connected to a distribution system. The integration of DGs in a distribution system has resulted in a network known as active distribution network due to the existence of bidirectional power flow in the system. Voltage rise issue is one of the predominantly important technical issues to be addressed when DGs exist in an active distribution network. This paper presents the application of the backtracking search algorithm (BSA), which is relatively new optimisation technique to determine the optimal settings of coordinated voltage control in a distribution system. The coordinated voltage control considers power factor, on-load tap-changer and generation curtailment control to manage voltage rise issue. A multi-objective function is formulated to minimise total losses and voltage deviation in a distribution system. The proposed BSA is compared with that of particle swarm optimisation (PSO) so as to evaluate its effectiveness in determining the optimal settings of power factor, tap-changer and percentage active power generation to be curtailed. The load flow algorithm from MATPOWER is integrated in the MATLAB environment to solve the multi-objective optimisation problem. Both the BSA and PSO optimisation techniques have been tested on a radial 13-bus distribution system and the results show that the BSA performs better than PSO by providing better fitness value and convergence rate.

Multi-step optimization strategy for fuel-optimal orbital transfer of low-thrust spacecraft

NASA Astrophysics Data System (ADS)

Rasotto, M.; Armellin, R.; Di Lizia, P.

2016-03-01

An effective method for the design of fuel-optimal transfers in two- and three-body dynamics is presented. The optimal control problem is formulated using calculus of variation and primer vector theory. This leads to a multi-point boundary value problem (MPBVP), characterized by complex inner constraints and a discontinuous thrust profile. The first issue is addressed by embedding the MPBVP in a parametric optimization problem, thus allowing a simplification of the set of transversality constraints. The second problem is solved by representing the discontinuous control function by a smooth function depending on a continuation parameter. The resulting trajectory optimization method can deal with different intermediate conditions, and no a priori knowledge of the control structure is required. Test cases in both the two- and three-body dynamics show the capability of the method in solving complex trajectory design problems.

Who reaps the benefits, who bears the risks? Comparative optimism, comparative utility, and regulatory preferences for mobile phone technology.

PubMed

White, Mathew P; Eiser, J Richard; Harris, Peter R; Pahl, Sabine

2007-06-01

Although the issue of risk target (e.g., self, others, children) is widely acknowledged in risk perception research, its importance appears underappreciated. To date, most research has been satisfied with demonstrating comparative optimism, i.e., lower perceived risk for the self than others, and exploring its moderators, such as perceived controllability and personal exposure. Much less research has investigated how the issue of target may affect benefit perceptions or key outcomes such as stated preferences for hazard regulation. The current research investigated these issues using data from a public survey of attitudes toward mobile phone technology (N= 1,320). First, results demonstrated comparative optimism for this hazard, and also found moderating effects of both controllability and personal exposure. Second, there was evidence of comparative utility, i.e., users believed that the benefits from mobile phone technology are greater for the self than others. Third, and most important for policy, preferences for handset regulation were best predicted by perceptions of the risks to others but perceived benefits for the self. Results suggest a closer awareness of target can improve prediction of stated preferences for hazard regulation and that it would be profitable for future research to pay more attention to the issue of target for both risk and benefit perceptions.

On the use of controls for subsonic transport performance improvement: Overview and future directions

NASA Technical Reports Server (NTRS)

Gilyard, Glenn; Espana, Martin

1994-01-01

Increasing competition among airline manufacturers and operators has highlighted the issue of aircraft efficiency. Fewer aircraft orders have led to an all-out efficiency improvement effort among the manufacturers to maintain if not increase their share of the shrinking number of aircraft sales. Aircraft efficiency is important in airline profitability and is key if fuel prices increase from their current low. In a continuing effort to improve aircraft efficiency and develop an optimal performance technology base, NASA Dryden Flight Research Center developed and flight tested an adaptive performance seeking control system to optimize the quasi-steady-state performance of the F-15 aircraft. The demonstrated technology is equally applicable to transport aircraft although with less improvement. NASA Dryden, in transitioning this technology to transport aircraft, is specifically exploring the feasibility of applying adaptive optimal control techniques to performance optimization of redundant control effectors. A simulation evaluation of a preliminary control law optimizes wing-aileron camber for minimum net aircraft drag. Two submodes are evaluated: one to minimize fuel and the other to maximize velocity. This paper covers the status of performance optimization of the current fleet of subsonic transports. Available integrated controls technologies are reviewed to define approaches using active controls. A candidate control law for adaptive performance optimization is presented along with examples of algorithm operation.

Optimized multiparametric flow cytometric analysis of circulating endothelial cells and their subpopulations in peripheral blood of patients with solid tumors: a technical analysis.

PubMed

Zhou, Fangbin; Zhou, Yaying; Yang, Ming; Wen, Jinli; Dong, Jun; Tan, Wenyong

2018-01-01

Circulating endothelial cells (CECs) and their subpopulations could be potential novel biomarkers for various malignancies. However, reliable enumerable methods are warranted to further improve their clinical utility. This study aimed to optimize a flow cytometric method (FCM) assay for CECs and subpopulations in peripheral blood for patients with solid cancers. An FCM assay was used to detect and identify CECs. A panel of 60 blood samples, including 44 metastatic cancer patients and 16 healthy controls, were used in this study. Some key issues of CEC enumeration, including sample material and anticoagulant selection, optimal titration of antibodies, lysis/wash procedures of blood sample preparation, conditions of sample storage, sufficient cell events to enhance the signal, fluorescence-minus-one controls instead of isotype controls to reduce background noise, optimal selection of cell surface markers, and evaluating the reproducibility of our method, were integrated and investigated. Wilcoxon and Mann-Whitney U tests were used to determine statistically significant differences. In this validation study, we refined a five-color FCM method to detect CECs and their subpopulations in peripheral blood of patients with solid tumors. Several key technical issues regarding preanalytical elements, FCM data acquisition, and analysis were addressed. Furthermore, we clinically validated the utility of our method. The baseline levels of mature CECs, endothelial progenitor cells, and activated CECs were higher in cancer patients than healthy subjects ( P <0.01). However, there was no significant difference in resting CEC levels between healthy subjects and cancer patients ( P =0.193). We integrated and comprehensively addressed significant technical issues found in previously published assays and validated the reproducibility and sensitivity of our proposed method. Future work is required to explore the potential of our optimized method in clinical oncologic applications.

System controls challenges of hypersonic combined-cycle engine powered vehicles

NASA Technical Reports Server (NTRS)

Morrison, Russell H.; Ianculescu, George D.

1992-01-01

Hypersonic aircraft with air-breathing engines have been described as the most complex and challenging air/space vehicle designs ever attempted. This is particularly true for aircraft designed to accelerate to orbital velocities. The propulsion system for the National Aerospace Plane will be an active factor in maintaining the aircraft on course. Typically addressed are the difficulties with the aerodynamic vehicle design and development, materials limitations and propulsion performance. The propulsion control system requires equal materials limitations and propulsion performance. The propulsion control system requires equal concern. Far more important than merely a subset of propulsion performance, the propulsion control system resides at the crossroads of trajectory optimization, engine static performance, and vehicle-engine configuration optimization. To date, solutions at these crossroads are multidisciplinary and generally lag behind the broader performance issues. Just how daunting these demands will be is suggested. A somewhat simplified treatment of the behavioral characteristics of hypersonic aircraft and the issues associated with their air-breathing propulsion control system design are presented.

Optimal combinations of control strategies and cost-effective analysis for visceral leishmaniasis disease transmission.

PubMed

Biswas, Santanu; Subramanian, Abhishek; ELMojtaba, Ibrahim M; Chattopadhyay, Joydev; Sarkar, Ram Rup

2017-01-01

Visceral leishmaniasis (VL) is a deadly neglected tropical disease that poses a serious problem in various countries all over the world. Implementation of various intervention strategies fail in controlling the spread of this disease due to issues of parasite drug resistance and resistance of sandfly vectors to insecticide sprays. Due to this, policy makers need to develop novel strategies or resort to a combination of multiple intervention strategies to control the spread of the disease. To address this issue, we propose an extensive SIR-type model for anthroponotic visceral leishmaniasis transmission with seasonal fluctuations modeled in the form of periodic sandfly biting rate. Fitting the model for real data reported in South Sudan, we estimate the model parameters and compare the model predictions with known VL cases. Using optimal control theory, we study the effects of popular control strategies namely, drug-based treatment of symptomatic and PKDL-infected individuals, insecticide treated bednets and spray of insecticides on the dynamics of infected human and vector populations. We propose that the strategies remain ineffective in curbing the disease individually, as opposed to the use of optimal combinations of the mentioned strategies. Testing the model for different optimal combinations while considering periodic seasonal fluctuations, we find that the optimal combination of treatment of individuals and insecticide sprays perform well in controlling the disease for the time period of intervention introduced. Performing a cost-effective analysis we identify that the same strategy also proves to be efficacious and cost-effective. Finally, we suggest that our model would be helpful for policy makers to predict the best intervention strategies for specific time periods and their appropriate implementation for elimination of visceral leishmaniasis.

Meaning-making intervention during breast or colorectal cancer treatment improves self-esteem, optimism, and self-efficacy.

PubMed

Lee, Virginia; Robin Cohen, S; Edgar, Linda; Laizner, Andrea M; Gagnon, Anita J

2006-06-01

Existential issues often accompany a diagnosis of cancer and remain one aspect of psychosocial oncology care for which there is a need for focused, empirically tested interventions. This study examined the efficacy of a novel psychological intervention specifically designed to address existential issues through the use of meaning-making coping strategies on psychological adjustment to cancer. Eighty-two breast or colorectal cancer patients were randomly chosen to receive routine care (control group) or up to four sessions that explored the meaning of the emotional responses and cognitive appraisals of each individual's cancer experience within the context of past life events and future goals (experimental group). This paper reports the results from 74 patients who completed and returned pre- and post-test measures for self-esteem, optimism, and self-efficacy. After controlling for baseline scores, the experimental group participants demonstrated significantly higher levels of self-esteem, optimism, and self-efficacy compared to the control group. The results are discussed in light of the theoretical and clinical implications of meaning-making coping in the context of stress and illness.

Novel Numerical Methods for Optimal Control Problems Involving Fractional-Order Differential Equations

DTIC Science & Technology

2018-03-14

pricing, Appl. Math . Comp. Vol.305, 174-187 (2017) 5. W. Li, S. Wang, Pricing European options with proportional transaction costs and stochastic...for fractional differential equation. Numer. Math . Theor. Methods Appl. 5, 229–241, 2012. [23] Kilbas A.A. and Marzan, S.A., Cauchy problem for...numerical technique for solving fractional optimal control problems, Comput. Math . Appl., 62, Issue 3, 1055–1067, 2011. [26] Lotfi A., Yousefi SA., Dehghan M

A neuro-data envelopment analysis approach for optimization of uncorrelated multiple response problems with smaller the better type controllable factors

NASA Astrophysics Data System (ADS)

Bashiri, Mahdi; Farshbaf-Geranmayeh, Amir; Mogouie, Hamed

2013-11-01

In this paper, a new method is proposed to optimize a multi-response optimization problem based on the Taguchi method for the processes where controllable factors are the smaller-the-better (STB)-type variables and the analyzer desires to find an optimal solution with smaller amount of controllable factors. In such processes, the overall output quality of the product should be maximized while the usage of the process inputs, the controllable factors, should be minimized. Since all possible combinations of factors' levels, are not considered in the Taguchi method, the response values of the possible unpracticed treatments are estimated using the artificial neural network (ANN). The neural network is tuned by the central composite design (CCD) and the genetic algorithm (GA). Then data envelopment analysis (DEA) is applied for determining the efficiency of each treatment. Although the important issue for implementation of DEA is its philosophy, which is maximization of outputs versus minimization of inputs, this important issue has been neglected in previous similar studies in multi-response problems. Finally, the most efficient treatment is determined using the maximin weight model approach. The performance of the proposed method is verified in a plastic molding process. Moreover a sensitivity analysis has been done by an efficiency estimator neural network. The results show efficiency of the proposed approach.

A Survey on Optimal Signal Processing Techniques Applied to Improve the Performance of Mechanical Sensors in Automotive Applications

PubMed Central

Hernandez, Wilmar

2007-01-01

In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart) sensors that today's cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher's interest in the fusion of intelligent sensors and optimal signal processing techniques.

Grey Wolf based control for speed ripple reduction at low speed operation of PMSM drives.

PubMed

Djerioui, Ali; Houari, Azeddine; Ait-Ahmed, Mourad; Benkhoris, Mohamed-Fouad; Chouder, Aissa; Machmoum, Mohamed

2018-03-01

Speed ripple at low speed-high torque operation of Permanent Magnet Synchronous Machine (PMSM) drives is considered as one of the major issues to be treated. The presented work proposes an efficient PMSM speed controller based on Grey Wolf (GW) algorithm to ensure a high-performance control for speed ripple reduction at low speed operation. The main idea of the proposed control algorithm is to propose a specific objective function in order to incorporate the advantage of fast optimization process of the GW optimizer. The role of GW optimizer is to find the optimal input controls that satisfy the speed tracking requirements. The synthesis methodology of the proposed control algorithm is detailed and the feasibility and performances of the proposed speed controller is confirmed by simulation and experimental results. The GW algorithm is a model-free controller and the parameters of its objective function are easy to be tuned. The GW controller is compared to PI one on real test bench. Then, the superiority of the first algorithm is highlighted. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal wide-area monitoring and nonlinear adaptive coordinating neurocontrol of a power system with wind power integration and multiple FACTS devices.

PubMed

Qiao, Wei; Venayagamoorthy, Ganesh K; Harley, Ronald G

2008-01-01

Wide-area coordinating control is becoming an important issue and a challenging problem in the power industry. This paper proposes a novel optimal wide-area coordinating neurocontrol (WACNC), based on wide-area measurements, for a power system with power system stabilizers, a large wind farm and multiple flexible ac transmission system (FACTS) devices. An optimal wide-area monitor (OWAM), which is a radial basis function neural network (RBFNN), is designed to identify the input-output dynamics of the nonlinear power system. Its parameters are optimized through particle swarm optimization (PSO). Based on the OWAM, the WACNC is then designed by using the dual heuristic programming (DHP) method and RBFNNs, while considering the effect of signal transmission delays. The WACNC operates at a global level to coordinate the actions of local power system controllers. Each local controller communicates with the WACNC, receives remote control signals from the WACNC to enhance its dynamic performance and therefore helps improve system-wide dynamic and transient performance. The proposed control is verified by simulation studies on a multimachine power system.

Large-scale optimal control of interconnected natural gas and electrical transmission systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiang, Nai-Yuan; Zavala, Victor M.

2016-04-01

We present a detailed optimal control model that captures spatiotemporal interactions between gas and electric transmission networks. We use the model to study flexibility and economic opportunities provided by coordination. A large-scale case study in the Illinois system reveals that coordination can enable the delivery of significantly larger amounts of natural gas to the power grid. In particular, under a coordinated setting, gas-fired generators act as distributed demand response resources that can be controlled by the gas pipeline operator. This enables more efficient control of pressures and flows in space and time and overcomes delivery bottlenecks. We demonstrate that themore » additional flexibility not only can benefit the gas operator but can also lead to more efficient power grid operations and results in increased revenue for gas-fired power plants. We also use the optimal control model to analyze computational issues arising in these complex models. We demonstrate that the interconnected Illinois system with full physical resolution gives rise to a highly nonlinear optimal control problem with 4400 differential and algebraic equations and 1040 controls that can be solved with a state-of-the-art sparse optimization solver. (C) 2016 Elsevier Ltd. All rights reserved.« less

Optimization of controllability and robustness of complex networks by edge directionality

NASA Astrophysics Data System (ADS)

Liang, Man; Jin, Suoqin; Wang, Dingjie; Zou, Xiufen

2016-09-01

Recently, controllability of complex networks has attracted enormous attention in various fields of science and engineering. How to optimize structural controllability has also become a significant issue. Previous studies have shown that an appropriate directional assignment can improve structural controllability; however, the evolution of the structural controllability of complex networks under attacks and cascading has always been ignored. To address this problem, this study proposes a new edge orientation method (NEOM) based on residual degree that changes the link direction while conserving topology and directionality. By comparing the results with those of previous methods in two random graph models and several realistic networks, our proposed approach is demonstrated to be an effective and competitive method for improving the structural controllability of complex networks. Moreover, numerical simulations show that our method is near-optimal in optimizing structural controllability. Strikingly, compared to the original network, our method maintains the structural controllability of the network under attacks and cascading, indicating that the NEOM can also enhance the robustness of controllability of networks. These results alter the view of the nature of controllability in complex networks, change the understanding of structural controllability and affect the design of network models to control such networks.

Finite burn maneuver modeling for a generalized spacecraft trajectory design and optimization system.

PubMed

Ocampo, Cesar

2004-05-01

The modeling, design, and optimization of finite burn maneuvers for a generalized trajectory design and optimization system is presented. A generalized trajectory design and optimization system is a system that uses a single unified framework that facilitates the modeling and optimization of complex spacecraft trajectories that may operate in complex gravitational force fields, use multiple propulsion systems, and involve multiple spacecraft. The modeling and optimization issues associated with the use of controlled engine burn maneuvers of finite thrust magnitude and duration are presented in the context of designing and optimizing a wide class of finite thrust trajectories. Optimal control theory is used examine the optimization of these maneuvers in arbitrary force fields that are generally position, velocity, mass, and are time dependent. The associated numerical methods used to obtain these solutions involve either, the solution to a system of nonlinear equations, an explicit parameter optimization method, or a hybrid parameter optimization that combines certain aspects of both. The theoretical and numerical methods presented here have been implemented in copernicus, a prototype trajectory design and optimization system under development at the University of Texas at Austin.

Application of the advanced engineering environment for optimization energy consumption in designed vehicles

NASA Astrophysics Data System (ADS)

Monica, Z.; Sękala, A.; Gwiazda, A.; Banaś, W.

2016-08-01

Nowadays a key issue is to reduce the energy consumption of road vehicles. In particular solution one could find different strategies of energy optimization. The most popular but not sophisticated is so called eco-driving. In this strategy emphasized is particular behavior of drivers. In more sophisticated solution behavior of drivers is supported by control system measuring driving parameters and suggesting proper operation of the driver. The other strategy is concerned with application of different engineering solutions that aid optimization the process of energy consumption. Such systems take into consideration different parameters measured in real time and next take proper action according to procedures loaded to the control computer of a vehicle. The third strategy bases on optimization of the designed vehicle taking into account especially main sub-systems of a technical mean. In this approach the optimal level of energy consumption by a vehicle is obtained by synergetic results of individual optimization of particular constructional sub-systems of a vehicle. It is possible to distinguish three main sub-systems: the structural one the drive one and the control one. In the case of the structural sub-system optimization of the energy consumption level is related with the optimization or the weight parameter and optimization the aerodynamic parameter. The result is optimized body of a vehicle. Regarding the drive sub-system the optimization of the energy consumption level is related with the fuel or power consumption using the previously elaborated physical models. Finally the optimization of the control sub-system consists in determining optimal control parameters.

Optimizing the way kinematical feed chains with great distance between slides are chosen for CNC machine tools

NASA Astrophysics Data System (ADS)

Lucian, P.; Gheorghe, S.

2017-08-01

This paper presents a new method, based on FRISCO formula, for optimizing the choice of the best control system for kinematical feed chains with great distance between slides used in computer numerical controlled machine tools. Such machines are usually, but not limited to, used for machining large and complex parts (mostly in the aviation industry) or complex casting molds. For such machine tools the kinematic feed chains are arranged in a dual-parallel drive structure that allows the mobile element to be moved by the two kinematical branches and their related control systems. Such an arrangement allows for high speed and high rigidity (a critical requirement for precision machining) during the machining process. A significant issue for such an arrangement it’s the ability of the two parallel control systems to follow the same trajectory accurately in order to address this issue it is necessary to achieve synchronous motion control for the two kinematical branches ensuring that the correct perpendicular position it’s kept by the mobile element during its motion on the two slides.

Control and structural optimization for maneuvering large spacecraft

NASA Technical Reports Server (NTRS)

Chun, H. M.; Turner, J. D.; Yu, C. C.

1990-01-01

Presented here are the results of an advanced control design as well as a discussion of the requirements for automating both the structures and control design efforts for maneuvering a large spacecraft. The advanced control application addresses a general three dimensional slewing problem, and is applied to a large geostationary platform. The platform consists of two flexible antennas attached to the ends of a flexible truss. The control strategy involves an open-loop rigid body control profile which is derived from a nonlinear optimal control problem and provides the main control effort. A perturbation feedback control reduces the response due to the flexibility of the structure. Results are shown which demonstrate the usefulness of the approach. Software issues are considered for developing an integrated structures and control design environment.

Active member control of a precision structure with an H(infinity) performance objective

NASA Technical Reports Server (NTRS)

Fanson, J. L.; Chu, C.-C.; Smith, R. S.; Anderson, E. H.

1990-01-01

This paper addresses the noncollocated control of active structures using active structural elements. A top level architecture for active structures is presented, and issues pertaining to robust control of structures are discussed. Controllers optimized for an H sub inf performance specification are implemented on a test structure and the results are compared with analytical predictions. Directions for further research are identified.

Efficient control schemes with limited computation complexity for Tomographic AO systems on VLTs and ELTs

NASA Astrophysics Data System (ADS)

Petit, C.; Le Louarn, M.; Fusco, T.; Madec, P.-Y.

2011-09-01

Various tomographic control solutions have been proposed during the last decades to ensure efficient or even optimal closed-loop correction to tomographic Adaptive Optics (AO) concepts such as Laser Tomographic AO (LTAO), Multi-Conjugate AO (MCAO). The optimal solution, based on Linear Quadratic Gaussian (LQG) approach, as well as suboptimal but efficient solutions such as Pseudo-Open Loop Control (POLC) require multiple Matrix Vector Multiplications (MVM). Disregarding their respective performance, these efficient control solutions thus exhibit strong increase of on-line complexity and their implementation may become difficult in demanding cases. Among them, two cases are of particular interest. First, the system Real-Time Computer architecture and implementation is derived from past or present solutions and does not support multiple MVM. This is the case of the AO Facility which RTC architecture is derived from the SPARTA platform and inherits its simple MVM architecture, which does not fit with LTAO control solutions for instance. Second, considering future systems such as Extremely Large Telescopes, the number of degrees of freedom is twenty to one hundred times bigger than present systems. In these conditions, tomographic control solutions can hardly be used in their standard form and optimized implementation shall be considered. Single MVM tomographic control solutions represent a potential solution, and straightforward solutions such as Virtual Deformable Mirrors have been already proposed for LTAO but with tuning issues. We investigate in this paper the possibility to derive from tomographic control solutions, such as POLC or LQG, simplified control solutions ensuring simple MVM architecture and that could be thus implemented on nowadays systems or future complex systems. We theoretically derive various solutions and analyze their respective performance on various systems thanks to numerical simulation. We discuss the optimization of their performance and stability issues with respect to classic control solutions. We finally discuss off-line computation and implementation constraints.

Reduced Order Adaptive Controllers for Distributed Parameter Systems

DTIC Science & Technology

2005-09-01

pitch moment [J313. Neural Network adaptive output feedback control for intensive care unit sedation and intraop- erative anesthesia . Neural network...depth of anesthesia for noncardiac surgery [C3, J15]. These results present an extension of [C8, J9, J10]. Modelling and vibration control of...for Intensive Care Unit Sedation and Operating Room Hypnosis , Submitted to 6 Special Issue of SIAM Journal of Control and Optimization on Control

Market-based control strategy for long-span structures considering the multi-time delay issue

NASA Astrophysics Data System (ADS)

Li, Hongnan; Song, Jianzhu; Li, Gang

2017-01-01

To solve the different time delays that exist in the control device installed on spatial structures, in this study, discrete analysis using a 2 N precise algorithm was selected to solve the multi-time-delay issue for long-span structures based on the market-based control (MBC) method. The concept of interval mixed energy was introduced from computational structural mechanics and optimal control research areas, and it translates the design of the MBC multi-time-delay controller into a solution for the segment matrix. This approach transforms the serial algorithm in time to parallel computing in space, greatly improving the solving efficiency and numerical stability. The designed controller is able to consider the issue of time delay with a linear controlling force combination and is especially effective for large time-delay conditions. A numerical example of a long-span structure was selected to demonstrate the effectiveness of the presented controller, and the time delay was found to have a significant impact on the results.

Optimization of Process Parameters of Edge Robotic Deburring with Force Control

NASA Astrophysics Data System (ADS)

Burghardt, A.; Szybicki, D.; Kurc, K.; Muszyńska, M.

2016-12-01

The issues addressed in the paper present a part of the scientific research conducted within the framework of the automation of the aircraft engine part manufacturing processes. The results of the research presented in the article provided information in which tolerances while using a robotic control station with the option of force control we can make edge deburring.

Forest road erosion control using multiobjective optimization

Treesearch

Matthew Thompson; John Sessions; Kevin Boston; Arne Skaugset; David Tomberlin

2010-01-01

Forest roads are associated with accelerated erosion and can be a major source of sediment delivery to streams, which can degrade aquatic habitat. Controlling road-related erosion therefore remains an important issue for forest stewardship. Managers are faced with the task to develop efficient road management strategies to achieve conflicting environmental and economic...

Intelligent sensor in control systems for objects with changing thermophysical properties

NASA Astrophysics Data System (ADS)

Belousov, O. A.; Muromtsev, D. Yu; Belyaev, M. P.

2018-04-01

The control of heat devices in a wide temperature range given thermophysical properties of an object is a topical issue. Optimal control systems of electric furnaces have to meet strict requirements in terms of accuracy of production procedures and efficiency of energy consumption. The fulfillment of these requirements is possible only if the dynamics model describing adequately the processes occurring in the furnaces is used to calculate the optimal control actions. One of the types of electric furnaces is the electric chamber furnace intended for heat treatment of various materials at temperatures from thousands of degrees Celsius and above. To solve the above-mentioned problem and to determine its place in the system of energy-efficient control of dynamic modes in the electric furnace, we propose the concept of an intelligent sensor and a method of synthesizing variables on sets of functioning states. The use of synthesis algorithms for optimal control in real time ensures the required accuracy when operating under different conditions and operating modes of the electric chamber furnace.

Sound-field reproduction in-room using optimal control techniques: simulations in the frequency domain.

PubMed

Gauthier, Philippe-Aubert; Berry, Alain; Woszczyk, Wieslaw

2005-02-01

This paper describes the simulations and results obtained when applying optimal control to progressive sound-field reproduction (mainly for audio applications) over an area using multiple monopole loudspeakers. The model simulates a reproduction system that operates either in free field or in a closed space approaching a typical listening room, and is based on optimal control in the frequency domain. This rather simple approach is chosen for the purpose of physical investigation, especially in terms of sensing microphones and reproduction loudspeakers configurations. Other issues of interest concern the comparison with wave-field synthesis and the control mechanisms. The results suggest that in-room reproduction of sound field using active control can be achieved with a residual normalized squared error significantly lower than open-loop wave-field synthesis in the same situation. Active reproduction techniques have the advantage of automatically compensating for the room's natural dynamics. For the considered cases, the simulations show that optimal control results are not sensitive (in terms of reproduction error) to wall absorption in the reproduction room. A special surrounding configuration of sensors is introduced for a sensor-free listening area in free field.

Issues in the digital implementation of control compensators. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Moroney, P.

1979-01-01

Techniques developed for the finite-precision implementation of digital filters were used, adapted, and extended for digital feedback compensators, with particular emphasis on steady state, linear-quadratic-Gaussian compensators. Topics covered include: (1) the linear-quadratic-Gaussian problem; (2) compensator structures; (3) architectural issues: serialism, parallelism, and pipelining; (4) finite wordlength effects: quantization noise, quantizing the coefficients, and limit cycles; and (5) the optimization of structures.

Approximating the linear quadratic optimal control law for hereditary systems with delays in the control

NASA Technical Reports Server (NTRS)

Milman, Mark H.

1987-01-01

The fundamental control synthesis issue of establishing a priori convergence rates of approximation schemes for feedback controllers for a class of distributed parameter systems is addressed within the context of hereditary systems. Specifically, a factorization approach is presented for deriving approximations to the optimal feedback gains for the linear regulator-quadratic cost problem associated with time-varying functional differential equations with control delays. The approach is based on a discretization of the state penalty which leads to a simple structure for the feedback control law. General properties of the Volterra factors of Hilbert-Schmidt operators are then used to obtain convergence results for the controls, trajectories and feedback kernels. Two algorithms are derived from the basic approximation scheme, including a fast algorithm, in the time-invariant case. A numerical example is also considered.

Approximating the linear quadratic optimal control law for hereditary systems with delays in the control

NASA Technical Reports Server (NTRS)

Milman, Mark H.

1988-01-01

The fundamental control synthesis issue of establishing a priori convergence rates of approximation schemes for feedback controllers for a class of distributed parameter systems is addressed within the context of hereditary schemes. Specifically, a factorization approach is presented for deriving approximations to the optimal feedback gains for the linear regulator-quadratic cost problem associated with time-varying functional differential equations with control delays. The approach is based on a discretization of the state penalty which leads to a simple structure for the feedback control law. General properties of the Volterra factors of Hilbert-Schmidt operators are then used to obtain convergence results for the controls, trajectories and feedback kernels. Two algorithms are derived from the basic approximation scheme, including a fast algorithm, in the time-invariant case. A numerical example is also considered.

Energy Center Structure Optimization by using Smart Technologies in Process Control System

NASA Astrophysics Data System (ADS)

Shilkina, Svetlana V.

2018-03-01

The article deals with practical application of fuzzy logic methods in process control systems. A control object - agroindustrial greenhouse complex, which includes its own energy center - is considered. The paper analyzes object power supply options taking into account connection to external power grids and/or installation of own power generating equipment with various layouts. The main problem of a greenhouse facility basic process is extremely uneven power consumption, which forces to purchase redundant generating equipment idling most of the time, which quite negatively affects project profitability. Energy center structure optimization is largely based on solving the object process control system construction issue. To cut investor’s costs it was proposed to optimize power consumption by building an energy-saving production control system based on a fuzzy logic controller. The developed algorithm of automated process control system functioning ensured more even electric and thermal energy consumption, allowed to propose construction of the object energy center with a smaller number of units due to their more even utilization. As a result, it is shown how practical use of microclimate parameters fuzzy control system during object functioning leads to optimization of agroindustrial complex energy facility structure, which contributes to a significant reduction in object construction and operation costs.

Ultra-high enhancement of light focusing through disordered media controlled by mega-pixel modes (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yu, Hyeonseung; Lee, KyeoReh; Park, YongKeun

2017-02-01

Developing an efficient strategy for light focusing through scattering media is an important topic in the study of multiple light scattering. The enhancement factor of the light focusing, defined as the ratio between the optimized intensity and the background intensity is proportional to the number of controlling modes in a spatial light modulator (SLM). The demonstrated enhancement factors in previous studies are typically less than 1,000 due to several limiting factors, such as the slow refresh rate of a LCoS SLM, long optimization time, and lack of an efficient algorithm for high controlling modes. A digital micro-mirror device is an amplitude modulator, which is recently widely used for fast optimization through dynamic biological tissues. The fast frame rate of the DMD up to 16 kHz can also be exploited for increasing the number of controlling modes. However, the manipulation of large pattern data and efficient calculation of the optimized pattern remained as an issue. In this work, we demonstrate the enhancement factor more than 100,000 in focusing through scattering media by using 1 Mega controlling modes of a DMD. Through careful synchronization between a DMD, a photo-detector and an additional computer for parallel optimization, we achieved the unprecedented enhancement factor with 75 mins of the optimization time. We discuss the design principles of the system and the possible applications of the enhanced light focusing.

Self-entrainment to optimal gaits of an underactuated biomimetic swimming robot using adaptive frequency oscillators.

PubMed

Alessi, Alessio; Accoto, Dino; Guglielmelli, Eugenio

2015-08-01

Underactuated compliant swimming robots are characterized by a simple mechanical structure, capable to mimic the body undulation of many fish species. One of the design issue for these robots is the generation and control of best performing swimming gaits. In this paper we propose a new controller, based on AFO oscillators, to address this issue. After analyzing the effects of the motion on the robot natural frequencies, we show that the closed loop system is able to generate self-sustained oscillations, at a characteristic frequency, while maximizing swimming velocity.

Experimental design and multiple response optimization. Using the desirability function in analytical methods development.

PubMed

Candioti, Luciana Vera; De Zan, María M; Cámara, María S; Goicoechea, Héctor C

2014-06-01

A review about the application of response surface methodology (RSM) when several responses have to be simultaneously optimized in the field of analytical methods development is presented. Several critical issues like response transformation, multiple response optimization and modeling with least squares and artificial neural networks are discussed. Most recent analytical applications are presented in the context of analytLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, ArgentinaLaboratorio de Control de Calidad de Medicamentos (LCCM), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, C.C. 242, S3000ZAA Santa Fe, Argentinaical methods development, especially in multiple response optimization procedures using the desirability function. Copyright © 2014 Elsevier B.V. All rights reserved.

Optimal design of loudspeaker arrays for robust cross-talk cancellation using the Taguchi method and the genetic algorithm.

PubMed

Bai, Mingsian R; Tung, Chih-Wei; Lee, Chih-Chung

2005-05-01

An optimal design technique of loudspeaker arrays for cross-talk cancellation with application in three-dimensional audio is presented. An array focusing scheme is presented on the basis of the inverse propagation that relates the transducers to a set of chosen control points. Tikhonov regularization is employed in designing the inverse cancellation filters. An extensive analysis is conducted to explore the cancellation performance and robustness issues. To best compromise the performance and robustness of the cross-talk cancellation system, optimal configurations are obtained with the aid of the Taguchi method and the genetic algorithm (GA). The proposed systems are further justified by physical as well as subjective experiments. The results reveal that large number of loudspeakers, closely spaced configuration, and optimal control point design all contribute to the robustness of cross-talk cancellation systems (CCS) against head misalignment.

Optimal experience among teachers: new insights into the work paradox.

PubMed

Bassi, Marta; Delle Fave, Antonella

2012-01-01

Several studies highlighted that individuals perceive work as an opportunity for flow or optimal experience, but not as desirable and pleasant. This finding was defined as the work paradox. The present study addressed this issue among teachers from the perspective of self-determination theory, investigating work-related intrinsic and extrinsic motivation, as well as autonomous and controlled behavior regulation. In Study 1, 14 teachers were longitudinally monitored with Experience Sampling Method for one work week. In Study 2, 184 teachers were administered Flow Questionnaire and Work Preference Inventory, respectively investigating opportunities for optimal experience, and motivational orientations at work. Results showed that work-related optimal experiences were associated with both autonomous regulation and with controlled regulation. Moreover, teachers reported both intrinsic and extrinsic motivation at work, with a prevailing intrinsic orientation. Findings provide novel insights on the work paradox, and suggestions for teachers' well-being promotion.

Model-Based Battery Management Systems: From Theory to Practice

NASA Astrophysics Data System (ADS)

Pathak, Manan

Lithium-ion batteries are now extensively being used as the primary storage source. Capacity and power fade, and slow recharging times are key issues that restrict its use in many applications. Battery management systems are critical to address these issues, along with ensuring its safety. This dissertation focuses on exploring various control strategies using detailed physics-based electrochemical models developed previously for lithium-ion batteries, which could be used in advanced battery management systems. Optimal charging profiles for minimizing capacity fade based on SEI-layer formation are derived and the benefits of using such control strategies are shown by experimentally testing them on a 16 Ah NMC-based pouch cell. This dissertation also explores different time-discretization strategies for non-linear models, which gives an improved order of convergence for optimal control problems. Lastly, this dissertation also explores a physics-based model for predicting the linear impedance of a battery, and develops a freeware that is extremely robust and computationally fast. Such a code could be used for estimating transport, kinetic and material properties of the battery based on the linear impedance spectra.

Optimizing real-time Web-based user interfaces for observatories

NASA Astrophysics Data System (ADS)

Gibson, J. Duane; Pickering, Timothy E.; Porter, Dallan; Schaller, Skip

2008-08-01

In using common HTML/Ajax approaches for web-based data presentation and telescope control user interfaces at the MMT Observatory (MMTO), we rapidly were confronted with web browser performance issues. Much of the operational data at the MMTO is highly dynamic and is constantly changing during normal operations. Status of telescope subsystems must be displayed with minimal latency to telescope operators and other users. A major motivation of migrating toward web-based applications at the MMTO is to provide easy access to current and past observatory subsystem data for a wide variety of users on their favorite operating system through a familiar interface, their web browser. Performance issues, especially for user interfaces that control telescope subsystems, led to investigations of more efficient use of HTML/Ajax and web server technologies as well as other web-based technologies, such as Java and Flash/Flex. The results presented here focus on techniques for optimizing HTML/Ajax web applications with near real-time data display. This study indicates that direct modification of the contents or "nodeValue" attribute of text nodes is the most efficient method of updating data values displayed on a web page. Other optimization techniques are discussed for web-based applications that display highly dynamic data.

Optimal control of the signal-to-noise ratio per unit time of a spin 1/2 particle: The crusher gradient and the radiation damping cases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lapert, M.; Glaser, S. J.; Assémat, E.

We show to which extent the signal to noise ratio per unit time of a spin 1/2 particle can be maximized. We consider a cyclic repetition of experiments made of a measurement followed by a radio-frequency magnetic field excitation of the system, in the case of unbounded amplitude. In the periodic regime, the objective of the control problem is to design the initial state of the system and the pulse sequence which leads to the best signal to noise performance. We focus on two specific issues relevant in nuclear magnetic resonance, the crusher gradient and the radiation damping cases. Optimalmore » control techniques are used to solve this non-standard control problem. We discuss the optimality of the Ernst angle solution, which is commonly applied in spectroscopic and medical imaging applications. In the radiation damping situation, we show that in some cases, the optimal solution differs from the Ernst one.« less

Common foundations of optimal control across the sciences: evidence of a free lunch

NASA Astrophysics Data System (ADS)

Russell, Benjamin; Rabitz, Herschel

2017-03-01

A common goal in the sciences is optimization of an objective function by selecting control variables such that a desired outcome is achieved. This scenario can be expressed in terms of a control landscape of an objective considered as a function of the control variables. At the most basic level, it is known that the vast majority of quantum control landscapes possess no traps, whose presence would hinder reaching the objective. This paper reviews and extends the quantum control landscape assessment, presenting evidence that the same highly favourable landscape features exist in many other domains of science. The implications of this broader evidence are discussed. Specifically, control landscape examples from quantum mechanics, chemistry and evolutionary biology are presented. Despite the obvious differences, commonalities between these areas are highlighted within a unified mathematical framework. This mathematical framework is driven by the wide-ranging experimental evidence on the ease of finding optimal controls (in terms of the required algorithmic search effort beyond the laboratory set-up overhead). The full scope and implications of this observed common control behaviour pose an open question for assessment in further work. This article is part of the themed issue 'Horizons of cybernetical physics'.

Optimal case-control matching in practice.

PubMed

Cologne, J B; Shibata, Y

1995-05-01

We illustrate modern matching techniques and discuss practical issues in defining the closeness of matching for retrospective case-control designs (in which the pool of subjects already exists when the study commences). We empirically compare matching on a balancing score, analogous to the propensity score for treated/control matching, with matching on a weighted distance measure. Although both methods in principle produce balance between cases and controls in the marginal distributions of the matching covariates, the weighted distance measure provides better balance in practice because the balancing score can be poorly estimated. We emphasize the use of optimal matching based on efficient network algorithms. An illustration is based on the design of a case-control study of hepatitis B virus infection as a possible confounder and/or effect modifier of radiation-related primary liver cancer in atomic bomb survivors.

Enabling Controlling Complex Networks with Local Topological Information.

PubMed

Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

2018-03-15

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

Minimal complexity control law synthesis

NASA Technical Reports Server (NTRS)

Bernstein, Dennis S.; Haddad, Wassim M.; Nett, Carl N.

1989-01-01

A paradigm for control law design for modern engineering systems is proposed: Minimize control law complexity subject to the achievement of a specified accuracy in the face of a specified level of uncertainty. Correspondingly, the overall goal is to make progress towards the development of a control law design methodology which supports this paradigm. Researchers achieve this goal by developing a general theory of optimal constrained-structure dynamic output feedback compensation, where here constrained-structure means that the dynamic-structure (e.g., dynamic order, pole locations, zero locations, etc.) of the output feedback compensation is constrained in some way. By applying this theory in an innovative fashion, where here the indicated iteration occurs over the choice of the compensator dynamic-structure, the paradigm stated above can, in principle, be realized. The optimal constrained-structure dynamic output feedback problem is formulated in general terms. An elegant method for reducing optimal constrained-structure dynamic output feedback problems to optimal static output feedback problems is then developed. This reduction procedure makes use of star products, linear fractional transformations, and linear fractional decompositions, and yields as a byproduct a complete characterization of the class of optimal constrained-structure dynamic output feedback problems which can be reduced to optimal static output feedback problems. Issues such as operational/physical constraints, operating-point variations, and processor throughput/memory limitations are considered, and it is shown how anti-windup/bumpless transfer, gain-scheduling, and digital processor implementation can be facilitated by constraining the controller dynamic-structure in an appropriate fashion.

Power Allocation and Outage Probability Analysis for SDN-based Radio Access Networks

NASA Astrophysics Data System (ADS)

Zhao, Yongxu; Chen, Yueyun; Mai, Zhiyuan

2018-01-01

In this paper, performance of Access network Architecture based SDN (Software Defined Network) is analyzed with respect to the power allocation issue. A power allocation scheme PSO-PA (Particle Swarm Optimization-power allocation) algorithm is proposed, the proposed scheme is subjected to constant total power with the objective of minimizing system outage probability. The entire access network resource configuration is controlled by the SDN controller, then it sends the optimized power distribution factor to the base station source node (SN) and the relay node (RN). Simulation results show that the proposed scheme reduces the system outage probability at a low complexity.

78 FR 1206 - Notice of Intent To Grant Exclusive Patent License; Allied Communications, LLC

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-08

... Development, Navy Case No. 99,766, filed December 30, 2009.//U.S. Patent No. 8,238,924: Real-Time Optimization... U.S. Patent No. 7,685,207: Adaptive Web- Based Asset Control System, Navy Case No. 83634, issued...

Joint U.S./Japan Conference on Adaptive Structures, 1st, Maui, HI, Nov. 13-15, 1990, Proceedings

NASA Technical Reports Server (NTRS)

Wada, Ben K. (Editor); Fanson, James L. (Editor); Miura, Koryo (Editor)

1991-01-01

The present volume of adaptive structures discusses the development of control laws for an orbiting tethered antenna/reflector system test scale model, the sizing of active piezoelectric struts for vibration suppression on a space-based interferometer, the control design of a space station mobile transporter with multiple constraints, and optimum configuration control of an intelligent truss structure. Attention is given to the formulation of full state feedback for infinite order structural systems, robustness issues in the design of smart structures, passive piezoelectric vibration damping, shape control experiments with a functional model for large optical reflectors, and a mathematical basis for the design optimization of adaptive trusses in precision control. Topics addressed include approaches to the optimal adaptive geometries of intelligent truss structures, the design of an automated manufacturing system for tubular smart structures, the Sandia structural control experiments, and the zero-gravity dynamics of space structures in parabolic aircraft flight.

Joint U.S./Japan Conference on Adaptive Structures, 1st, Maui, HI, Nov. 13-15, 1990, Proceedings

NASA Astrophysics Data System (ADS)

Wada, Ben K.; Fanson, James L.; Miura, Koryo

1991-11-01

The present volume of adaptive structures discusses the development of control laws for an orbiting tethered antenna/reflector system test scale model, the sizing of active piezoelectric struts for vibration suppression on a space-based interferometer, the control design of a space station mobile transporter with multiple constraints, and optimum configuration control of an intelligent truss structure. Attention is given to the formulation of full state feedback for infinite order structural systems, robustness issues in the design of smart structures, passive piezoelectric vibration damping, shape control experiments with a functional model for large optical reflectors, and a mathematical basis for the design optimization of adaptive trusses in precision control. Topics addressed include approaches to the optimal adaptive geometries of intelligent truss structures, the design of an automated manufacturing system for tubular smart structures, the Sandia structural control experiments, and the zero-gravity dynamics of space structures in parabolic aircraft flight.

Evidence for composite cost functions in arm movement planning: an inverse optimal control approach.

PubMed

Berret, Bastien; Chiovetto, Enrico; Nori, Francesco; Pozzo, Thierry

2011-10-01

An important issue in motor control is understanding the basic principles underlying the accomplishment of natural movements. According to optimal control theory, the problem can be stated in these terms: what cost function do we optimize to coordinate the many more degrees of freedom than necessary to fulfill a specific motor goal? This question has not received a final answer yet, since what is optimized partly depends on the requirements of the task. Many cost functions were proposed in the past, and most of them were found to be in agreement with experimental data. Therefore, the actual principles on which the brain relies to achieve a certain motor behavior are still unclear. Existing results might suggest that movements are not the results of the minimization of single but rather of composite cost functions. In order to better clarify this last point, we consider an innovative experimental paradigm characterized by arm reaching with target redundancy. Within this framework, we make use of an inverse optimal control technique to automatically infer the (combination of) optimality criteria that best fit the experimental data. Results show that the subjects exhibited a consistent behavior during each experimental condition, even though the target point was not prescribed in advance. Inverse and direct optimal control together reveal that the average arm trajectories were best replicated when optimizing the combination of two cost functions, nominally a mix between the absolute work of torques and the integrated squared joint acceleration. Our results thus support the cost combination hypothesis and demonstrate that the recorded movements were closely linked to the combination of two complementary functions related to mechanical energy expenditure and joint-level smoothness.

Implications of optimization cost for balancing exploration and exploitation in global search and for experimental optimization

NASA Astrophysics Data System (ADS)

Chaudhuri, Anirban

Global optimization based on expensive and time consuming simulations or experiments usually cannot be carried out to convergence, but must be stopped because of time constraints, or because the cost of the additional function evaluations exceeds the benefits of improving the objective(s). This dissertation sets to explore the implications of such budget and time constraints on the balance between exploration and exploitation and the decision of when to stop. Three different aspects are considered in terms of their effects on the balance between exploration and exploitation: 1) history of optimization, 2) fixed evaluation budget, and 3) cost as a part of objective function. To this end, this research develops modifications to the surrogate-based optimization technique, Efficient Global Optimization algorithm, that controls better the balance between exploration and exploitation, and stopping criteria facilitated by these modifications. Then the focus shifts to examining experimental optimization, which shares the issues of cost and time constraints. Through a study on optimization of thrust and power for a small flapping wing for micro air vehicles, important differences and similarities between experimental and simulation-based optimization are identified. The most important difference is that reduction of noise in experiments becomes a major time and cost issue, and a second difference is that parallelism as a way to cut cost is more challenging. The experimental optimization reveals the tendency of the surrogate to display optimistic bias near the surrogate optimum, and this tendency is then verified to also occur in simulation based optimization.

Dendritic cells for active immunotherapy: optimizing design and manufacture in order to develop commercially and clinically viable products.

PubMed

Nicolette, C A; Healey, D; Tcherepanova, I; Whelton, P; Monesmith, T; Coombs, L; Finke, L H; Whiteside, T; Miesowicz, F

2007-09-27

Dendritic cell (DC) active immunotherapy is potentially efficacious in a broad array of malignant disease settings. However, challenges remain in optimizing DC-based therapy for maximum clinical efficacy within manufacturing processes that permit quality control and scale-up of consistent products. In this review we discuss the critical issues that must be addressed in order to optimize DC-based product design and manufacture, and highlight the DC based platforms currently addressing these issues. Variables in DC-based product design include the type of antigenic payload used, DC maturation steps and activation processes, and functional assays. Issues to consider in development include: (a) minimizing the invasiveness of patient biological material collection; (b) minimizing handling and manipulations of tissue at the clinical site; (c) centralized product manufacturing and standardized processing and capacity for commercial-scale production; (d) rapid product release turnaround time; (e) the ability to manufacture sufficient product from limited starting material; and (f) standardized release criteria for DC phenotype and function. Improvements in the design and manufacture of DC products have resulted in a handful of promising leads currently in clinical development.

Optimal Control of Fully Routed Air Traffic in the Presence of Uncertainty and Kinodynamic Constraints

DTIC Science & Technology

2014-09-18

Operations and Developing Issues . . . . . . . . . . . . . . . . . . 6 2.1.2 Next-Generation Air Transportation System (NextGen...Air Traffic Management ESP Euclidean Shortest Path FAA Federal Aviation Administration FCFS First-Come-First-Served HCS Hybrid Control System KKT...Karush-Kuhn-Tucker LGR Legendre-Gauss-Radau MLD Minimum Lateral Distance NAS National Airspace System NASA National Aeronautics and Space Administration

A roadmap for optimal control: the right way to commute.

PubMed

Ross, I Michael

2005-12-01

Optimal control theory is the foundation for many problems in astrodynamics. Typical examples are trajectory design and optimization, relative motion control of distributed space systems and attitude steering. Many such problems in astrodynamics are solved by an alternative route of mathematical analysis and deep physical insight, in part because of the perception that an optimal control framework generates hard problems. Although this is indeed true of the Bellman and Pontryagin frameworks, the covector mapping principle provides a neoclassical approach that renders hard problems easy. That is, although the origins of this philosophy can be traced back to Bernoulli and Euler, it is essentially modern as a result of the strong linkage between approximation theory, set-valued analysis and computing technology. Motivated by the broad success of this approach, mission planners are now conceiving and demanding higher performance from space systems. This has resulted in new set of theoretical and computational problems. Recently, under the leadership of NASA-GRC, several workshops were held to address some of these problems. This paper outlines the theoretical issues stemming from practical problems in astrodynamics. Emphasis is placed on how it pertains to advanced mission design problems.

Fourier transform and particle swarm optimization based modified LQR algorithm for mitigation of vibrations using magnetorheological dampers

NASA Astrophysics Data System (ADS)

Kumar, Gaurav; Kumar, Ashok

2017-11-01

Structural control has gained significant attention in recent times. The standalone issue of power requirement during an earthquake has already been solved up to a large extent by designing semi-active control systems using conventional linear quadratic control theory, and many other intelligent control algorithms such as fuzzy controllers, artificial neural networks, etc. In conventional linear-quadratic regulator (LQR) theory, it is customary to note that the values of the design parameters are decided at the time of designing the controller and cannot be subsequently altered. During an earthquake event, the response of the structure may increase or decrease, depending the quasi-resonance occurring between the structure and the earthquake. In this case, it is essential to modify the value of the design parameters of the conventional LQR controller to obtain optimum control force to mitigate the vibrations due to the earthquake. A few studies have been done to sort out this issue but in all these studies it was necessary to maintain a database of the earthquake. To solve this problem and to find the optimized design parameters of the LQR controller in real time, a fast Fourier transform and particle swarm optimization based modified linear quadratic regulator method is presented here. This method comprises four different algorithms: particle swarm optimization (PSO), the fast Fourier transform (FFT), clipped control algorithm and the LQR. The FFT helps to obtain the dominant frequency for every time window. PSO finds the optimum gain matrix through the real-time update of the weighting matrix R, thereby, dispensing with the experimentation. The clipped control law is employed to match the magnetorheological (MR) damper force with the desired force given by the controller. The modified Bouc-Wen phenomenological model is taken to recognize the nonlinearities in the MR damper. The assessment of the advised method is done by simulation of a three-story structure having an MR damper at the ground floor level subjected to three different near-fault historical earthquake time histories, and the outcomes are equated with those of simple conventional LQR. The results establish that the advised methodology is more effective than conventional LQR controllers in reducing inter-storey drift, relative displacement, and acceleration response.

Optimal control of native predators

USGS Publications Warehouse

Martin, Julien; O'Connell, Allan F.; Kendall, William L.; Runge, Michael C.; Simons, Theodore R.; Waldstein, Arielle H.; Schulte, Shiloh A.; Converse, Sarah J.; Smith, Graham W.; Pinion, Timothy; Rikard, Michael; Zipkin, Elise F.

2010-01-01

We apply decision theory in a structured decision-making framework to evaluate how control of raccoons (Procyon lotor), a native predator, can promote the conservation of a declining population of American Oystercatchers (Haematopus palliatus) on the Outer Banks of North Carolina. Our management objective was to maintain Oystercatcher productivity above a level deemed necessary for population recovery while minimizing raccoon removal. We evaluated several scenarios including no raccoon removal, and applied an adaptive optimization algorithm to account for parameter uncertainty. We show how adaptive optimization can be used to account for uncertainties about how raccoon control may affect Oystercatcher productivity. Adaptive management can reduce this type of uncertainty and is particularly well suited for addressing controversial management issues such as native predator control. The case study also offers several insights that may be relevant to the optimal control of other native predators. First, we found that stage-specific removal policies (e.g., yearling versus adult raccoon removals) were most efficient if the reproductive values among stage classes were very different. Second, we found that the optimal control of raccoons would result in higher Oystercatcher productivity than the minimum levels recommended for this species. Third, we found that removing more raccoons initially minimized the total number of removals necessary to meet long term management objectives. Finally, if for logistical reasons managers cannot sustain a removal program by removing a minimum number of raccoons annually, managers may run the risk of creating an ecological trap for Oystercatchers.

Parameter Estimation of Fractional-Order Chaotic Systems by Using Quantum Parallel Particle Swarm Optimization Algorithm

PubMed Central

Huang, Yu; Guo, Feng; Li, Yongling; Liu, Yufeng

2015-01-01

Parameter estimation for fractional-order chaotic systems is an important issue in fractional-order chaotic control and synchronization and could be essentially formulated as a multidimensional optimization problem. A novel algorithm called quantum parallel particle swarm optimization (QPPSO) is proposed to solve the parameter estimation for fractional-order chaotic systems. The parallel characteristic of quantum computing is used in QPPSO. This characteristic increases the calculation of each generation exponentially. The behavior of particles in quantum space is restrained by the quantum evolution equation, which consists of the current rotation angle, individual optimal quantum rotation angle, and global optimal quantum rotation angle. Numerical simulation based on several typical fractional-order systems and comparisons with some typical existing algorithms show the effectiveness and efficiency of the proposed algorithm. PMID:25603158

Motion-Based Piloted Simulation Evaluation of a Control Allocation Technique to Recover from Pilot Induced Oscillations

NASA Technical Reports Server (NTRS)

Craun, Robert W.; Acosta, Diana M.; Beard, Steven D.; Leonard, Michael W.; Hardy, Gordon H.; Weinstein, Michael; Yildiz, Yildiray

2013-01-01

This paper describes the maturation of a control allocation technique designed to assist pilots in the recovery from pilot induced oscillations (PIOs). The Control Allocation technique to recover from Pilot Induced Oscillations (CAPIO) is designed to enable next generation high efficiency aircraft designs. Energy efficient next generation aircraft require feedback control strategies that will enable lowering the actuator rate limit requirements for optimal airframe design. One of the common issues flying with actuator rate limits is PIOs caused by the phase lag between the pilot inputs and control surface response. CAPIO utilizes real-time optimization for control allocation to eliminate phase lag in the system caused by control surface rate limiting. System impacts of the control allocator were assessed through a piloted simulation evaluation of a non-linear aircraft simulation in the NASA Ames Vertical Motion Simulator. Results indicate that CAPIO helps reduce oscillatory behavior, including the severity and duration of PIOs, introduced by control surface rate limiting.

Adaptive control for solar energy based DC microgrid system development

NASA Astrophysics Data System (ADS)

Zhang, Qinhao

During the upgrading of current electric power grid, it is expected to develop smarter, more robust and more reliable power systems integrated with distributed generations. To realize these objectives, traditional control techniques are no longer effective in either stabilizing systems or delivering optimal and robust performances. Therefore, development of advanced control methods has received increasing attention in power engineering. This work addresses two specific problems in the control of solar panel based microgrid systems. First, a new control scheme is proposed for the microgrid systems to achieve optimal energy conversion ratio in the solar panels. The control system can optimize the efficiency of the maximum power point tracking (MPPT) algorithm by implementing two layers of adaptive control. Such a hierarchical control architecture has greatly improved the system performance, which is validated through both mathematical analysis and computer simulation. Second, in the development of the microgrid transmission system, the issues related to the tele-communication delay and constant power load (CPL)'s negative incremental impedance are investigated. A reference model based method is proposed for pole and zero placements that address the challenges of the time delay and CPL in closed-loop control. The effectiveness of the proposed modeling and control design methods are demonstrated in a simulation testbed. Practical aspects of the proposed methods for general microgrid systems are also discussed.

2011 Quantum Control of Light & Matter Gordon Research Conference (July 31-August 5, 2011, Mount Holyoke College, South Hadley, MA)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas Weinacht

2011-08-05

Quantum control of light and matter is the quest to steer a physical process to a desirable outcome, employing constructive and destructive interference. Three basic questions address feasibility of quantum control: (1) The problem of controllability, does a control field exist for a preset initial and target state; (2) Synthesis, constructively finding the field that leads to the target; and (3) Optimal Control Theory - optimizing the field that carries out this task. These continue to be the fundamental theoretical questions to be addressed in the conference. How to realize control fields in the laboratory is an ongoing challenge. Thismore » task is very diverse viewing the emergence of control scenarios ranging from attoseconds to microseconds. How do the experimental observations reflect on the theoretical framework? The typical arena of quantum control is an open environment where much of the control is indirect. How are control scenarios realized in dissipative open systems? Can new control opportunities emerge? Can one null decoherence effects? An ideal setting for control is ultracold matter. The initial and final state can be defined more precisely. Coherent control unifies many fields of physical science. A lesson learned in one field can reflect on another. Currently quantum information processing has emerged as a primary target of control where the key issue is controlling quantum gate operation. Modern nonlinear spectroscopy has emerged as another primary field. The challenge is to unravel the dynamics of molecular systems undergoing strong interactions with the environment. Quantum optics where non-classical fields are to be generated and employed. Finally, coherent control is the basis for quantum engineering. These issues will be under the limelight of the Gordon conference on Quantum Control of Light and Matter.« less

Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms

PubMed Central

Hu, Haigen; Xu, Lihong; Wei, Ruihua; Zhu, Bingkun

2011-01-01

This paper investigates the issue of tuning the Proportional Integral and Derivative (PID) controller parameters for a greenhouse climate control system using an Evolutionary Algorithm (EA) based on multiple performance measures such as good static-dynamic performance specifications and the smooth process of control. A model of nonlinear thermodynamic laws between numerous system variables affecting the greenhouse climate is formulated. The proposed tuning scheme is tested for greenhouse climate control by minimizing the integrated time square error (ITSE) and the control increment or rate in a simulation experiment. The results show that by tuning the gain parameters the controllers can achieve good control performance through step responses such as small overshoot, fast settling time, and less rise time and steady state error. Besides, it can be applied to tuning the system with different properties, such as strong interactions among variables, nonlinearities and conflicting performance criteria. The results implicate that it is a quite effective and promising tuning method using multi-objective optimization algorithms in the complex greenhouse production. PMID:22163927

Stereotactic radiosurgery alone for multiple brain metastases? A review of clinical and technical issues

PubMed Central

Ruschin, Mark; Ma, Lijun; Verbakel, Wilko; Larson, David; Brown, Paul D.

2017-01-01

Abstract Over the past three decades several randomized trials have enabled evidence-based practice for patients presenting with limited brain metastases. These trials have focused on the role of surgery or stereotactic radiosurgery (SRS) with or without whole brain radiation therapy (WBRT). As a result, it is clear that local control should be optimized with surgery or SRS in patients with optimal prognostic factors presenting with up to 4 brain metastases. The routine use of adjuvant WBRT remains debatable, as although greater distant brain control rates are observed, there is no impact on survival, and modern outcomes suggest adverse effects from WBRT on patient cognition and quality of life. With dramatic technologic advances in radiation oncology facilitating the adoption of SRS into mainstream practice, the optimal management of patients with multiple brain metastases is now being put forward. Practice is evolving to SRS alone in these patients despite a lack of level 1 evidence to support a clinical departure from WBRT. The purpose of this review is to summarize the current state of the evidence for patients presenting with limited and multiple metastases, and to present an in-depth analysis of the technology and dosimetric issues specific to the treatment of multiple metastases. PMID:28380635

Optimization of MBR hydrodynamics for cake layer fouling control through CFD simulation and RSM design.

PubMed

Yang, Min; Yu, Dawei; Liu, Mengmeng; Zheng, Libing; Zheng, Xiang; Wei, Yuansong; Wang, Fang; Fan, Yaobo

2017-03-01

Membrane fouling is an important issue for membrane bioreactor (MBR) operation. This paper aims at the investigation and the controlling of reversible membrane fouling due to cake layer formation and foulants deposition by optimizing MBR hydrodynamics through the combination of computational fluid dynamics (CFD) and design of experiment (DOE). The model was validated by comparing simulations with measurements of liquid velocity and dissolved oxygen (DO) concentration in a lab-scale submerged MBR. The results demonstrated that the sludge concentration is the most influencing for responses including shear stress, particle deposition propensity (PDP), sludge viscosity and strain rate. A medium sludge concentration of 8820mgL -1 is optimal for the reduction of reversible fouling in this submerged MBR. The bubble diameter is more decisive than air flowrate for membrane shear stress due to its role in sludge viscosity. The optimal bubble diameter was at around 4.8mm for both of shear stress and PDP. Copyright © 2016 Elsevier Ltd. All rights reserved.

Anaerobic digestion of food waste: A review focusing on process stability.

PubMed

Li, Lei; Peng, Xuya; Wang, Xiaoming; Wu, Di

2018-01-01

Food waste (FW) is rich in biomass energy, and increasing numbers of national programs are being established to recover energy from FW using anaerobic digestion (AD). However process instability is a common operational issue for AD of FW. Process monitoring and control as well as microbial management can be used to control instability and increase the energy conversion efficiency of anaerobic digesters. Here, we review research progress related to these methods and identify existing limitations to efficient AD; recommendations for future research are also discussed. Process monitoring and control are suitable for evaluating the current operational status of digesters, whereas microbial management can facilitate early diagnosis and process optimization. Optimizing and combining these two methods are necessary to improve AD efficiency. Copyright © 2017 Elsevier Ltd. All rights reserved.

Issues for the Traveling Team Physician.

PubMed

Kaeding, Christopher C; Borchers, James

2016-07-01

This article outlines the value of having the team physician traveling with athletes to away venues for competitions or training sessions. At present, this travel presents several issues for the team physician who crosses state lines for taking care of the athletes. In this article, these issues and their possible remedies are discussed. A concern for the travelling team physician is practicing medicine while caring for the team in a state where the physician is not licensed. Another issue can be the transportation of controlled substances in the course of providing optimal care for the team athletes. These two issues are regulatory and legislative issues at both the state and federal levels. On the practical side of being a team physician, the issues of emergency action plans, supplies, and when to transport injured or ill patients are also reviewed. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Information support for decision making on dispatching control of water distribution in irrigation

NASA Astrophysics Data System (ADS)

Yurchenko, I. F.

2018-05-01

The research has been carried out on developing the technique of supporting decision making for on-line control, operational management of water allocation for the interfarm irrigation projects basing on the analytical patterns of dispatcher control. This technique provides an increase of labour productivity as well as higher management quality due to the improved level of automation, as well as decision making optimization taking into account diagnostics of the issues, solutions classification, information being required to the decision makers.

An efficient and accurate solution methodology for bilevel multi-objective programming problems using a hybrid evolutionary-local-search algorithm.

PubMed

Deb, Kalyanmoy; Sinha, Ankur

2010-01-01

Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.

Research and application of an intelligent control system in central air-conditioning based on energy consumption simulation

NASA Astrophysics Data System (ADS)

Cao, Ling; Che, Wenbin

2018-05-01

For the central air-conditioning energy-saving, it is common practice to use a wide range of PTD controllers in engineering to optimize energy savings. However, the shortcomings of the PTD controller have also been magnified on this issue, such as: calculation accuracy is not enough, the calculation time is too long. Particle swarm optimization has the advantage of fast convergence. This paper is based on Particle Swarm Optimization apply in PTD controller tuning parameters in order to achieve the purpose of saving energy while ensuring comfort. The algorithm proposed in this paper can adjust the weight according to the change of population fitness, reduce the weights of particles with lower fitness and enhance the weights of particles with higher fitness in the population, and fully release the population vitality. The method in this paper is validated by the TRNSYS model based on the central air-conditioning system. The experimental results show that the room temperature fluctuation is small, the overshoot is small, the adjustment speed is fast, and the energy-saving fluctuates at 10%.

Optimal control issues in plant disease with host demographic factor and botanical fungicides

NASA Astrophysics Data System (ADS)

Anggriani, N.; Mardiyah, M.; Istifadah, N.; Supriatna, A. K.

2018-03-01

In this paper, we discuss a mathematical model of plant disease with the effect of fungicide. We assume that the fungicide is given as a preventive treatment to infectious plants. The model is constructed based on the development of the disease in which the monomolecular is monocyclic. We show the value of the Basic Reproduction Number (BRN) ℛ0 of the plant disease transmission. The BRN is computed from the largest eigenvalue of the next generation matrix of the model. The result shows that in the region where ℛ0 greater than one there is a single stable endemic equilibrium. However, in the region where ℛ0 less than one this endemic equilibrium becomes unstable. The dynamics of the model is highly sensitive to changes in contact rate and infectious period. We also discuss the optimal control of the infected plant host by considering a preventive treatment aimed at reducing the infected host plant. The obtaining optimal control shows that it can reduce the number of infected hosts compared to that without control. Some numerical simulations are also given to illustrate our analytical results.

Two Archetypes of Motor Control Research.

PubMed

Latash, Mark L

2010-07-01

This reply to the Commentaries is focused on two archetypes of motor control research, one based on physics and physiology and the other based on control theory and ideas of neural computations. The former approach, represented by the equilibrium-point hypothesis, strives to discover the physical laws and salient physiological variables that make purposeful coordinated movements possible. The latter approach, represented by the ideas of internal models and optimal control, tries to apply methods of control developed for man-made inanimate systems to the human body. Specific issues related to control with subthreshold membrane depolarization, motor redundancy, and the idea of synergies are briefly discussed.

Design Optimization Tool for Synthetic Jet Actuators Using Lumped Element Modeling

NASA Technical Reports Server (NTRS)

Gallas, Quentin; Sheplak, Mark; Cattafesta, Louis N., III; Gorton, Susan A. (Technical Monitor)

2005-01-01

The performance specifications of any actuator are quantified in terms of an exhaustive list of parameters such as bandwidth, output control authority, etc. Flow-control applications benefit from a known actuator frequency response function that relates the input voltage to the output property of interest (e.g., maximum velocity, volumetric flow rate, momentum flux, etc.). Clearly, the required performance metrics are application specific, and methods are needed to achieve the optimal design of these devices. Design and optimization studies have been conducted for piezoelectric cantilever-type flow control actuators, but the modeling issues are simpler compared to synthetic jets. Here, lumped element modeling (LEM) is combined with equivalent circuit representations to estimate the nonlinear dynamic response of a synthetic jet as a function of device dimensions, material properties, and external flow conditions. These models provide reasonable agreement between predicted and measured frequency response functions and thus are suitable for use as design tools. In this work, we have developed a Matlab-based design optimization tool for piezoelectric synthetic jet actuators based on the lumped element models mentioned above. Significant improvements were achieved by optimizing the piezoceramic diaphragm dimensions. Synthetic-jet actuators were fabricated and benchtop tested to fully document their behavior and validate a companion optimization effort. It is hoped that the tool developed from this investigation will assist in the design and deployment of these actuators.

Nonlinear Model Predictive Control for Cooperative Control and Estimation

NASA Astrophysics Data System (ADS)

Ru, Pengkai

Recent advances in computational power have made it possible to do expensive online computations for control systems. It is becoming more realistic to perform computationally intensive optimization schemes online on systems that are not intrinsically stable and/or have very small time constants. Being one of the most important optimization based control approaches, model predictive control (MPC) has attracted a lot of interest from the research community due to its natural ability to incorporate constraints into its control formulation. Linear MPC has been well researched and its stability can be guaranteed in the majority of its application scenarios. However, one issue that still remains with linear MPC is that it completely ignores the system's inherent nonlinearities thus giving a sub-optimal solution. On the other hand, if achievable, nonlinear MPC, would naturally yield a globally optimal solution and take into account all the innate nonlinear characteristics. While an exact solution to a nonlinear MPC problem remains extremely computationally intensive, if not impossible, one might wonder if there is a middle ground between the two. We tried to strike a balance in this dissertation by employing a state representation technique, namely, the state dependent coefficient (SDC) representation. This new technique would render an improved performance in terms of optimality compared to linear MPC while still keeping the problem tractable. In fact, the computational power required is bounded only by a constant factor of the completely linearized MPC. The purpose of this research is to provide a theoretical framework for the design of a specific kind of nonlinear MPC controller and its extension into a general cooperative scheme. The controller is designed and implemented on quadcopter systems.

Control landscapes are almost always trap free: a geometric assessment

NASA Astrophysics Data System (ADS)

Russell, Benjamin; Rabitz, Herschel; Wu, Re-Bing

2017-05-01

A proof is presented that almost all closed, finite dimensional quantum systems have trap free (i.e. free from local optima) landscapes for a large and physically general class of circumstances, which includes qubit evolutions in quantum computing. This result offers an explanation for why gradient-based methods succeed so frequently in quantum control. The role of singular controls is analyzed using geometric tools in the case of the control of the propagator, and thus in the case of observables as well. Singular controls have been implicated as a source of landscape traps. The conditions under which singular controls can introduce traps, and thus interrupt the progress of a control optimization, are discussed and a geometrical characterization of the issue is presented. It is shown that a control being singular is not sufficient to cause control optimization progress to halt, and sufficient conditions for a trap free landscape are presented. It is further shown that the local surjectivity (full rank) assumption of landscape analysis can be refined to the condition that the end-point map is transverse to each of the level sets of the fidelity function. This mild condition is shown to be sufficient for a quantum system’s landscape to be trap free. The control landscape is shown to be trap free for all but a null set of Hamiltonians using a geometric technique based on the parametric transversality theorem. Numerical evidence confirming this analysis is also presented. This new result is the analogue of the work of Altifini, wherein it was shown that controllability holds for all but a null set of quantum systems in the dipole approximation. These collective results indicate that the availability of adequate control resources remains the most physically relevant issue for achieving high fidelity control performance while also avoiding landscape traps.

Advanced model-based FDIR techniques for aerospace systems: Today challenges and opportunities

NASA Astrophysics Data System (ADS)

Zolghadri, Ali

2012-08-01

This paper discusses some trends and recent advances in model-based Fault Detection, Isolation and Recovery (FDIR) for aerospace systems. The FDIR challenges range from pre-design and design stages for upcoming and new programs, to improvement of the performance of in-service flying systems. For space missions, optimization of flight conditions and safe operation is intrinsically related to GNC (Guidance, Navigation & Control) system of the spacecraft and includes sensors and actuators monitoring. Many future space missions will require autonomous proximity operations including fault diagnosis and the subsequent control and guidance recovery actions. For upcoming and future aircraft, one of the main issues is how early and robust diagnosis of some small and subtle faults could contribute to the overall optimization of aircraft design. This issue would be an important factor for anticipating the more and more stringent requirements which would come in force for future environmentally-friendlier programs. The paper underlines the reasons for a widening gap between the advanced scientific FDIR methods being developed by the academic community and technological solutions demanded by the aerospace industry.

Optimistic expectations in early marriage: a resource or vulnerability for adaptive relationship functioning?

PubMed

Neff, Lisa A; Geers, Andrew L

2013-07-01

Do optimistic expectations facilitate or hinder adaptive responses to relationship challenges? Traditionally, optimism has been characterized as a resource that encourages positive coping efforts within relationships. Yet, some work suggests optimism can be a liability, as expecting the best may prevent individuals from taking proactive steps when confronted with difficulties. To reconcile these perspectives, the current article argues that greater attention must be given to the way in which optimistic expectancies are conceptualized. Whereas generalized dispositional optimism may predict constructive responses to relationship difficulties, more focused relationship-specific forms of optimism may predict poor coping responses. A multi-method, longitudinal study of newly married couples confirmed that spouses higher in dispositional optimism (a) reported engaging in more positive problem-solving behaviors on days in which they experienced greater relationship conflict, (b) were observed to display more constructive problem-solving behaviors when discussing important marital issues with their partner in the lab, and (c) experienced fewer declines in marital well-being over the 1st year of marriage. Conversely, spouses higher in relationship-specific optimism (a) reported engaging in fewer constructive problem-solving behaviors on high conflict days, (b) were observed to exhibit worse problem-solving behaviors in the lab-particularly when discussing marital issues of greater importance-and (c) experienced steeper declines in marital well-being over time. All findings held controlling for self-esteem and neuroticism. Together, results suggest that whereas global forms of optimism may represent a relationship asset, specific forms of optimism can place couples at risk for marital deterioration. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Extreme Learning Machine and Particle Swarm Optimization in optimizing CNC turning operation

NASA Astrophysics Data System (ADS)

Janahiraman, Tiagrajah V.; Ahmad, Nooraziah; Hani Nordin, Farah

2018-04-01

The CNC machine is controlled by manipulating cutting parameters that could directly influence the process performance. Many optimization methods has been applied to obtain the optimal cutting parameters for the desired performance function. Nonetheless, the industry still uses the traditional technique to obtain those values. Lack of knowledge on optimization techniques is the main reason for this issue to be prolonged. Therefore, the simple yet easy to implement, Optimal Cutting Parameters Selection System is introduced to help the manufacturer to easily understand and determine the best optimal parameters for their turning operation. This new system consists of two stages which are modelling and optimization. In modelling of input-output and in-process parameters, the hybrid of Extreme Learning Machine and Particle Swarm Optimization is applied. This modelling technique tend to converge faster than other artificial intelligent technique and give accurate result. For the optimization stage, again the Particle Swarm Optimization is used to get the optimal cutting parameters based on the performance function preferred by the manufacturer. Overall, the system can reduce the gap between academic world and the industry by introducing a simple yet easy to implement optimization technique. This novel optimization technique can give accurate result besides being the fastest technique.

Astrodynamics 1991; Proceedings of the AAS/AIAA Astrodynamics Conference, Durango, CO, Aug. 19-22, 1991. Pts. 1, 2, and 3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaufman, B.; Alfriend, K.T.; Roehrich, R.L.

1992-01-01

The present conference on astrodynamics and advances in the astronautical sciences encompasses orbit determination, orbital debris, flexible-body dynamics and control, attitude dynamics and control, and topics related to the projects of the European space program. Specific issues addressed include a numerical approach to the angles-only initial orbit determination problem, precise orbit determination of the SPOT platform with DORIS, space-debris measurement and modeling, H(infinity)-optimized broadband compensator for wave-absorbing control, and the application of linear actuators for for telescope pointing control. Also addressed are attitude determination and dynamical performance in free drift for the Space Station Freedom, a Kalman filter for amore » gravity-gradient satellite, the positioning of the Eutelsat II satellite from supersynchronous transfer orbit to reduce satellite velocity-correction requirements, and trajectory analysis and issues.« less

Cooperative Search and Rescue with Artificial Fishes Based on Fish-Swarm Algorithm for Underwater Wireless Sensor Networks

PubMed Central

Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua

2014-01-01

This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties. PMID:24741341

Cooperative search and rescue with artificial fishes based on fish-swarm algorithm for underwater wireless sensor networks.

PubMed

Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua

2014-01-01

This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties.

Bio-mimic optimization strategies in wireless sensor networks: a survey.

PubMed

Adnan, Md Akhtaruzzaman; Abdur Razzaque, Mohammd; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2013-12-24

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted.

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression, Flight-Test Performance

NASA Technical Reports Server (NTRS)

Miller, Christopher J.; Goodrick, Dan

2017-01-01

The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads to specified values. This technique has been implemented and flown on the National Aeronautics and Space Administration Full-scale Advanced Systems Testbed aircraft. The flight tests illustrate that the approach achieves the desired performance and show promising potential benefits. The flights also uncovered some important issues that will need to be addressed for production application.

Practical Study on HVAC Control Technology Based on the Learning Function and Optimum Multiple Objective Processes

NASA Astrophysics Data System (ADS)

Ueda, Haruka; Dazai, Ryota; Kaseda, Chosei; Ikaga, Toshiharu; Kato, Akihiro

Demand among large office buildings for the energy-saving benefits of the HVAC (Heating, Ventilating and Air-Conditioning) System are increasing as more and more people become concerned with global environmental issues. However, immoderate measures taken in the interest of energy conservation may encroach on the thermal comfort and productivity level of office workers. Building management should satisfy both indoor thermal comfort and energy conservation while adapting to the many regulatory, social, climate, and other changes that occur during the lifespan of the building. This paper demonstrates how optimal control of the HVAC system, based on data modeling and the multi-objective optimal method, achieves an efficient equilibrium between thermal comfort and energy conservation.

Multidisciplinary Optimization Approach for Design and Operation of Constrained and Complex-shaped Space Systems

NASA Astrophysics Data System (ADS)

Lee, Dae Young

The design of a small satellite is challenging since they are constrained by mass, volume, and power. To mitigate these constraint effects, designers adopt deployable configurations on the spacecraft that result in an interesting and difficult optimization problem. The resulting optimization problem is challenging due to the computational complexity caused by the large number of design variables and the model complexity created by the deployables. Adding to these complexities, there is a lack of integration of the design optimization systems into operational optimization, and the utility maximization of spacecraft in orbit. The developed methodology enables satellite Multidisciplinary Design Optimization (MDO) that is extendable to on-orbit operation. Optimization of on-orbit operations is possible with MDO since the model predictive controller developed in this dissertation guarantees the achievement of the on-ground design behavior in orbit. To enable the design optimization of highly constrained and complex-shaped space systems, the spherical coordinate analysis technique, called the "Attitude Sphere", is extended and merged with an additional engineering tools like OpenGL. OpenGL's graphic acceleration facilitates the accurate estimation of the shadow-degraded photovoltaic cell area. This technique is applied to the design optimization of the satellite Electric Power System (EPS) and the design result shows that the amount of photovoltaic power generation can be increased more than 9%. Based on this initial methodology, the goal of this effort is extended from Single Discipline Optimization to Multidisciplinary Optimization, which includes the design and also operation of the EPS, Attitude Determination and Control System (ADCS), and communication system. The geometry optimization satisfies the conditions of the ground development phase; however, the operation optimization may not be as successful as expected in orbit due to disturbances. To address this issue, for the ADCS operations, controllers based on Model Predictive Control that are effective for constraint handling were developed and implemented. All the suggested design and operation methodologies are applied to a mission "CADRE", which is space weather mission scheduled for operation in 2016. This application demonstrates the usefulness and capability of the methodology to enhance CADRE's capabilities, and its ability to be applied to a variety of missions.

Review of Findings for Human Performance Contribution to Risk in Operating Events

DTIC Science & Technology

2002-03-01

and loss of DC power. Key to this event was failure to control setpoints on safety-related equipment and failure to maintain the load tap changer...34 Therefore, "to optimize task execution at the job site, it is important to align organizational processes and values." Effective team skills are an...reactor was blocked and the water level rapidly dropped to the automatic low-level scram setpoint . Human Performance Issues Control rods were fully

An Architecture for SCADA Network Forensics

NASA Astrophysics Data System (ADS)

Kilpatrick, Tim; Gonzalez, Jesus; Chandia, Rodrigo; Papa, Mauricio; Shenoi, Sujeet

Supervisory control and data acquisition (SCADA) systems are widely used in industrial control and automation. Modern SCADA protocols often employ TCP/IP to transport sensor data and control signals. Meanwhile, corporate IT infrastructures are interconnecting with previously isolated SCADA networks. The use of TCP/IP as a carrier protocol and the interconnection of IT and SCADA networks raise serious security issues. This paper describes an architecture for SCADA network forensics. In addition to supporting forensic investigations of SCADA network incidents, the architecture incorporates mechanisms for monitoring process behavior, analyzing trends and optimizing plant performance.

Evaluation of some significant issues affecting trajectory and control management for air-breathing hypersonic vehicles

NASA Technical Reports Server (NTRS)

Hattis, Philip D.; Malchow, Harvey L.

1992-01-01

Horizontal takeoff airbreathing-propulsion launch vehicles require near-optimal guidance and control which takes into account performance sensitivities to atmospheric characteristics while satisfying physically-derived operational constraints. A generic trajectory/control analysis tool that deepens insight into these considerations has been applied to two versions of a winged-cone vehicle model. Information that is critical to the design and trajectory of these vehicles is derived, and several unusual characteristics of the airbreathing propulsion model are shown to have potentially substantial effects on vehicle dynamics.

Strategies for global optimization in photonics design.

PubMed

Vukovic, Ana; Sewell, Phillip; Benson, Trevor M

2010-10-01

This paper reports on two important issues that arise in the context of the global optimization of photonic components where large problem spaces must be investigated. The first is the implementation of a fast simulation method and associated matrix solver for assessing particular designs and the second, the strategies that a designer can adopt to control the size of the problem design space to reduce runtimes without compromising the convergence of the global optimization tool. For this study an analytical simulation method based on Mie scattering and a fast matrix solver exploiting the fast multipole method are combined with genetic algorithms (GAs). The impact of the approximations of the simulation method on the accuracy and runtime of individual design assessments and the consequent effects on the GA are also examined. An investigation of optimization strategies for controlling the design space size is conducted on two illustrative examples, namely, 60° and 90° waveguide bends based on photonic microstructures, and their effectiveness is analyzed in terms of a GA's ability to converge to the best solution within an acceptable timeframe. Finally, the paper describes some particular optimized solutions found in the course of this work.

Practitioner Review: Use of Antiepileptic Drugs in Children

ERIC Educational Resources Information Center

Guerrini, Renzo; Parmeggiani, Lucio

2006-01-01

Background: The aim in treating epilepsy is to minimise or control seizures with full respect of quality-of-life issues, especially of cognitive functions. Optimal treatment first demands a correct recognition of the major type of seizures, followed by a correct diagnosis of the type of epilepsy or of the specific syndrome. Methods: Review of data…

World Population: U.N. on the Move but Grounds for Optimism Are Scant

ERIC Educational Resources Information Center

Holden, Constance

1974-01-01

Discusses current trends and problems relating to world population, and focuses on action being taken by the United Nations. This year (1974) has been designated World Population Year, and will be highlighted by a conference in Bucharest in which all 130 member governments will meet to confront the issue of population control. (JR)

Lateral control system design for VTOL landing on a DD963 in high sea states. M.S. Thesis

NASA Technical Reports Server (NTRS)

Bodson, M.

1982-01-01

The problem of designing lateral control systems for the safe landing of VTOL aircraft on small ships is addressed. A ship model is derived. The issues of estimation and prediction of ship motions are discussed, using optimal linear linear estimation techniques. The roll motion is the most important of the lateral motions, and it is found that it can be predicted for up to 10 seconds in perfect conditions. The automatic landing of the VTOL aircraft is considered, and a lateral controller, defined as a ship motion tracker, is designed, using optimal control techniqes. The tradeoffs between the tracking errors and the control authority are obtained. The important couplings between the lateral motions and controls are demonstrated, and it is shown that the adverse couplings between the sway and the roll motion at the landing pad are significant constraints in the tracking of the lateral ship motions. The robustness of the control system, including the optimal estimator, is studied, using the singular values analysis. Through a robustification procedure, a robust control system is obtained, and the usefulness of the singular values to define stability margins that take into account general types of unstructured modelling errors is demonstrated. The minimal destabilizing perturbations indicated by the singular values analysis are interpreted and related to the multivariable Nyquist diagrams.

Bio-Mimic Optimization Strategies in Wireless Sensor Networks: A Survey

PubMed Central

Adnan, Md. Akhtaruzzaman; Razzaque, Mohammd Abdur; Ahmed, Ishtiaque; Isnin, Ismail Fauzi

2014-01-01

For the past 20 years, many authors have focused their investigations on wireless sensor networks. Various issues related to wireless sensor networks such as energy minimization (optimization), compression schemes, self-organizing network algorithms, routing protocols, quality of service management, security, energy harvesting, etc., have been extensively explored. The three most important issues among these are energy efficiency, quality of service and security management. To get the best possible results in one or more of these issues in wireless sensor networks optimization is necessary. Furthermore, in number of applications (e.g., body area sensor networks, vehicular ad hoc networks) these issues might conflict and require a trade-off amongst them. Due to the high energy consumption and data processing requirements, the use of classical algorithms has historically been disregarded. In this context contemporary researchers started using bio-mimetic strategy-based optimization techniques in the field of wireless sensor networks. These techniques are diverse and involve many different optimization algorithms. As far as we know, most existing works tend to focus only on optimization of one specific issue of the three mentioned above. It is high time that these individual efforts are put into perspective and a more holistic view is taken. In this paper we take a step in that direction by presenting a survey of the literature in the area of wireless sensor network optimization concentrating especially on the three most widely used bio-mimetic algorithms, namely, particle swarm optimization, ant colony optimization and genetic algorithm. In addition, to stimulate new research and development interests in this field, open research issues, challenges and future research directions are highlighted. PMID:24368702

Delivering successful randomized controlled trials in surgery: Methods to optimize collaboration and study design.

PubMed

Blencowe, Natalie S; Cook, Jonathan A; Pinkney, Thomas; Rogers, Chris; Reeves, Barnaby C; Blazeby, Jane M

2017-04-01

Randomized controlled trials in surgery are notoriously difficult to design and conduct due to numerous methodological and cultural challenges. Over the last 5 years, several UK-based surgical trial-related initiatives have been funded to address these issues. These include the development of Surgical Trials Centers and Surgical Specialty Leads (individual surgeons responsible for championing randomized controlled trials in their specialist fields), both funded by the Royal College of Surgeons of England; networks of research-active surgeons in training; and investment in methodological research relating to surgical randomized controlled trials (to address issues such as recruitment, blinding, and the selection and standardization of interventions). This article discusses these initiatives more in detail and provides exemplar cases to illustrate how the methodological challenges have been tackled. The initiatives have surpassed expectations, resulting in a renaissance in surgical research throughout the United Kingdom, such that the number of patients entering surgical randomized controlled trials has doubled.

New approaches to optimization in aerospace conceptual design

NASA Technical Reports Server (NTRS)

Gage, Peter J.

1995-01-01

Aerospace design can be viewed as an optimization process, but conceptual studies are rarely performed using formal search algorithms. Three issues that restrict the success of automatic search are identified in this work. New approaches are introduced to address the integration of analyses and optimizers, to avoid the need for accurate gradient information and a smooth search space (required for calculus-based optimization), and to remove the restrictions imposed by fixed complexity problem formulations. (1) Optimization should be performed in a flexible environment. A quasi-procedural architecture is used to conveniently link analysis modules and automatically coordinate their execution. It efficiently controls a large-scale design tasks. (2) Genetic algorithms provide a search method for discontinuous or noisy domains. The utility of genetic optimization is demonstrated here, but parameter encodings and constraint-handling schemes must be carefully chosen to avoid premature convergence to suboptimal designs. The relationship between genetic and calculus-based methods is explored. (3) A variable-complexity genetic algorithm is created to permit flexible parameterization, so that the level of description can change during optimization. This new optimizer automatically discovers novel designs in structural and aerodynamic tasks.

A single sensor and single actuator approach to performance tailoring over a prescribed frequency band.

PubMed

Wang, Jiqiang

2016-03-01

Restricted sensing and actuation control represents an important area of research that has been overlooked in most of the design methodologies. In many practical control engineering problems, it is necessitated to implement the design through a single sensor and single actuator for multivariate performance variables. In this paper, a novel approach is proposed for the solution to the single sensor and single actuator control problem where performance over any prescribed frequency band can also be tailored. The results are obtained for the broad band control design based on the formulation for discrete frequency control. It is shown that the single sensor and single actuator control problem over a frequency band can be cast into a Nevanlinna-Pick interpolation problem. An optimal controller can then be obtained via the convex optimization over LMIs. Even remarkable is that robustness issues can also be tackled in this framework. A numerical example is provided for the broad band attenuation of rotor blade vibration to illustrate the proposed design procedures. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Consensus of satellite cluster flight using an energy-matching optimal control method

NASA Astrophysics Data System (ADS)

Luo, Jianjun; Zhou, Liang; Zhang, Bo

2017-11-01

This paper presents an optimal control method for consensus of satellite cluster flight under a kind of energy matching condition. Firstly, the relation between energy matching and satellite periodically bounded relative motion is analyzed, and the satellite energy matching principle is applied to configure the initial conditions. Then, period-delayed errors are adopted as state variables to establish the period-delayed errors dynamics models of a single satellite and the cluster. Next a novel satellite cluster feedback control protocol with coupling gain is designed, so that the satellite cluster periodically bounded relative motion consensus problem (period-delayed errors state consensus problem) is transformed to the stability of a set of matrices with the same low dimension. Based on the consensus region theory in the research of multi-agent system consensus issues, the coupling gain can be obtained to satisfy the requirement of consensus region and decouple the satellite cluster information topology and the feedback control gain matrix, which can be determined by Linear quadratic regulator (LQR) optimal method. This method can realize the consensus of satellite cluster period-delayed errors, leading to the consistency of semi-major axes (SMA) and the energy-matching of satellite cluster. Then satellites can emerge the global coordinative cluster behavior. Finally the feasibility and effectiveness of the present energy-matching optimal consensus for satellite cluster flight is verified through numerical simulations.

Optimal haptic feedback control of artificial muscles

NASA Astrophysics Data System (ADS)

Chen, Daniel; Besier, Thor; Anderson, Iain; McKay, Thomas

2014-03-01

As our population ages, and trends in obesity continue to grow, joint degenerative diseases like osteoarthritis (OA) are becoming increasingly prevalent. With no cure currently in sight, the only effective treatments for OA are orthopaedic surgery and prolonged rehabilitation, neither of which is guaranteed to succeed. Gait retraining has tremendous potential to alter the contact forces in the joints due to walking, reducing the risk of one developing hip and knee OA. Dielectric Elastomer Actuators (DEAs) are being explored as a potential way of applying intuitive haptic feedback to alter a patient's walking gait. The main challenge with the use of DEAs in this application is producing large enough forces and strains to induce sensation when coupled to a patient's skin. A novel controller has been proposed to solve this issue. The controller uses simultaneous capacitive self-sensing and actuation which will optimally apply a haptic sensation to the patient's skin independent of variability in DEAs and patient geometries.

To Demonstrate an Integrated Solution for Plasma-Material Interfaces Compatible with an Optimized Core Plasma

NASA Astrophysics Data System (ADS)

Goldston, Robert; Brooks, Jeffrey; Hubbard, Amanda; Leonard, Anthony; Lipschultz, Bruce; Maingi, Rajesh; Ulrickson, Michael; Whyte, Dennis

2009-11-01

The plasma facing components in a Demo reactor will face much more extreme boundary plasma conditions and operating requirements than any present or planned experiment. These include 1) Power density a factor of four or more greater than in ITER, 2) Continuous operation resulting in annual energy and particle throughput 100-200 times larger than ITER, 3) Elevated surface operating temperature for efficient electricity production, 4) Tritium fuel cycle control for safety and breeding requirements, and 5) Steady state plasma confinement and control. Consistent with ReNeW Thrust 12, design options are being explored for a new moderate-scale facility to assess core-edge interaction issues and solutions. Key desired features include high power density, sufficient pulse length and duty cycle, elevated wall temperature, steady-state control of an optimized core plasma, and flexibility in changing boundary components as well as access for comprehensive measurements.

Optimal trajectory planning of free-floating space manipulator using differential evolution algorithm

NASA Astrophysics Data System (ADS)

Wang, Mingming; Luo, Jianjun; Fang, Jing; Yuan, Jianping

2018-03-01

The existence of the path dependent dynamic singularities limits the volume of available workspace of free-floating space robot and induces enormous joint velocities when such singularities are met. In order to overcome this demerit, this paper presents an optimal joint trajectory planning method using forward kinematics equations of free-floating space robot, while joint motion laws are delineated with application of the concept of reaction null-space. Bézier curve, in conjunction with the null-space column vectors, are applied to describe the joint trajectories. Considering the forward kinematics equations of the free-floating space robot, the trajectory planning issue is consequently transferred to an optimization issue while the control points to construct the Bézier curve are the design variables. A constrained differential evolution (DE) scheme with premature handling strategy is implemented to find the optimal solution of the design variables while specific objectives and imposed constraints are satisfied. Differ from traditional methods, we synthesize null-space and specialized curve to provide a novel viewpoint for trajectory planning of free-floating space robot. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) kinematically redundant manipulator mounted on a free-floating spacecraft and demonstrate the feasibility and effectiveness of the proposed method.

Microgravity human factors workstation development

NASA Technical Reports Server (NTRS)

Whitmore, Mihriban; Wilmington, Robert P.; Morris, Randy B.; Jensen, Dean G.

1992-01-01

Microgravity evaluations of workstation hardware as well as its system components were found to be very useful for determining the expected needs of the Space Station crew and for refining overall workstation design. Research at the Johnson Space Center has been carried out to provide optimal workstation design and human interface. The research included evaluations of hand controller configurations for robots and free flyers, the identification of cursor control device requirements, and the examination of anthropometric issues of workstation design such as reach, viewing distance, and head clearance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dobson, Ian; Hiskens, Ian; Linderoth, Jeffrey

Building on models of electrical power systems, and on powerful mathematical techniques including optimization, model predictive control, and simluation, this project investigated important issues related to the stable operation of power grids. A topic of particular focus was cascading failures of the power grid: simulation, quantification, mitigation, and control. We also analyzed the vulnerability of networks to component failures, and the design of networks that are responsive to and robust to such failures. Numerous other related topics were investigated, including energy hubs and cascading stall of induction machines

Enhanced optical design by distortion control

NASA Astrophysics Data System (ADS)

Thibault, Simon; Gauvin, Jonny; Doucet, Michel; Wang, Min

2005-09-01

The control of optical distortion is useful for the design of a variety of optical system. The most popular is the F-theta lens used in laser scanning system to produce a constant scan velocity across the image plane. Many authors have designed during the last 20 years distortion control corrector. Today, many challenging digital imaging system can use distortion the enhanced their imaging capability. A well know example is a reversed telephoto type, if the barrel distortion is increased instead of being corrected; the result is a so-called Fish-eye lens. However, if we control the barrel distortion instead of only increasing it, the resulting system can have enhanced imaging capability. This paper will present some lens design and real system examples that clearly demonstrate how the distortion control can improve the system performances such as resolution. We present innovative optical system which increases the resolution in the field of view of interest to meet the needs of specific applications. One critical issue when we designed using distortion is the optimization management. Like most challenging lens design, the automatic optimization is less reliable. Proper management keeps the lens design within the correct range, which is critical for optimal performance (size, cost, manufacturability). Many lens design presented tailor a custom merit function and approach.

Smart Inverter Control and Operation for Distributed Energy Resources

NASA Astrophysics Data System (ADS)

Tazay, Ahmad F.

The motivation of this research is to carry out the control and operation of smart inverters and voltage source converters (VSC) for distributed energy resources (DERs) such as photovoltaic (PV), battery, and plug-in hybrid electric vehicles (PHEV). The main contribution of the research includes solving a couple of issues for smart grids by controlling and implementing multifunctions of VSC and smart inverter as well as improving the operational scheme of the microgrid. The work is mainly focused on controlling and operating of smart inverter since it promises a new technology for the future microgrid. Two major applications of the smart inverter will be investigated in this work based on the connection modes: microgrid at grid-tied mode and autonomous mode. In grid-tied connection, the smart inverter and VSC are used to integrate DER such as Photovoltaic (PV) and battery to provide suitable power to the system by controlling the supplied real and reactive power. The role of a smart inverter at autonomous mode includes supplying a sufficient voltage and frequency, mitigate abnormal condition of the load as well as equally sharing the total load's power. However, the operational control of the microgrid still has a major issue on the operation of the microgrid. The dissertation is divided into two main sections which are: 1. Low-level control of a single smart Inverter. 2. High-level control of the microgrid. The first part investigates a comprehensive research for a smart inverter and VSC technology at the two major connections of the microgrid. This involves controlling and modeling single smart inverter and VSC to solve specific issues of microgrid as well as improve the operation of the system. The research provides developed features for smart inverter comparing with a conventional voltage sourced converter (VSC). The two main connections for a microgrid have been deeply investigated to analyze a better way to develop and improve the operational procedure of the microgrid as well as solve specific issues of connecting the microgrid to the system. A detailed procedure for controlling VSC and designing an optimal operation of the controller is also covered in the first part of the dissertation. This section provides an optimal operation for controlling motor drive and demonstrates issues when motor load exists at an autonomous microgrid. It also provides a solution for specific issues at operating a microgrid at autonomous mode as well as improving the structural design for the grid-tied microgrid. The solution for autonomous microgrid includes changing the operational state of the switching pattern of the smart inverter to solve the issue of a common mode voltage (CMV) that appears across the motor load. It also solves the issue of power supplying to large loads, such as induction motors. The last section of the low-level section involves an improvement of the performance and operation of the PV charging station for a plug-in hybrid electric vehicle (PHEV) at grid-tied mode. This section provides a novel structure and smart controller for PV charging station using three-phase hybrid boost converter topology. It also provides a form of applications of a multifunction smart inverter using PV charging station. The second part of the research is focusing on improving the performance of the microgrid by integrating several smart inverters to form a microgrid. It investigates the issue of connecting DER units with the microgrid at real applications. One of the common issues of the microgrid is the circulating current which is caused by poor reactive power sharing accuracy. When more than two DER units are connected in parallel, a microgrid is forming be generating required power for the load. When the microgrid is operated at autonomous mode, all DER units participate in generating voltage and frequency as well as share the load's power. This section provides a smart and novel controlling technique to solve the issue of unequal power sharing. The feature of the smart inverter is realized by the communication link between smart inverters and the main operator. The analysis and derivation of the problem are presented in this section. The dissertation has led to two accepted conference papers, one accepted transaction IEEE manuscript, and one submitted IET transaction manuscript. The future work aims to improve the current work by investigating the performance of the smart inverter at real applications.

Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects.

PubMed

Kang, Ziho; Mandal, Saptarshi; Crutchfield, Jerry; Millan, Angel; McClung, Sarah N

2016-01-01

Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1) developing dynamic areas of interests (AOIs) in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2) introducing the concept of AOI gap tolerance (AGT) that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3) finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC) operations where air traffic controller specialists (ATCSs) interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance.

Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects

PubMed Central

Mandal, Saptarshi

2016-01-01

Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1) developing dynamic areas of interests (AOIs) in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2) introducing the concept of AOI gap tolerance (AGT) that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3) finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC) operations where air traffic controller specialists (ATCSs) interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance. PMID:27725830

Thermal control systems for low-temperature heat rejection on a lunar base

NASA Technical Reports Server (NTRS)

Sridhar, K. R.; Gottmann, Matthias

1992-01-01

One of the important issues in the lunar base architecture is the design of a Thermal Control System (TCS) to reject the low temperature heat from the base. The TCS ensures that the base and all components inside are maintained within the operating temperature range. A significant portion of the total mass of the TCS is due to the radiator. Shading the radiation from the sun and the hot lunar soil could decrease the radiator operating temperature significantly. Heat pumps have been in use for terrestrial applications. To optimize the mass of the heat pump augmented TCS, all promising options have to be evaluated and compared. Careful attention is given to optimizing system operating parameters, working fluids, and component masses. The systems are modeled for full load operation.

Singular perturbation techniques for real time aircraft trajectory optimization and control

NASA Technical Reports Server (NTRS)

Calise, A. J.; Moerder, D. D.

1982-01-01

The usefulness of singular perturbation methods for developing real time computer algorithms to control and optimize aircraft flight trajectories is examined. A minimum time intercept problem using F-8 aerodynamic and propulsion data is used as a baseline. This provides a framework within which issues relating to problem formulation, solution methodology and real time implementation are examined. Theoretical questions relating to separability of dynamics are addressed. With respect to implementation, situations leading to numerical singularities are identified, and procedures for dealing with them are outlined. Also, particular attention is given to identifying quantities that can be precomputed and stored, thus greatly reducing the on-board computational load. Numerical results are given to illustrate the minimum time algorithm, and the resulting flight paths. An estimate is given for execution time and storage requirements.

Integrated modeling environment for systems-level performance analysis of the Next-Generation Space Telescope

NASA Astrophysics Data System (ADS)

Mosier, Gary E.; Femiano, Michael; Ha, Kong; Bely, Pierre Y.; Burg, Richard; Redding, David C.; Kissil, Andrew; Rakoczy, John; Craig, Larry

1998-08-01

All current concepts for the NGST are innovative designs which present unique systems-level challenges. The goals are to outperform existing observatories at a fraction of the current price/performance ratio. Standard practices for developing systems error budgets, such as the 'root-sum-of- squares' error tree, are insufficient for designs of this complexity. Simulation and optimization are the tools needed for this project; in particular tools that integrate controls, optics, thermal and structural analysis, and design optimization. This paper describes such an environment which allows sub-system performance specifications to be analyzed parametrically, and includes optimizing metrics that capture the science requirements. The resulting systems-level design trades are greatly facilitated, and significant cost savings can be realized. This modeling environment, built around a tightly integrated combination of commercial off-the-shelf and in-house- developed codes, provides the foundation for linear and non- linear analysis on both the time and frequency-domains, statistical analysis, and design optimization. It features an interactive user interface and integrated graphics that allow highly-effective, real-time work to be done by multidisciplinary design teams. For the NGST, it has been applied to issues such as pointing control, dynamic isolation of spacecraft disturbances, wavefront sensing and control, on-orbit thermal stability of the optics, and development of systems-level error budgets. In this paper, results are presented from parametric trade studies that assess requirements for pointing control, structural dynamics, reaction wheel dynamic disturbances, and vibration isolation. These studies attempt to define requirements bounds such that the resulting design is optimized at the systems level, without attempting to optimize each subsystem individually. The performance metrics are defined in terms of image quality, specifically centroiding error and RMS wavefront error, which directly links to science requirements.

Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Long, Theresa W.

1995-01-01

Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

Optimization and Design of an Absorbance Spectrometer Controlled Using a Raspberry Pi to Improve Analytical Skills

ERIC Educational Resources Information Center

Bougot-Robin, Kristelle; Paget, Jack; Atkins, Stephen C.; Edel, Joshua B.

2016-01-01

It is not uncommon for students to view laboratory instruments as black boxes. Unfortunately, this can often result in poor experimental results and interpretation. To tackle this issue, a laboratory course was designed to enable students not only to critically think about operating principles of the instrument but also to improve interpretation…

Optimization of wetland restoration siting and zoning in flood retention areas of river basins in China: A case study in Mengwa, Huaihe River Basin

NASA Astrophysics Data System (ADS)

Zhang, Xiaolei; Song, Yuqin

2014-11-01

Wetland restoration in floodplains is an ecological solution that can address basin-wide flooding issues and minimize flooding and damages to riverine and downstream areas. High population densities, large economic outputs, and heavy reliance on water resources make flood retention and management pressing issues in China. To balance flood control and sustainable development economically, socially, and politically, flood retention areas have been established to increase watershed flood storage capacities and enhance the public welfare for the populace living in the areas. However, conflicts between flood storage functions and human habitation appear irreconcilable. We developed a site-specific methodology for identifying potential sites and functional zones for wetland restoration in a flood retention area in middle and eastern China, optimizing the spatial distribution and functional zones to maximize flood control and human and regional development. This methodology was applied to Mengwa, one of 21 flood retention areas in China's Huaihe River Basin, using nine scenarios that reflected different flood, climatic, and hydraulic conditions. The results demonstrated improved flood retention and ecological functions, as well as increased economic benefits.

An inverse problem of determining the implied volatility in option pricing

NASA Astrophysics Data System (ADS)

Deng, Zui-Cha; Yu, Jian-Ning; Yang, Liu

2008-04-01

In the Black-Scholes world there is the important quantity of volatility which cannot be observed directly but has a major impact on the option value. In practice, traders usually work with what is known as implied volatility which is implied by option prices observed in the market. In this paper, we use an optimal control framework to discuss an inverse problem of determining the implied volatility when the average option premium, namely the average value of option premium corresponding with a fixed strike price and all possible maturities from the current time to a chosen future time, is known. The issue is converted into a terminal control problem by Green function method. The existence and uniqueness of the minimum of the control functional are addressed by the optimal control method, and the necessary condition which must be satisfied by the minimum is also given. The results obtained in the paper may be useful for those who engage in risk management or volatility trading.

On the use of PGD for optimal control applied to automated fibre placement

NASA Astrophysics Data System (ADS)

Bur, N.; Joyot, P.

2017-10-01

Automated Fibre Placement (AFP) is an incipient manufacturing process for composite structures. Despite its concep-tual simplicity it involves many complexities related to the necessity of melting the thermoplastic at the interface tape-substrate, ensuring the consolidation that needs the diffusion of molecules and control the residual stresses installation responsible of the residual deformations of the formed parts. The optimisation of the process and the determination of the process window cannot be achieved in a traditional way since it requires a plethora of trials/errors or numerical simulations, because there are many parameters involved in the characterisation of the material and the process. Using reduced order modelling such as the so called Proper Generalised Decomposition method, allows the construction of multi-parametric solution taking into account many parameters. This leads to virtual charts that can be explored on-line in real time in order to perform process optimisation or on-line simulation-based control. Thus, for a given set of parameters, determining the power leading to an optimal temperature becomes easy. However, instead of controlling the power knowing the temperature field by particularizing an abacus, we propose here an approach based on optimal control: we solve by PGD a dual problem from heat equation and optimality criteria. To circumvent numerical issue due to ill-conditioned system, we propose an algorithm based on Uzawa's method. That way, we are able to solve the dual problem, setting the desired state as an extra-coordinate in the PGD framework. In a single computation, we get both the temperature field and the required heat flux to reach a parametric optimal temperature on a given zone.

Antimicrobial resistance in Saudi Arabia

PubMed Central

Zowawi, Hosam M.

2016-01-01

Antimicrobial resistance (AMR) is increasingly being highlighted as an urgent public and animal health issue worldwide. This issue is well demonstrated in bacteria that are resistant to last-line antibiotics, suggesting a future with untreatable infections. International agencies have suggested combating strategies against AMR. Saudi Arabia has several challenges that can stimulate the emergence and spread of multidrug-resistant bacteria. Tackling these challenges need efforts from multiple sectors to successfully control the spread and emergence of AMR in the country. Actions should include active surveillance to monitor the emergence and spread of AMR. Infection prevention and control precautions should also be optimized to limit further spread. Raising awareness is essential to limit inappropriate antibiotics use, and the antibiotic stewardship programs in hospital settings, outpatients, and community pharmacies, should regulate the ongoing use of antimicrobials. PMID:27570847

Lessons Learned During Solutions of Multidisciplinary Design Optimization Problems

NASA Technical Reports Server (NTRS)

Patnaik, Suna N.; Coroneos, Rula M.; Hopkins, Dale A.; Lavelle, Thomas M.

2000-01-01

Optimization research at NASA Glenn Research Center has addressed the design of structures, aircraft and airbreathing propulsion engines. During solution of the multidisciplinary problems several issues were encountered. This paper lists four issues and discusses the strategies adapted for their resolution: (1) The optimization process can lead to an inefficient local solution. This deficiency was encountered during design of an engine component. The limitation was overcome through an augmentation of animation into optimization. (2) Optimum solutions obtained were infeasible for aircraft and air-breathing propulsion engine problems. Alleviation of this deficiency required a cascading of multiple algorithms. (3) Profile optimization of a beam produced an irregular shape. Engineering intuition restored the regular shape for the beam. (4) The solution obtained for a cylindrical shell by a subproblem strategy converged to a design that can be difficult to manufacture. Resolution of this issue remains a challenge. The issues and resolutions are illustrated through six problems: (1) design of an engine component, (2) synthesis of a subsonic aircraft, (3) operation optimization of a supersonic engine, (4) design of a wave-rotor-topping device, (5) profile optimization of a cantilever beam, and (6) design of a cvlindrical shell. The combined effort of designers and researchers can bring the optimization method from academia to industry.

Design and fabrication of a magnetic propulsion system for self-propelled capsule endoscope.

PubMed

Gao, Mingyuan; Hu, Chengzhi; Chen, Zhenzhi; Zhang, Honghai; Liu, Sheng

2010-12-01

This paper investigates design, modeling, simulation, and control issues related to self-propelled endoscopic capsule navigated inside the human body through external magnetic fields. A novel magnetic propulsion system is proposed and fabricated, which has great potential of being used in the field of noninvasive gastrointestinal endoscopy. Magnetic-analysis model is established and finite-element simulations as well as orthogonal design are performed for obtaining optimized mechanical and control parameters for generating appropriate external magnetic field. Simulated intestinal tract experiments are conducted, demonstrating controllable movement of the capsule under the developed magnetic propulsion system.

Methodological Issues in Research on Web-Based Behavioral Interventions

PubMed Central

Danaher, Brian G; Seeley, John R

2013-01-01

Background Web-based behavioral intervention research is rapidly growing. Purpose We review methodological issues shared across Web-based intervention research to help inform future research in this area. Methods We examine measures and their interpretation using exemplar studies and our research. Results We report on research designs used to evaluate Web-based interventions and recommend newer, blended designs. We review and critique methodological issues associated with recruitment, engagement, and social validity. Conclusions We suggest that there is value to viewing this burgeoning realm of research from the broader context of behavior change research. We conclude that many studies use blended research designs, that innovative mantling designs such as the Multiphase Optimization Strategy and Sequential Multiple Assignment Randomized Trial methods hold considerable promise and should be used more widely, and that Web-based controls should be used instead of usual care or no-treatment controls in public health research. We recommend topics for future research that address participant recruitment, engagement, and social validity. PMID:19806416

Feasibility Study of a Satellite Solar Power Station

NASA Technical Reports Server (NTRS)

Glaser, P. E.; Maynard, O. E.; Mackovciak, J. J. R.; Ralph, E. I.

1974-01-01

A feasibility study of a satellite solar power station (SSPS) was conducted to: (1) explore how an SSPS could be flown and controlled in orbit; (2) determine the techniques needed to avoid radio frequency interference (RFI); and (3) determine the key environmental, technological, and economic issues involved. Structural and dynamic analyses of the SSPS structure were performed, and deflections and internal member loads were determined. Desirable material characteristics were assessed and technology developments identified. Flight control performance of the SSPS baseline design was evaluated and parametric sizing studies were performed. The study of RFI avoidance techniques covered (1) optimization of the microwave transmission system; (2) device design and expected RFI; and (3) SSPS RFI effects. The identification of key issues involved (1) microwave generation, transmissions, and rectification and solar energy conversion; (2) environmental-ecological impact and biological effects; and (3) economic issues, i.e., costs and benefits associated with the SSPS. The feasibility of the SSPS based on the parameters of the study was established.

Computational design of treatment strategies for proactive therapy on atopic dermatitis using optimal control theory

PubMed Central

Christodoulides, Panayiotis; Hirata, Yoshito; Domínguez-Hüttinger, Elisa; Danby, Simon G.; Cork, Michael J.; Williams, Hywel C.; Aihara, Kazuyuki

2017-01-01

Atopic dermatitis (AD) is a common chronic skin disease characterized by recurrent skin inflammation and a weak skin barrier, and is known to be a precursor to other allergic diseases such as asthma. AD affects up to 25% of children worldwide and the incidence continues to rise. There is still uncertainty about the optimal treatment strategy in terms of choice of treatment, potency, duration and frequency. This study aims to develop a computational method to design optimal treatment strategies for the clinically recommended ‘proactive therapy’ for AD. Proactive therapy aims to prevent recurrent flares once the disease has been brought under initial control. Typically, this is done by using an anti-inflammatory treatment such as a potent topical corticosteroid intensively for a few weeks to ‘get control’, followed by intermittent weekly treatment to suppress subclinical inflammation to ‘keep control’. Using a hybrid mathematical model of AD pathogenesis that we recently proposed, we computationally derived the optimal treatment strategies for individual virtual patient cohorts, by recursively solving optimal control problems using a differential evolution algorithm. Our simulation results suggest that such an approach can inform the design of optimal individualized treatment schedules that include application of topical corticosteroids and emollients, based on the disease status of patients observed on their weekly hospital visits. We demonstrate the potential and the gaps of our approach to be applied to clinical settings. This article is part of the themed issue ‘Mathematical methods in medicine: neuroscience, cardiology and pathology’. PMID:28507230

Design of freeze-drying processes for pharmaceuticals: practical advice.

PubMed

Tang, Xiaolin; Pikal, Michael J

2004-02-01

Design of freeze-drying processes is often approached with a "trial and error" experimental plan or, worse yet, the protocol used in the first laboratory run is adopted without further attempts at optimization. Consequently, commercial freeze-drying processes are often neither robust nor efficient. It is our thesis that design of an "optimized" freeze-drying process is not particularly difficult for most products, as long as some simple rules based on well-accepted scientific principles are followed. It is the purpose of this review to discuss the scientific foundations of the freeze-drying process design and then to consolidate these principles into a set of guidelines for rational process design and optimization. General advice is given concerning common stability issues with proteins, but unusual and difficult stability issues are beyond the scope of this review. Control of ice nucleation and crystallization during the freezing step is discussed, and the impact of freezing on the rest of the process and final product quality is reviewed. Representative freezing protocols are presented. The significance of the collapse temperature and the thermal transition, denoted Tg', are discussed, and procedures for the selection of the "target product temperature" for primary drying are presented. Furthermore, guidelines are given for selection of the optimal shelf temperature and chamber pressure settings required to achieve the target product temperature without thermal and/or mass transfer overload of the freeze dryer. Finally, guidelines and "rules" for optimization of secondary drying and representative secondary drying protocols are presented.

2-D Ultrasound Sparse Arrays Multidepth Radiation Optimization Using Simulated Annealing and Spiral-Array Inspired Energy Functions.

PubMed

Roux, Emmanuel; Ramalli, Alessandro; Tortoli, Piero; Cachard, Christian; Robini, Marc C; Liebgott, Herve

2016-12-01

Full matrix arrays are excellent tools for 3-D ultrasound imaging, but the required number of active elements is too high to be individually controlled by an equal number of scanner channels. The number of active elements is significantly reduced by the sparse array techniques, but the position of the remaining elements must be carefully optimized. This issue is faced here by introducing novel energy functions in the simulated annealing (SA) algorithm. At each iteration step of the optimization process, one element is freely translated and the associated radiated pattern is simulated. To control the pressure field behavior at multiple depths, three energy functions inspired by the pressure field radiated by a Blackman-tapered spiral array are introduced. Such energy functions aim at limiting the main lobe width while lowering the side lobe and grating lobe levels at multiple depths. Numerical optimization results illustrate the influence of the number of iterations, pressure measurement points, and depths, as well as the influence of the energy function definition on the optimized layout. It is also shown that performance close to or even better than the one provided by a spiral array, here assumed as reference, may be obtained. The finite-time convergence properties of SA allow the duration of the optimization process to be set in advance.

Using spatial information about recurrence risk for robust optimization of dose-painting prescription functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bender, Edward T.

Purpose: To develop a robust method for deriving dose-painting prescription functions using spatial information about the risk for disease recurrence. Methods: Spatial distributions of radiobiological model parameters are derived from distributions of recurrence risk after uniform irradiation. These model parameters are then used to derive optimal dose-painting prescription functions given a constant mean biologically effective dose. Results: An estimate for the optimal dose distribution can be derived based on spatial information about recurrence risk. Dose painting based on imaging markers that are moderately or poorly correlated with recurrence risk are predicted to potentially result in inferior disease control when comparedmore » the same mean biologically effective dose delivered uniformly. A robust optimization approach may partially mitigate this issue. Conclusions: The methods described here can be used to derive an estimate for a robust, patient-specific prescription function for use in dose painting. Two approximate scaling relationships were observed: First, the optimal choice for the maximum dose differential when using either a linear or two-compartment prescription function is proportional to R, where R is the Pearson correlation coefficient between a given imaging marker and recurrence risk after uniform irradiation. Second, the predicted maximum possible gain in tumor control probability for any robust optimization technique is nearly proportional to the square of R.« less

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Tao; Li, Cheng; Huang, Can

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

Memetic Algorithm-Based Multi-Objective Coverage Optimization for Wireless Sensor Networks

PubMed Central

Chen, Zhi; Li, Shuai; Yue, Wenjing

2014-01-01

Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MOCADMA, which models the coverage control of WSNs as the multi-objective optimization problem. MOCADMA uses a memetic algorithm with a dynamic local search strategy to optimize the coverage of WSNs and achieve the objectives such as high network coverage, effective node utilization and more residual energy. In MOCADMA, the alternative solutions are represented as the chromosomes in matrix form, and the optimal solutions are selected through numerous iterations of the evolution process, including selection, crossover, mutation, local enhancement, and fitness evaluation. The experiment and evaluation results show MOCADMA can have good capabilities in maintaining the sensing coverage, achieve higher network coverage while improving the energy efficiency and effectively prolonging the network lifetime, and have a significant improvement over some existing algorithms. PMID:25360579

Memetic algorithm-based multi-objective coverage optimization for wireless sensor networks.

PubMed

Chen, Zhi; Li, Shuai; Yue, Wenjing

2014-10-30

Maintaining effective coverage and extending the network lifetime as much as possible has become one of the most critical issues in the coverage of WSNs. In this paper, we propose a multi-objective coverage optimization algorithm for WSNs, namely MOCADMA, which models the coverage control of WSNs as the multi-objective optimization problem. MOCADMA uses a memetic algorithm with a dynamic local search strategy to optimize the coverage of WSNs and achieve the objectives such as high network coverage, effective node utilization and more residual energy. In MOCADMA, the alternative solutions are represented as the chromosomes in matrix form, and the optimal solutions are selected through numerous iterations of the evolution process, including selection, crossover, mutation, local enhancement, and fitness evaluation. The experiment and evaluation results show MOCADMA can have good capabilities in maintaining the sensing coverage, achieve higher network coverage while improving the energy efficiency and effectively prolonging the network lifetime, and have a significant improvement over some existing algorithms.

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE PAGES

Ding, Tao; Li, Cheng; Huang, Can; ...

2017-01-09

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

Astronomy Village Reaches for New Heights

NASA Astrophysics Data System (ADS)

Croft, S. K.; Pompea, S. M.

2007-12-01

We are developing a set of complex, multimedia-based instructional modules emphasizing technical and scientific issues related to Giant Segmented Mirror Telescope project. The modules" pedagogy will be open-ended and problem-based to promote development of problem-solving skills. Problem- based-learning modules that emphasize work on open-ended complex real world problems are particularly valuable in illustrating and promoting a perspective on the process of science and engineering. Research in this area shows that these kinds of learning experiences are superior to more conventional student training in terms of gains in student learning. The format for the modules will be based on the award-winning multi-media educational Astronomy Village products that present students with a simulated environment: a mountaintop community surrounded by a cluster of telescopes, satellite receivers, and telecommunication towers. A number of "buildings" are found in the Village, such as a library, a laboratory, and an auditorium. Each building contains an array of information sources and computer simulations. Students navigate through their research with a mentor via imbedded video. The first module will be "Observatory Site Selection." Students will use astronomical data, basic weather information, and sky brightness data to select the best site for an observatory. Students will investigate the six GSMT sites considered by the professional site selection teams. Students will explore weather and basic site issues (e.g., roads and topography) using remote sensing images, computational fluid dynamics results, turbulence profiles, and scintillation of the different sites. Comparison of student problem solving with expert problem solving will also be done as part of the module. As part of a site selection team they will have to construct a case and present it on why they chose a particular site. The second module will address aspects of system engineering and optimization for a GSMT-like telescope. Basic system issues will be addressed and studied. These might include various controls issues and optimization issues such as mirror figure, mirror support stability, and wind loading trade-offs. Using system modeling and system optimization results from existing and early GSMT trade studies, we will create a simulation where students are part of an engineering design and optimization team. They will explore the cost/performance/schedule issues associate with the GSMT design.

Active vibration and noise control of vibro-acoustic system by using PID controller

NASA Astrophysics Data System (ADS)

Li, Yunlong; Wang, Xiaojun; Huang, Ren; Qiu, Zhiping

2015-07-01

Active control simulation of the acoustic and vibration response of a vibro-acoustic cavity of an airplane based on a PID controller is presented. A full numerical vibro-acoustic model is developed by using an Eulerian model, which is a coupled model based on the finite element formulation. The reduced order model, which is used to design the closed-loop control system, is obtained by the combination of modal expansion and variable substitution. Some physical experiments are made to validate and update the full-order and the reduced-order numerical models. Optimization of the actuator placement is employed in order to get an effective closed-loop control system. For the controller design, an iterative method is used to determine the optimal parameters of the PID controller. The process is illustrated by the design of an active noise and vibration control system for a cavity structure. The numerical and experimental results show that a PID-based active control system can effectively suppress the noise inside the cavity using a sound pressure signal as the controller input. It is also possible to control the noise by suppressing the vibration of the structure using the structural displacement signal as the controller input. For an airplane cavity structure, considering the issue of space-saving, the latter is more suitable.

Optimal design of a microgripper-type actuator based on AlN/Si heterogeneous bimorph

NASA Astrophysics Data System (ADS)

Ruiz, D.; Díaz-Molina, A.; Sigmund, O.; Donoso, A.; Bellido, J. C.; Sánchez-Rojas, J. L.

2017-05-01

This work presents a systematic procedure to design piezoelectrically actuated microgrippers. Topology optimization combined with optimal design of electrodes is used to maximize the displacement at the output port of the gripper. The fabrication at the microscale leads us to overcome an important issue: the difficulty of placing a piezoelectric film on both top and bottom of the host layer. Due to the non-symmetric lamination of the structure, an out-of-plane bending spoils the behaviour of the gripper. Suppression of this out-of-plane deformation is the main novelty introduced. In addition, a robust formulation approach is used in order to control the length scale in the whole domain and to reduce sensitivity of the designs to small manufacturing errors.

Applied optimal shape design

NASA Astrophysics Data System (ADS)

Mohammadi, B.; Pironneau, O.

2002-12-01

This paper is a short survey of optimal shape design (OSD) for fluids. OSD is an interesting field both mathematically and for industrial applications. Existence, sensitivity, correct discretization are important theoretical issues. Practical implementation issues for airplane designs are critical too. The paper is also a summary of the material covered in our recent book, Applied Optimal Shape Design, Oxford University Press, 2001.

Model-based Acceleration Control of Turbofan Engines with a Hammerstein-Wiener Representation

NASA Astrophysics Data System (ADS)

Wang, Jiqiang; Ye, Zhifeng; Hu, Zhongzhi; Wu, Xin; Dimirovsky, Georgi; Yue, Hong

2017-05-01

Acceleration control of turbofan engines is conventionally designed through either schedule-based or acceleration-based approach. With the widespread acceptance of model-based design in aviation industry, it becomes necessary to investigate the issues associated with model-based design for acceleration control. In this paper, the challenges for implementing model-based acceleration control are explained; a novel Hammerstein-Wiener representation of engine models is introduced; based on the Hammerstein-Wiener model, a nonlinear generalized minimum variance type of optimal control law is derived; the feature of the proposed approach is that it does not require the inversion operation that usually upsets those nonlinear control techniques. The effectiveness of the proposed control design method is validated through a detailed numerical study.

Improving the Critic Learning for Event-Based Nonlinear $H_{\\infty }$ Control Design.

PubMed

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

In this paper, we aim at improving the critic learning criterion to cope with the event-based nonlinear H ∞ state feedback control design. First of all, the H ∞ control problem is regarded as a two-player zero-sum game and the adaptive critic mechanism is used to achieve the minimax optimization under event-based environment. Then, based on an improved updating rule, the event-based optimal control law and the time-based worst-case disturbance law are obtained approximately by training a single critic neural network. The initial stabilizing control is no longer required during the implementation process of the new algorithm. Next, the closed-loop system is formulated as an impulsive model and its stability issue is handled by incorporating the improved learning criterion. The infamous Zeno behavior of the present event-based design is also avoided through theoretical analysis on the lower bound of the minimal intersample time. Finally, the applications to an aircraft dynamics and a robot arm plant are carried out to verify the efficient performance of the present novel design method.

Grid Generation for Multidisciplinary Design and Optimization of an Aerospace Vehicle: Issues and Challenges

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

2000-01-01

The purpose of this paper is to discuss grid generation issues and to challenge the grid generation community to develop tools suitable for automated multidisciplinary analysis and design optimization of aerospace vehicles. Special attention is given to the grid generation issues of computational fluid dynamics and computational structural mechanics disciplines.

Design and Construction of a Thermal Contact Resistance and Thermal Conductivity Measurement System

DTIC Science & Technology

2015-09-01

plate interface resistance control. Numerical heat transfer and uncertainty analyses with applied engineering judgement were extensively used to come... heat transfer issues facing the Department of Defense. 14. SUBJECT TERMS Thermal contact resistance, thermal conductivity, measurement system 15... heat transfer and uncertainty analyses with applied engineering judgement were extensively used to come up with an optimized design and construction

Optimization of transonic wind tunnel data acquisition and control systems for providing continuous mode tests

NASA Astrophysics Data System (ADS)

Petronevich, V. V.

2016-10-01

The paper observes the issues related to the increase of efficiency and information content of experimental research in transonic wind tunnels (WT). In particular, questions of optimizing the WT Data Acquisition and Control Systems (DACS) to provide the continuous mode test method are discussed. The problem of Mach number (M number) stabilization in the test section of the large transonic compressor-type wind tunnels at subsonic flow conditions with continuous change of the aircraft model angle of attack is observed on the example of T-128 wind tunnel. To minimize the signals distortion in T-128 DACS measurement channels the optimal MGCplus filter settings of the data acquisition system used in T-128 wind tunnel to measure loads were experimentally determined. As a result of the tests performed a good agreement of the results of balance measurements for pitch/pause and continuous test modes was obtained. Carrying out balance tests for pitch/pause and continuous test methods was provided by the regular data acquisition and control system of T-128 wind tunnel with unified software package POTOK. The architecture and functional abilities of POTOK software package are observed.

Computational issues in complex water-energy optimization problems: Time scales, parameterizations, objectives and algorithms

NASA Astrophysics Data System (ADS)

Efstratiadis, Andreas; Tsoukalas, Ioannis; Kossieris, Panayiotis; Karavokiros, George; Christofides, Antonis; Siskos, Alexandros; Mamassis, Nikos; Koutsoyiannis, Demetris

2015-04-01

Modelling of large-scale hybrid renewable energy systems (HRES) is a challenging task, for which several open computational issues exist. HRES comprise typical components of hydrosystems (reservoirs, boreholes, conveyance networks, hydropower stations, pumps, water demand nodes, etc.), which are dynamically linked with renewables (e.g., wind turbines, solar parks) and energy demand nodes. In such systems, apart from the well-known shortcomings of water resources modelling (nonlinear dynamics, unknown future inflows, large number of variables and constraints, conflicting criteria, etc.), additional complexities and uncertainties arise due to the introduction of energy components and associated fluxes. A major difficulty is the need for coupling two different temporal scales, given that in hydrosystem modeling, monthly simulation steps are typically adopted, yet for a faithful representation of the energy balance (i.e. energy production vs. demand) a much finer resolution (e.g. hourly) is required. Another drawback is the increase of control variables, constraints and objectives, due to the simultaneous modelling of the two parallel fluxes (i.e. water and energy) and their interactions. Finally, since the driving hydrometeorological processes of the integrated system are inherently uncertain, it is often essential to use synthetically generated input time series of large length, in order to assess the system performance in terms of reliability and risk, with satisfactory accuracy. To address these issues, we propose an effective and efficient modeling framework, key objectives of which are: (a) the substantial reduction of control variables, through parsimonious yet consistent parameterizations; (b) the substantial decrease of computational burden of simulation, by linearizing the combined water and energy allocation problem of each individual time step, and solve each local sub-problem through very fast linear network programming algorithms, and (c) the substantial decrease of the required number of function evaluations for detecting the optimal management policy, using an innovative, surrogate-assisted global optimization approach.

Role of transfused red blood cells for shock and coagulopathy within remote damage control resuscitation.

PubMed

Spinella, Philip C; Doctor, Allan

2014-05-01

The philosophy of damage control resuscitation (DCR) and remote damage control resuscitation (RDCR) can be summarized by stating that the goal is to prevent death from hemorrhagic shock by "staying out of trouble instead of getting out of trouble." In other words, it is preferred to arrest the progression of shock, rather than also having to reverse this condition after significant tissue damage and organ injury cascades are established. Moreover, to prevent death from exsanguination, a balanced approach to the treatment of both shock and coagulopathy is required. This was military doctrine during World War II, but seemed to be forgotten during the last half of the 20th century. Damage control resuscitation and RDCR have revitalized the approach, but there is still more to learn about the most effective and safe resuscitative strategies to simultaneously treat shock and hemorrhage. Current data suggest that our preconceived notions regarding the efficacy of standard issue red blood cells (RBCs) during the hours after transfusion may be false. Standard issue RBCs may not increase oxygen delivery and may in fact decrease it by disturbing control of regional blood flow distribution (impaired nitric oxide processing) and failing to release oxygen, even when perfusing hypoxic tissue (abnormal oxygen affinity). Standard issue RBCs may assist with hemostasis but appear to have competing effects on thrombin generation and platelet function. If standard issue or RBCs of increased storage age are not optimal, then are there alternatives that will allow for an efficacious and safe treatment of shock while also supporting hemostasis? Studies are required to determine if fresh RBCs less than 7 to 10 days provide an outcome advantage. A resurgence in the study of whole blood stored at 4°C for up to 10 days also holds promise. Two randomized controlled trials in humans have indicated that following transfusion with either whole blood stored at 4°C or platelets stored at 4°C there was less clinical bleeding than when blood was reconstituted with components or when platelets were stored at 22°C. Early reversal of shock is essential to prevent exacerbation of coagulopathy and progression of cell death cascades in patients with severe traumatic injuries. Red blood cell storage solutions have evolved to accommodate the needs of non-critically ill patients yet may not be optimal for patients in hemorrhagic shock. Continued focus on the recognition and treatment of shock is essential for continued improvement in outcomes for patients who require damage control resuscitation and RDCR.

Multidisciplinary optimization in aircraft design using analytic technology models

NASA Technical Reports Server (NTRS)

Malone, Brett; Mason, W. H.

1991-01-01

An approach to multidisciplinary optimization is presented which combines the Global Sensitivity Equation method, parametric optimization, and analytic technology models. The result is a powerful yet simple procedure for identifying key design issues. It can be used both to investigate technology integration issues very early in the design cycle, and to establish the information flow framework between disciplines for use in multidisciplinary optimization projects using much more computational intense representations of each technology. To illustrate the approach, an examination of the optimization of a short takeoff heavy transport aircraft is presented for numerous combinations of performance and technology constraints.

Optimal dynamic voltage scaling for wireless sensor nodes with real-time constraints

NASA Astrophysics Data System (ADS)

Cassandras, Christos G.; Zhuang, Shixin

2005-11-01

Sensors are increasingly embedded in manufacturing systems and wirelessly networked to monitor and manage operations ranging from process and inventory control to tracking equipment and even post-manufacturing product monitoring. In building such sensor networks, a critical issue is the limited and hard to replenish energy in the devices involved. Dynamic voltage scaling is a technique that controls the operating voltage of a processor to provide desired performance while conserving energy and prolonging the overall network's lifetime. We consider such power-limited devices processing time-critical tasks which are non-preemptive, aperiodic and have uncertain arrival times. We treat voltage scaling as a dynamic optimization problem whose objective is to minimize energy consumption subject to hard or soft real-time execution constraints. In the case of hard constraints, we build on prior work (which engages a voltage scaling controller at task completion times) by developing an intra-task controller that acts at all arrival times of incoming tasks. We show that this optimization problem can be decomposed into two simpler ones whose solution leads to an algorithm that does not actually require solving any nonlinear programming problems. In the case of soft constraints, this decomposition must be partly relaxed, but it still leads to a scalable (linear in the number of tasks) algorithm. Simulation results are provided to illustrate performance improvements in systems with intra-task controllers compared to uncontrolled systems or those using inter-task control.

Resource allocation for epidemic control in metapopulations.

PubMed

Ndeffo Mbah, Martial L; Gilligan, Christopher A

2011-01-01

Deployment of limited resources is an issue of major importance for decision-making in crisis events. This is especially true for large-scale outbreaks of infectious diseases. Little is known when it comes to identifying the most efficient way of deploying scarce resources for control when disease outbreaks occur in different but interconnected regions. The policy maker is frequently faced with the challenge of optimizing efficiency (e.g. minimizing the burden of infection) while accounting for social equity (e.g. equal opportunity for infected individuals to access treatment). For a large range of diseases described by a simple SIRS model, we consider strategies that should be used to minimize the discounted number of infected individuals during the course of an epidemic. We show that when faced with the dilemma of choosing between socially equitable and purely efficient strategies, the choice of the control strategy should be informed by key measurable epidemiological factors such as the basic reproductive number and the efficiency of the treatment measure. Our model provides new insights for policy makers in the optimal deployment of limited resources for control in the event of epidemic outbreaks at the landscape scale.

Earth Observation Data Quality Monitoring and Control: A Case Study of STAR Central Data Repository

NASA Astrophysics Data System (ADS)

Han, W.; Jochum, M.

2017-12-01

Earth observation data quality is very important for researchers and decision makers involved in weather forecasting, severe weather warning, disaster and emergency response, environmental monitoring, etc. Monitoring and control earth observation data quality, especially accuracy, completeness, and timeliness, is very useful in data management and governance to optimize data flow, discover potential transmission issues, and better connect data providers and users. Taking a centralized near real-time satellite data repository, STAR (Center for Satellite Applications and Research of NOAA) Central Data Repository (SCDR), as an example, this paper describes how to develop new mechanism to verify data integrity, check data completeness, and monitor data latency in an operational data management system. Such quality monitoring and control of large volume satellite data help data providers and managers improve data transmission of near real-time satellite data, enhance its acquisition and management, and overcome performance and management issues to better serve research and development activities.

A Coral Reef Algorithm Based on Learning Automata for the Coverage Control Problem of Heterogeneous Directional Sensor Networks

PubMed Central

Li, Ming; Miao, Chunyan; Leung, Cyril

2015-01-01

Coverage control is one of the most fundamental issues in directional sensor networks. In this paper, the coverage optimization problem in a directional sensor network is formulated as a multi-objective optimization problem. It takes into account the coverage rate of the network, the number of working sensor nodes and the connectivity of the network. The coverage problem considered in this paper is characterized by the geographical irregularity of the sensed events and heterogeneity of the sensor nodes in terms of sensing radius, field of angle and communication radius. To solve this multi-objective problem, we introduce a learning automata-based coral reef algorithm for adaptive parameter selection and use a novel Tchebycheff decomposition method to decompose the multi-objective problem into a single-objective problem. Simulation results show the consistent superiority of the proposed algorithm over alternative approaches. PMID:26690162

A Coral Reef Algorithm Based on Learning Automata for the Coverage Control Problem of Heterogeneous Directional Sensor Networks.

PubMed

Li, Ming; Miao, Chunyan; Leung, Cyril

2015-12-04

Coverage control is one of the most fundamental issues in directional sensor networks. In this paper, the coverage optimization problem in a directional sensor network is formulated as a multi-objective optimization problem. It takes into account the coverage rate of the network, the number of working sensor nodes and the connectivity of the network. The coverage problem considered in this paper is characterized by the geographical irregularity of the sensed events and heterogeneity of the sensor nodes in terms of sensing radius, field of angle and communication radius. To solve this multi-objective problem, we introduce a learning automata-based coral reef algorithm for adaptive parameter selection and use a novel Tchebycheff decomposition method to decompose the multi-objective problem into a single-objective problem. Simulation results show the consistent superiority of the proposed algorithm over alternative approaches.

A DDS-Based Energy Management Framework for Small Microgrid Operation and Control

DOE PAGES

Youssef, Tarek A.; El Hariri, Mohamad; Elsayed, Ahmed T.; ...

2017-09-26

The smart grid is seen as a power system with realtime communication and control capabilities between the consumer and the utility. This modern platform facilitates the optimization in energy usage based on several factors including environmental, price preferences, and system technical issues. In this paper a real-time energy management system (EMS) for microgrids or nanogrids was developed. The developed system involves an online optimization scheme to adapt its parameters based on previous, current, and forecasted future system states. The communication requirements for all EMS modules were analyzed and are all integrated over a data distribution service (DDS) Ethernet network withmore » appropriate quality of service (QoS) profiles. In conclusion, the developed EMS was emulated with actual residential energy consumption and irradiance data from Miami, Florida and proved its effectiveness in reducing consumers’ bills and achieving flat peak load profiles.« less

Increasing the technical level of mining haul trucks

NASA Astrophysics Data System (ADS)

Voronov, Yuri; Voronov, Artyom; Grishin, Sergey; Bujankin, Alexey

2017-11-01

Theoretical and methodological fundamentals of mining haul trucks optimal design are articulated. Methods based on the systems approach to integrated assessment of truck technical level and methods for optimization of truck parameters depending on performance standards are provided. The results of using these methods are given. The developed method allows not only assessing the truck technical levels but also choosing the most promising models and providing quantitative evaluations of the decisions to be made at the design stage. These areas are closely connected with the problem of improvement in the industrial output quality, which, being a part of the widely spread in Western world "total quality control" ideology, is one of the major issues for the Russian economy.

Availability Control for Means of Transport in Decisive Semi-Markov Models of Exploitation Process

NASA Astrophysics Data System (ADS)

Migawa, Klaudiusz

2012-12-01

The issues presented in this research paper refer to problems connected with the control process for exploitation implemented in the complex systems of exploitation for technical objects. The article presents the description of the method concerning the control availability for technical objects (means of transport) on the basis of the mathematical model of the exploitation process with the implementation of the decisive processes by semi-Markov. The presented method means focused on the preparing the decisive for the exploitation process for technical objects (semi-Markov model) and after that specifying the best control strategy (optimal strategy) from among possible decisive variants in accordance with the approved criterion (criteria) of the activity evaluation of the system of exploitation for technical objects. In the presented method specifying the optimal strategy for control availability in the technical objects means a choice of a sequence of control decisions made in individual states of modelled exploitation process for which the function being a criterion of evaluation reaches the extreme value. In order to choose the optimal control strategy the implementation of the genetic algorithm was chosen. The opinions were presented on the example of the exploitation process of the means of transport implemented in the real system of the bus municipal transport. The model of the exploitation process for the means of transports was prepared on the basis of the results implemented in the real transport system. The mathematical model of the exploitation process was built taking into consideration the fact that the model of the process constitutes the homogenous semi-Markov process.

YAPPA: a Compiler-Based Parallelization Framework for Irregular Applications on MPSoCs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lovergine, Silvia; Tumeo, Antonino; Villa, Oreste

Modern embedded systems include hundreds of cores. Because of the difficulty in providing a fast, coherent memory architecture, these systems usually rely on non-coherent, non-uniform memory architectures with private memories for each core. However, programming these systems poses significant challenges. The developer must extract large amounts of parallelism, while orchestrating communication among cores to optimize application performance. These issues become even more significant with irregular applications, which present data sets difficult to partition, unpredictable memory accesses, unbalanced control flow and fine grained communication. Hand-optimizing every single aspect is hard and time-consuming, and it often does not lead to the expectedmore » performance. There is a growing gap between such complex and highly-parallel architectures and the high level languages used to describe the specification, which were designed for simpler systems and do not consider these new issues. In this paper we introduce YAPPA (Yet Another Parallel Programming Approach), a compilation framework for the automatic parallelization of irregular applications on modern MPSoCs based on LLVM. We start by considering an efficient parallel programming approach for irregular applications on distributed memory systems. We then propose a set of transformations that can reduce the development and optimization effort. The results of our initial prototype confirm the correctness of the proposed approach.« less

i-SAIRAS '90; Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space, Kobe, Japan, Nov. 18-20, 1990

NASA Technical Reports Server (NTRS)

1990-01-01

The present conference on artificial intelligence (AI), robotics, and automation in space encompasses robot systems, lunar and planetary robots, advanced processing, expert systems, knowledge bases, issues of operation and management, manipulator control, and on-orbit service. Specific issues addressed include fundamental research in AI at NASA, the FTS dexterous telerobot, a target-capture experiment by a free-flying robot, the NASA Planetary Rover Program, the Katydid system for compiling KEE applications to Ada, and speech recognition for robots. Also addressed are a knowledge base for real-time diagnosis, a pilot-in-the-loop simulation of an orbital docking maneuver, intelligent perturbation algorithms for space scheduling optimization, a fuzzy control method for a space manipulator system, hyperredundant manipulator applications, robotic servicing of EOS instruments, and a summary of astronaut inputs on automation and robotics for the Space Station Freedom.

Optimization of controlled processes in combined-cycle plant (new developments and researches)

NASA Astrophysics Data System (ADS)

Tverskoy, Yu S.; Muravev, I. K.

2017-11-01

All modern complex technical systems, including power units of TPP and nuclear power plants, work in the system-forming structure of multifunctional APCS. The development of the modern APCS mathematical support allows bringing the automation degree to the solution of complex optimization problems of equipment heat-mass-exchange processes in real time. The difficulty of efficient management of a binary power unit is related to the need to solve jointly at least three problems. The first problem is related to the physical issues of combined-cycle technologies. The second problem is determined by the criticality of the CCGT operation to changes in the regime and climatic factors. The third problem is related to a precise description of a vector of controlled coordinates of a complex technological object. To obtain a joint solution of this complex of interconnected problems, the methodology of generalized thermodynamic analysis, methods of the theory of automatic control and mathematical modeling are used. In the present report, results of new developments and studies are shown. These results allow improving the principles of process control and the automatic control systems structural synthesis of power units with combined-cycle plants that provide attainable technical and economic efficiency and operational reliability of equipment.

3D Monte Carlo simulation of light propagation for laser acupuncture and optimization of illumination parameters

NASA Astrophysics Data System (ADS)

Zhong, Fulin; Li, Ting; Pan, Boan; Wang, Pengbo

2017-02-01

Laser acupuncture is an effective photochemical and nonthermal stimulation of traditional acupuncture points with lowintensity laser irradiation, which is advantageous in painless, sterile, and safe compared to traditional acupuncture. Laser diode (LD) provides single wavelength and relatively-higher power light for phototherapy. The quantitative effect of illumination parameters of LD in use of laser acupuncture is crucial for practical operation of laser acupuncture. However, this issue is not fully demonstrated, especially since experimental methodologies with animals or human are pretty hard to address to this issue. For example, in order to protect viability of cells and tissue, and get better therapeutic effect, it's necessary to control the output power varied at 5mW 10mW range, while the optimized power is still not clear. This study aimed to quantitatively optimize the laser output power, wavelength, and irradiation direction with highly realistic modeling of light transport in acupunctured tissue. A Monte Carlo Simulation software for 3D vowelized media and the highest-precision human anatomical model Visible Chinese Human (VCH) were employed. Our 3D simulation results showed that longer wavelength/higher illumination power, larger absorption in laser acupuncture; the vertical direction emission of the acupuncture laser results in higher amount of light absorption in both the acupunctured voxel of tissue and muscle layer. Our 3D light distribution of laser acupuncture within VCH tissue model is potential to be used in optimization and real time guidance in clinical manipulation of laser acupuncture.

Aerospace Non Chrome Corrosion Inhibiting Primer Systems

DTIC Science & Technology

2009-09-01

Meet all HSE specifications, TSCA, REACh, Akzo • Strippable • No weight increase over current system • Meet specification requirements for corrosion, not...Positive and negative controls • Primer only and topcoated samples Aerospace Coatings | Title 9 OEM CF Optimization/ Down Selects •Usual issues...found to be true • Good NSS ≠ Good filiform ≠ Good cure ≠ Good application properties • Down select process is to minimize ≠ and move to a balance of

Automating the design of scientific computing software

NASA Technical Reports Server (NTRS)

Kant, Elaine

1992-01-01

SINAPSE is a domain-specific software design system that generates code from specifications of equations and algorithm methods. This paper describes the system's design techniques (planning in a space of knowledge-based refinement and optimization rules), user interaction style (user has option to control decision making), and representation of knowledge (rules and objects). It also summarizes how the system knowledge has evolved over time and suggests some issues in building software design systems to facilitate reuse.

Feedback-tuned, noise resilient gates for encoded spin qubits

NASA Astrophysics Data System (ADS)

Bluhm, Hendrik

Spin 1/2 particles form native two level systems and thus lend themselves as a natural qubit implementation. However, encoding a single qubit in several spins entails benefits, such as reducing the resources necessary for qubit control and protection from certain decoherence channels. While several varieties of such encoded spin qubits have been implemented, accurate control remains challenging, and leakage out of the subspace of valid qubit states is a potential issue. Optimal performance typically requires large pulse amplitudes for fast control, which is prone to systematic errors and prohibits standard control approaches based on Rabi flopping. Furthermore, the exchange interaction typically used to electrically manipulate encoded spin qubits is inherently sensitive to charge noise. I will discuss all-electrical, high-fidelity single qubit operations for a spin qubit encoded in two electrons in a GaAs double quantum dot. Starting from a set of numerically optimized control pulses, we employ an iterative tuning procedure based on measured error syndromes to remove systematic errors.Randomized benchmarking yields an average gate fidelity exceeding 98 % and a leakage rate into invalid states of 0.2 %. These gates exhibit a certain degree of resilience to both slow charge and nuclear spin fluctuations due to dynamical correction analogous to a spin echo. Furthermore, the numerical optimization minimizes the impact of fast charge noise. Both types of noise make relevant contributions to gate errors. The general approach is also adaptable to other qubit encodings and exchange based two-qubit gates.

A Framework for WWW Query Processing

NASA Technical Reports Server (NTRS)

Wu, Binghui Helen; Wharton, Stephen (Technical Monitor)

2000-01-01

Query processing is the most common operation in a DBMS. Sophisticated query processing has been mainly targeted at a single enterprise environment providing centralized control over data and metadata. Submitting queries by anonymous users on the web is different in such a way that load balancing or DBMS' accessing control becomes the key issue. This paper provides a solution by introducing a framework for WWW query processing. The success of this framework lies in the utilization of query optimization techniques and the ontological approach. This methodology has proved to be cost effective at the NASA Goddard Space Flight Center Distributed Active Archive Center (GDAAC).

Applications in Robotics and Controls

NASA Astrophysics Data System (ADS)

Youcef-Toumi, Kamal

2008-06-01

Recent industry trends have set new standards in business dealings and trades. Issues such as time to market, shoter market wondows, product performance, rapid increase of product complexity, costly mistakes, costly late introductions, and customer expectations have changed significantly. These trends have also influenced to a great extend the academic world. Some of these trends will be illustrated through examples which include automated systems, robotics, biotechnollogy, and nanotechnology. The examples will include concepts and prototypes of engineering systems in the macro, micro and nanodomains. The presentation also amphasizes the merging of the traditionally segregated disciplines into one multidisciplinary modeling, design, optimization and control approach.

Optimal control of fuel overpressure in a polymer electrolyte membrane fuel cell with hydrogen transfer leak during load change

NASA Astrophysics Data System (ADS)

Ebadighajari, Alireza; DeVaal, Jake; Golnaraghi, Farid

2017-02-01

Formation of membrane pinholes is a common defect in fuel cells, inflicting more cost and making less durable cells. This work focuses on mitigating this issue, and offers a continuous online treatment instead of attempting to dynamically model the hydrogen transfer leak rate. This is achieved by controlling the differential pressure between the anode and cathode compartments at the inlet side of the fuel cell stack, known as the fuel overpressure. The model predictive control approach is used to attain the objectives in a Ballard 9-cell Mk1100 polymer electrolyte membrane fuel cell (PEMFC) with inclusion of hydrogen transfer leak. Furthermore, the pneumatic modeling technique is used to model the entire anode side of a fuel cell station. The hydrogen transfer leak is embedded in the model in a novel way, and is considered as a disturbance during the controller design. Experimental results for different sizes of hydrogen transfer leaks are provided to show the benefits of fuel overpressure control system in alleviating the effects of membrane pinholes, which in turn increases membrane longevity, and reduces hydrogen emissions in the eventual presence of transfer leaks. Moreover, the model predictive controller provides an optimal control input while satisfying the problem constraints.

Big Data Challenges of High-Dimensional Continuous-Time Mean-Variance Portfolio Selection and a Remedy.

PubMed

Chiu, Mei Choi; Pun, Chi Seng; Wong, Hoi Ying

2017-08-01

Investors interested in the global financial market must analyze financial securities internationally. Making an optimal global investment decision involves processing a huge amount of data for a high-dimensional portfolio. This article investigates the big data challenges of two mean-variance optimal portfolios: continuous-time precommitment and constant-rebalancing strategies. We show that both optimized portfolios implemented with the traditional sample estimates converge to the worst performing portfolio when the portfolio size becomes large. The crux of the problem is the estimation error accumulated from the huge dimension of stock data. We then propose a linear programming optimal (LPO) portfolio framework, which applies a constrained ℓ 1 minimization to the theoretical optimal control to mitigate the risk associated with the dimensionality issue. The resulting portfolio becomes a sparse portfolio that selects stocks with a data-driven procedure and hence offers a stable mean-variance portfolio in practice. When the number of observations becomes large, the LPO portfolio converges to the oracle optimal portfolio, which is free of estimation error, even though the number of stocks grows faster than the number of observations. Our numerical and empirical studies demonstrate the superiority of the proposed approach. © 2017 Society for Risk Analysis.

Optimizing Wartime Materiel Delivery: An Overview of DoD containerization. Volume 2. Framework for Action to Address DoD Containerization Issues

DOT National Transportation Integrated Search

1988-10-01

This second volume of the study entitled, Optimizing Wartime Materiel Delivery: An Overview of DOD Containerization Efforts, -outlines a framework for action to address containerization issues identified in Volume I. The objectives of the study inclu...

Experimental confirmation of a PDE-based approach to design of feedback controls

NASA Technical Reports Server (NTRS)

Banks, H. T.; Smith, Ralph C.; Brown, D. E.; Silcox, R. J.; Metcalf, Vern L.

1995-01-01

Issues regarding the experimental implementation of partial differential equation based controllers are discussed in this work. While the motivating application involves the reduction of vibration levels for a circular plate through excitation of surface-mounted piezoceramic patches, the general techniques described here will extend to a variety of applications. The initial step is the development of a PDE model which accurately captures the physics of the underlying process. This model is then discretized to yield a vector-valued initial value problem. Optimal control theory is used to determine continuous-time voltages to the patches, and the approximations needed to facilitate discrete time implementation are addressed. Finally, experimental results demonstrating the control of both transient and steady state vibrations through these techniques are presented.

An extended ASLD trading system to enhance portfolio management.

PubMed

Hung, Kei-Keung; Cheung, Yiu-Ming; Xu, Lei

2003-01-01

An adaptive supervised learning decision (ASLD) trading system has been presented by Xu and Cheung (1997) to optimize the expected returns of investment without considering risks. In this paper, we propose an extension of the ASLD system (EASLD), which combines the ASLD with a portfolio optimization scheme to take a balance between the expected returns and risks. This new system not only keeps the learning adaptability of the ASLD, but also dynamically controls the risk in pursuit of great profits by diversifying the capital to a time-varying portfolio of N assets. Consequently, it is shown that: 1) the EASLD system gives the investment risk much smaller than the ASLD one; and 2) more returns are gained through the EASLD system in comparison with the two individual portfolio optimization schemes that statically determine the portfolio weights without adaptive learning. We have justified these two issues by the experiments.

LQR-Based Optimal Distributed Cooperative Design for Linear Discrete-Time Multiagent Systems.

PubMed

Zhang, Huaguang; Feng, Tao; Liang, Hongjing; Luo, Yanhong

2017-03-01

In this paper, a novel linear quadratic regulator (LQR)-based optimal distributed cooperative design method is developed for synchronization control of general linear discrete-time multiagent systems on a fixed, directed graph. Sufficient conditions are derived for synchronization, which restrict the graph eigenvalues into a bounded circular region in the complex plane. The synchronizing speed issue is also considered, and it turns out that the synchronizing region reduces as the synchronizing speed becomes faster. To obtain more desirable synchronizing capacity, the weighting matrices are selected by sufficiently utilizing the guaranteed gain margin of the optimal regulators. Based on the developed LQR-based cooperative design framework, an approximate dynamic programming technique is successfully introduced to overcome the (partially or completely) model-free cooperative design for linear multiagent systems. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design methods.

Robust decentralized control laws for the ACES structure

NASA Technical Reports Server (NTRS)

Collins, Emmanuel G., Jr.; Phillips, Douglas J.; Hyland, David C.

1991-01-01

Control system design for the Active Control Technique Evaluation for Spacecraft (ACES) structure at NASA Marshall Space Flight Center is discussed. The primary objective of this experiment is to design controllers that provide substantial reduction of the line-of-sight pointing errors. Satisfaction of this objective requires the controllers to attenuate beam vibration significantly. The primary method chosen for control design is the optimal projection approach for uncertain systems (OPUS). The OPUS design process allows the simultaneous tradeoff of five fundamental issues in control design: actuator sizing, sensor accuracy, controller order, robustness, and system performance. A brief description of the basic ACES configuration is given. The development of the models used for control design and control design for eight system loops that were selected by analysis of test data collected from the structure are discussed. Experimental results showing that very significant performance improvement is achieved when all eight feedback loops are closed are presented.

Radar coordination and resource management in a distributed sensor network using emergent control

NASA Astrophysics Data System (ADS)

Weir, B. S.; Sokol, T. M.

2009-05-01

As the list of anti-air warfare and ballistic missile defense missions grows, there is an increasing need to coordinate and optimize usage of radar resources across the netted force. Early attempts at this optimization involved top-down control mechanisms whereby sensors accept resource tasking orders from networked tracking elements. These approaches rely heavily on uncertain knowledge of sensor constraints and capabilities. Furthermore, advanced sensor systems may support self-defense missions of the host platform and are therefore unable to relinquish control to an external function. To surmount these issues, the use of bottom-up emergent control techniques is proposed. The information necessary to make quality, network-wide resource allocations is readily available to sensor nodes with access to a netted track picture. By assessing resource priorities relative to the network (versus local) track picture, sensors can understand the contribution of their resources to the netted force. This allows the sensors to apply resources where most needed and remove waste. Furthermore, simple local rules for resource usage, when properly constructed, allow sensors to obtain a globally optimal resource allocation without direct coordination (emergence). These results are robust to partial implementation (i.e., not all nodes upgraded at once) and failures on individual nodes (whether from casualty or reallocation to other sensor missions), and they leave resource control decisions in the hands of the sensor systems instead of an external function. This paper presents independent research and development work on emergent control of sensor resources and the impact to resource allocation and tracking performance.

Energy optimization in mobile sensor networks

NASA Astrophysics Data System (ADS)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.

Issues and challenges in resource management and its interaction with levels 2/3 fusion with applications to real-world problems: an annotated perspective

NASA Astrophysics Data System (ADS)

Blasch, Erik; Kadar, Ivan; Hintz, Kenneth; Biermann, Joachim; Chong, Chee-Yee; Salerno, John; Das, Subrata

2007-04-01

Resource management (or process refinement) is critical for information fusion operations in that users, sensors, and platforms need to be informed, based on mission needs, on how to collect, process, and exploit data. To meet these growing concerns, a panel session was conducted at the International Society of Information Fusion Conference in 2006 to discuss the various issues surrounding the interaction of Resource Management with Level 2/3 Situation and Threat Assessment. This paper briefly consolidates the discussion of the invited panel panelists. The common themes include: (1) Addressing the user in system management, sensor control, and knowledge based information collection (2) Determining a standard set of fusion metrics for optimization and evaluation based on the application (3) Allowing dynamic and adaptive updating to deliver timely information needs and information rates (4) Optimizing the joint objective functions at all information fusion levels based on decision-theoretic analysis (5) Providing constraints from distributed resource mission planning and scheduling; and (6) Defining L2/3 situation entity definitions for knowledge discovery, modeling, and information projection

Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks

PubMed Central

Ahmed, Gulnaz; Zou, Jianhua; Zhao, Xi; Sadiq Fareed, Mian Muhammad

2017-01-01

The longer network lifetime of Wireless Sensor Networks (WSNs) is a goal which is directly related to energy consumption. This energy consumption issue becomes more challenging when the energy load is not properly distributed in the sensing area. The hierarchal clustering architecture is the best choice for these kind of issues. In this paper, we introduce a novel clustering protocol called Markov chain model-based optimal cluster heads (MOCHs) selection for WSNs. In our proposed model, we introduce a simple strategy for the optimal number of cluster heads selection to overcome the problem of uneven energy distribution in the network. The attractiveness of our model is that the BS controls the number of cluster heads while the cluster heads control the cluster members in each cluster in such a restricted manner that a uniform and even load is ensured in each cluster. We perform an extensive range of simulation using five quality measures, namely: the lifetime of the network, stable and unstable region in the lifetime of the network, throughput of the network, the number of cluster heads in the network, and the transmission time of the network to analyze the proposed model. We compare MOCHs against Sleep-awake Energy Efficient Distributed (SEED) clustering, Artificial Bee Colony (ABC), Zone Based Routing (ZBR), and Centralized Energy Efficient Clustering (CEEC) using the above-discussed quality metrics and found that the lifetime of the proposed model is almost 1095, 2630, 3599, and 2045 rounds (time steps) greater than SEED, ABC, ZBR, and CEEC, respectively. The obtained results demonstrate that the MOCHs is better than SEED, ABC, ZBR, and CEEC in terms of energy efficiency and the network throughput. PMID:28241492

Development of Variable Camber Continuous Trailing Edge Flap for Performance Adaptive Aeroelastic Wing

NASA Technical Reports Server (NTRS)

Nguyen, Nhan; Kaul, Upender; Lebofsky, Sonia; Ting, Eric; Chaparro, Daniel; Urnes, James

2015-01-01

This paper summarizes the recent development of an adaptive aeroelastic wing shaping control technology called variable camber continuous trailing edge flap (VCCTEF). As wing flexibility increases, aeroelastic interactions with aerodynamic forces and moments become an increasingly important consideration in aircraft design and aerodynamic performance. Furthermore, aeroelastic interactions with flight dynamics can result in issues with vehicle stability and control. The initial VCCTEF concept was developed in 2010 by NASA under a NASA Innovation Fund study entitled "Elastically Shaped Future Air Vehicle Concept," which showed that highly flexible wing aerodynamic surfaces can be elastically shaped in-flight by active control of wing twist and bending deflection in order to optimize the spanwise lift distribution for drag reduction. A collaboration between NASA and Boeing Research & Technology was subsequently funded by NASA from 2012 to 2014 to further develop the VCCTEF concept. This paper summarizes some of the key research areas conducted by NASA during the collaboration with Boeing Research and Technology. These research areas include VCCTEF design concepts, aerodynamic analysis of VCCTEF camber shapes, aerodynamic optimization of lift distribution for drag minimization, wind tunnel test results for cruise and high-lift configurations, flutter analysis and suppression control of flexible wing aircraft, and multi-objective flight control for adaptive aeroelastic wing shaping control.

General purpose optimization software for engineering design

NASA Technical Reports Server (NTRS)

Vanderplaats, G. N.

1990-01-01

The author has developed several general purpose optimization programs over the past twenty years. The earlier programs were developed as research codes and served that purpose reasonably well. However, in taking the formal step from research to industrial application programs, several important lessons have been learned. Among these are the importance of clear documentation, immediate user support, and consistent maintenance. Most important has been the issue of providing software that gives a good, or at least acceptable, design at minimum computational cost. Here, the basic issues developing optimization software for industrial applications are outlined and issues of convergence rate, reliability, and relative minima are discussed. Considerable feedback has been received from users, and new software is being developed to respond to identified needs. The basic capabilities of this software are outlined. A major motivation for the development of commercial grade software is ease of use and flexibility, and these issues are discussed with reference to general multidisciplinary applications. It is concluded that design productivity can be significantly enhanced by the more widespread use of optimization as an everyday design tool.

Spacesuit Radiation Shield Design Methods

NASA Technical Reports Server (NTRS)

Wilson, John W.; Anderson, Brooke M.; Cucinotta, Francis A.; Ware, J.; Zeitlin, Cary J.

2006-01-01

Meeting radiation protection requirements during EVA is predominantly an operational issue with some potential considerations for temporary shelter. The issue of spacesuit shielding is mainly guided by the potential of accidental exposure when operational and temporary shelter considerations fail to maintain exposures within operational limits. In this case, very high exposure levels are possible which could result in observable health effects and even be life threatening. Under these assumptions, potential spacesuit radiation exposures have been studied using known historical solar particle events to gain insight on the usefulness of modification of spacesuit design in which the control of skin exposure is a critical design issue and reduction of blood forming organ exposure is desirable. Transition to a new spacesuit design including soft upper-torso and reconfigured life support hardware gives an opportunity to optimize the next generation spacesuit for reduced potential health effects during an accidental exposure.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martino, Mikaël M.; Briquez, Priscilla S.; Maruyama, Kenta

Growth factors are very promising molecules to enhance bone regeneration. However, their translation to clinical use has been seriously limited, facing issues related to safety and cost-effectiveness. These problems derive from the vastly supra-physiological doses of growth factor used without optimized delivery systems. Therefore, these issues have motivated the development of new delivery systems allowing better control of the spatio-temporal release and signaling of growth factors. Because the extracellular matrix (ECM) naturally plays a fundamental role in coordinating growth factor activity in vivo, a number of novel delivery systems have been inspired by the growth factor regulatory function of themore » ECM. After introducing the role of growth factors during the bone regeneration process, this review exposes different issues that growth factor-based therapies have encountered in the clinic and highlights recent delivery approaches based on the natural interaction between growth factor and the ECM.« less

Management of epilepsy during pregnancy: an update

PubMed Central

Patel, Sima I.; Pennell, Page B.

2015-01-01

The clinical management of women with epilepsy on antiepileptic drugs (AEDs) during pregnancy presents unique challenges. The goal of treatment is optimal seizure control with minimal in utero fetal exposure to AEDs in an effort to reduce the risk of structural and neurodevelopmental teratogenic effects. This paper reviews the following key issues pertaining to women with epilepsy during pregnancy: AED pharmacokinetics; clinical management of AEDs; seizure frequency; major congenital malformation; neurodevelopmental outcomes; perinatal complications; and breast feeding. PMID:27006699

Propulsion/airframe integration issues for waverider aircraft

NASA Technical Reports Server (NTRS)

Blankson, Isaiah M.; Hagseth, Paul

1993-01-01

While many propulsion concepts and technologies developed for nonwaverider-type hypersonic vehicles may apply to waveriders, some aspects of these configurations require unique technological approaches. An evaluation is made of such distinctive opportunities in the cases of engine cycle selection, inlets, nozzle designs and integration, longitudinal stability, and thermal management. Also discussed are waverider requirements for control surface effectiveness, inlet boundary layer ingestion effects, and structural/configurational optimization, giving attention to trades in volumetric/structural efficiency and vehicle L/D.

Evidence-based practice: management of glottic cancer.

PubMed

Hartl, Dana M

2012-10-01

The main issue in the management of glottic squamous cell carcinoma, as for all cancers, is adequate disease control while optimizing functional outcomes and minimizing morbidity. This is true for early-stage disease as for advanced tumors. This article evaluates the current evidence for the diagnostic and pretherapeutic workup for glottic squamous cell carcinoma and the evidence concerning different treatment options for glottic carcinoma, from early-stage to advanced-stage disease. Copyright © 2012 Elsevier Inc. All rights reserved.

Standards of care issues with anticoagulation in real-world populations.

PubMed

2015-01-01

Current guidelines recommend anticoagulants for reducing the risk of stroke in appropriate patients with nonvalvular atrial fibrillation (NVAF) and for the acute treatment of venous thromboembolism (VTE) and the prevention of recurrent VTE. Warfarin is the standard of care for both NVAF and VTE, yet International Normalized Ratio (INR) control remains suboptimal, even in the clinical trial setting. Maintaining INR within the recommended therapeutic range is associated with better outcomes in these distinct populations. In VTE, high rates of recurrence have been reported during the first few weeks of treatment, emphasizing the importance of surveillance during this time and of early optimization of anticoagulation therapy. The NVAF population tends to have more comorbidities and requires longer-term therapy. It is important to keep in mind that real-world patient populations are more complex than those in controlled studies. Patients with multiple comorbidities are particularly challenging, and physicians may focus on clinically urgent issues rather than anticoagulation optimization. Despite the many complexities associated with the use of warfarin, it remains a mainstay of anticoagulation therapy. Aligning financial incentives and improving care coordination are important factors in moving toward better outcomes for patients who need anticoagulation therapy. The increased focus on value-based care and evolving approaches to patient treatment could lead more physicians and payers to consider alternatives to warfarin, including the use of novel oral anticoagulants.

Optimized Structures for Low-Profile Phase Change Thermal Spreaders

NASA Astrophysics Data System (ADS)

Sharratt, Stephen Andrew

Thin, low-profile phase change thermal spreaders can provide cooling solutions for some of today's most pressing heat flux dissipation issues. These thermal issues are only expected to increase as future electronic circuitry requirements lead to denser and potentially 3D chip packaging. Phase change based heat spreaders, such as heat pipes or vapor chambers, can provide a practical solution for effectively dissipating large heat fluxes. This thesis reports a comprehensive study of state-of-the-art capillary pumped wick structures using computational modeling, micro wick fabrication, and experimental analysis. Modeling efforts focus on predicting the shape of the liquid meniscus inside a complicated 3D wick structure. It is shown that this liquid shape can drastically affect the wick's thermal resistance. In addition, knowledge of the liquid meniscus shape allows for the computation of key parameters such as permeability and capillary pressure which are necessary for predicting the maximum heat flux. After the model is validated by comparison to experimental results, the wick structure is optimized so as to decrease overall wick thermal resistance and increase the maximum capillary limited heat flux before dryout. The optimized structures are then fabricated out of both silicon and copper using both traditional and novel micro-fabrication techniques. The wicks are made super-hydrophilic using chemical and thermal oxidation schemes. A sintered monolayer of Cu particles is fabricated and analyzed as well. The fabricated wick structures are experimentally tested for their heat transfer performance inside a well controlled copper vacuum chamber. Heat fluxes as high as 170 W/cm2 are realized for Cu wicks with structure heights of 100 μm. The structures optimized for both minimized thermal resistance and high liquid supply ability perform much better than their non-optimized counterparts. The super-hydrophilic oxidation scheme is found to drastically increase the maximum heat flux and decrease thermal resistance. This research provides key insights as to how to optimize heat pipe structures to minimize thermal resistance and increase maximum heat flux. These thin wick structures can also be combined with a thicker liquid supply layer so that thin, low-resistance evaporator layers can be constructed and higher heat fluxes realized. The work presented in this thesis can be used to aid in the development of high-performance phase change thermal spreaders, allowing for temperature control of a variety of powerful electronic components.

Nutritional support for children with epidermolysis bullosa.

PubMed

Haynes, Lesley

Epidermolysis bullosa (EB) comprises a rare group of genetically determined skin blistering disorders characterized by extreme fragility of the skin and mucous membranes, with recurrent blister formation. The cornerstones of management are control of infection, wound management, pain relief, promotion of optimal nutritional status and mobility, surgical intervention and provision of the best possible quality of life. There is currently no cure for EB and, throughout life, those with the more severe types are at risk of significant nutritional compromise which impacts negatively on health and overall quality of life. Nutritional support is an important facet of holistic care and the dietetic challenges can be considerable. This paper describes some of the issues involved in optimizing the nutritional status of children with this disorder.

Generalization of Water Pricing Model in Agriculture and Domestic Groundwater for Water Sustainability and Conservation

NASA Astrophysics Data System (ADS)

Hek, Tan Kim; Fadzli Ramli, Mohammad; Iryanto; Rohana Goh, Siti; Zaki, Mohd Faiz M.

2018-03-01

The water requirement greatly increased due to population growth, increased agricultural areas and industrial development, thus causing high water demand. The complex problems facing by country is water pricing is not designed optimally as a staple of human needs and on the other hand also cannot guarantee the maintenance and distribution of water effectively. The cheap water pricing caused increase of water use and unmanageable water resource. Therefore, the more optimal water pricing as an effective control of water policy is needed for the sake of ensuring water resources conservation and sustainability. This paper presents the review on problems, issues and mathematical modelling of water pricing based on agriculture and domestic groundwater for water sustainability and conservation.

The role of veterinary research laboratories in the provision of veterinary services.

PubMed

Verwoerd, D W

1998-08-01

Veterinary research laboratories play an essential role in the provision of veterinary services in most countries. These laboratories are the source of new knowledge, innovative ideas and improved technology for the surveillance, prevention and control of animal diseases. In addition, many laboratories provide diagnostic and other services. To ensure the optimal integration of various veterinary activities, administrators must understand the functions and constraints of research laboratories. Therefore, a brief discussion is presented of the following: organisational structures methods for developing research programmes outputs of research scientists and how these are measured the management of quality assurance funding of research. Optimal collaboration can only be attained by understanding the environment in which a research scientist functions and the motivational issues at stake.

Tackling optimization challenges in industrial load control and full-duplex radios

NASA Astrophysics Data System (ADS)

Gholian, Armen

In price-based demand response programs in smart grid, utilities set the price in accordance with the grid operating conditions and consumers respond to price signals by conducting optimal load control to minimize their energy expenditure while satisfying their energy needs. Industrial sector consumes a large portion of world electricity and addressing optimal load control of energy-intensive industrial complexes, such as steel industry and oil-refinery, is of practical importance. Formulating a general industrial complex and addressing issues in optimal industrial load control in smart grid is the focus of the second part of this dissertation. Several industrial load details are considered in the proposed formulation, including those that do not appear in residential or commercial load control problems. Operation under different smart pricing scenarios, namely, day-ahead pricing, time-of-use pricing, peak pricing, inclining block rates, and critical peak pricing are considered. The use of behind-the-meter renewable generation and energy storage is also considered. The formulated optimization problem is originally nonlinear and nonconvex and thus hard to solve. However, it is then reformulated into a tractable linear mixed-integer program. The performance of the design is assessed through various simulations for an oil refinery and a steel mini-mill. In the third part of this dissertation, a novel all-analog RF interference canceler is proposed. Radio self-interference cancellation (SIC) is the fundamental enabler for full-duplex radios. While SIC methods based on baseband digital signal processing and/or beamforming are inadequate, an all-analog method is useful to drastically reduce the self-interference as the first stage of SIC. It is shown that a uniform architecture with uniformly distributed RF attenuators has a performance highly dependent on the carrier frequency. It is also shown that a new architecture with the attenuators distributed in a clustered fashion has important advantages over the uniform architecture. These advantages are shown numerically through random multipath interference channels, number of control bits in step attenuators, attenuation-dependent phases, single and multi-level structures, etc.

2001 Gordon Research Conference on Quantum Control of Light and Matter. Final progress report [agenda and attendee list

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shapiro, Moshe

2001-08-03

The Gordon Research Conference on Quantum Control of Light and Matter [Quantum Control of Atomic and Molecular Motion] was held at Mount Holyoke College, South Hadley, Massachusetts, July 29 - August 3, 2001. The conference was attended by 119 participants. The attendees represented the spectrum of endeavor in this field, coming from academia, industry, and government laboratories, and included US and foreign scientists, senior researchers, young investigators, and students. Emphasis was placed on current unpublished research and discussion of the future target areas in this field. There was a conscious effort to stimulate discussion about the key issues in themore » field today. Session topics included the following: General perspectives, Phase control, Optimal control, Quantum information, Light manipulation and manipulation with light, Control in the condensed phase, Strong field control, Laser cooling and Bose-Einstein Condensate dynamics, and Control in the solid phase.« less

A non-autonomous optimal control model of renewable energy production under the aspect of fluctuating supply and learning by doing.

PubMed

Moser, Elke; Grass, Dieter; Tragler, Gernot

Given the constantly raising world-wide energy demand and the accompanying increase in greenhouse gas emissions that pushes the progression of climate change, the possibly most important task in future is to find a carbon-low energy supply that finds the right balance between sustainability and energy security. For renewable energy generation, however, especially the second aspect turns out to be difficult as the supply of renewable sources underlies strong volatility. Further on, investment costs for new technologies are so high that competitiveness with conventional energy forms is hard to achieve. To address this issue, we analyze in this paper a non-autonomous optimal control model considering the optimal composition of a portfolio that consists of fossil and renewable energy and which is used to cover the energy demand of a small country. While fossil energy is assumed to be constantly available, the supply of the renewable resource fluctuates seasonally. We further on include learning effects for the renewable energy technology, which will underline the importance of considering the whole life span of such a technology for long-term energy planning decisions.

Determining optimal parameters in magnetic spacecraft stabilization via attitude feedback

NASA Astrophysics Data System (ADS)

Bruni, Renato; Celani, Fabio

2016-10-01

The attitude control of a spacecraft using magnetorquers can be achieved by a feedback control law which has four design parameters. However, the practical determination of appropriate values for these parameters is a critical open issue. We propose here an innovative systematic approach for finding these values: they should be those that minimize the convergence time to the desired attitude. This a particularly diffcult optimization problem, for several reasons: 1) such time cannot be expressed in analytical form as a function of parameters and initial conditions; 2) design parameters may range over very wide intervals; 3) convergence time depends also on the initial conditions of the spacecraft, which are not known in advance. To overcome these diffculties, we present a solution approach based on derivative-free optimization. These algorithms do not need to write analytically the objective function: they only need to compute it in a number of points. We also propose a fast probing technique to identify which regions of the search space have to be explored densely. Finally, we formulate a min-max model to find robust parameters, namely design parameters that minimize convergence time under the worst initial conditions. Results are very promising.

Optimal harvesting for a predator-prey agent-based model using difference equations.

PubMed

Oremland, Matthew; Laubenbacher, Reinhard

2015-03-01

In this paper, a method known as Pareto optimization is applied in the solution of a multi-objective optimization problem. The system in question is an agent-based model (ABM) wherein global dynamics emerge from local interactions. A system of discrete mathematical equations is formulated in order to capture the dynamics of the ABM; while the original model is built up analytically from the rules of the model, the paper shows how minor changes to the ABM rule set can have a substantial effect on model dynamics. To address this issue, we introduce parameters into the equation model that track such changes. The equation model is amenable to mathematical theory—we show how stability analysis can be performed and validated using ABM data. We then reduce the equation model to a simpler version and implement changes to allow controls from the ABM to be tested using the equations. Cohen's weighted κ is proposed as a measure of similarity between the equation model and the ABM, particularly with respect to the optimization problem. The reduced equation model is used to solve a multi-objective optimization problem via a technique known as Pareto optimization, a heuristic evolutionary algorithm. Results show that the equation model is a good fit for ABM data; Pareto optimization provides a suite of solutions to the multi-objective optimization problem that can be implemented directly in the ABM.

ISS-Crystal Growth of Photorefractive Materials (BSO): Critical Design Issues for Optimized Data Extraction from Space Experiments

NASA Technical Reports Server (NTRS)

Hyers, Robert W.; Motakef, S.; Witt, A. F.; Wuensch, B.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

Realization of the full potential of photorefractive materials in device technology is seriously impeded by our inability to achieve controlled formation of critical defects during single crystal growth and by difficulties in meeting the required degree of compositional uniformity on a micro-scale over macroscopic dimensions. The exact nature and origin of the critical defects which control photorefractivity could not as yet be identified because of gravitational interference. There exists, however, strong evidence that the density of defect formation and their spatial distribution are adversely affected by gravitational interference which precludes the establishment of quantifiable and controllable heat and mass transfer conditions during crystal growth. The current, NASA sponsored research at MIT is directed at establishing a basis for the development of a comprehensive approach to the optimization of property control during melt growth of photorefractive materials, making use of the m-g environment, provided in the International Space Station. The objectives to be pursued in m-g research on photorefractive BSO (Bi12SiO20) are: (a) identification of the x-level(s) responsible for photorefractivity in undoped BSO; (b) development of approaches leading to the control of x-level formation at uniform spatial distribution; (c) development of doping and processing procedures for optimization of the critical, application specific parameters, spectral response, sensitivity, response time and matrix stability. The presentation will focus on: the rationale for the justification of the space experiment, ground-based development efforts, design considerations for the space experiments, strategic plan of the space experiments, and approaches to the quantitative analysis of the space experiments.

Automatic Speech Recognition in Air Traffic Control: a Human Factors Perspective

NASA Technical Reports Server (NTRS)

Karlsson, Joakim

1990-01-01

The introduction of Automatic Speech Recognition (ASR) technology into the Air Traffic Control (ATC) system has the potential to improve overall safety and efficiency. However, because ASR technology is inherently a part of the man-machine interface between the user and the system, the human factors issues involved must be addressed. Here, some of the human factors problems are identified and related methods of investigation are presented. Research at M.I.T.'s Flight Transportation Laboratory is being conducted from a human factors perspective, focusing on intelligent parser design, presentation of feedback, error correction strategy design, and optimal choice of input modalities.

A control approach for robots with flexible links and rigid end-effectors

NASA Technical Reports Server (NTRS)

Barbieri, Enrique; Ozguner, Umit

1989-01-01

Multiarm flexible robots with dexterous end effectors are currently being considered in such tasks as satellite retrieval, servicing and repair where a two phase problem can be identified: Phase 1, robot positioning in space; Phase 2, object retrieval. Some issues in Phase 1 regarding modelling and control strategies for a robotic system comprised of along flexible arm and a rigid three-link end effector are presented. The control objective is to maintain the last (rigid) link stationary in space in the presence of an additive disturbance caused by the flexible energy in the first link after a positioning maneuver has been accomplished. Several configuration strategies can be considered, and optimal decentralized servocompensators can be designed. Preliminary computer simulations are included for a simple proportional controller to illustrate the approach.

Topology synthesis and size optimization of morphing wing structures

NASA Astrophysics Data System (ADS)

Inoyama, Daisaku

This research demonstrates a novel topology and size optimization methodology for synthesis of distributed actuation systems with specific applications to morphing air vehicle structures. The main emphasis is placed on the topology and size optimization problem formulations and the development of computational modeling concepts. The analysis model is developed to meet several important criteria: It must allow a rigid-body displacement, as well as a variation in planform area, with minimum strain on structural members while retaining acceptable numerical stability for finite element analysis. Topology optimization is performed on a semi-ground structure with design variables that control the system configuration. In effect, the optimization process assigns morphing members as "soft" elements, non-morphing load-bearing members as "stiff' elements, and non-existent members as "voids." The optimization process also determines the optimum actuator placement, where each actuator is represented computationally by equal and opposite nodal forces with soft axial stiffness. In addition, the configuration of attachments that connect the morphing structure to a non-morphing structure is determined simultaneously. Several different optimization problem formulations are investigated to understand their potential benefits in solution quality, as well as meaningfulness of the formulations. Extensions and enhancements to the initial concept and problem formulations are made to accommodate multiple-configuration definitions. In addition, the principal issues on the external-load dependency and the reversibility of a design, as well as the appropriate selection of a reference configuration, are addressed in the research. The methodology to control actuator distributions and concentrations is also discussed. Finally, the strategy to transfer the topology solution to the sizing optimization is developed and cross-sectional areas of existent structural members are optimized under applied aerodynamic loads. That is, the optimization process is implemented in sequential order: The actuation system layout is first determined through multi-disciplinary topology optimization process, and then the thickness or cross-sectional area of each existent member is optimized under given constraints and boundary conditions. Sample problems are solved to demonstrate the potential capabilities of the presented methodology. The research demonstrates an innovative structural design procedure from a computational perspective and opens new insights into the potential design requirements and characteristics of morphing structures.

Issue a Boil-Water Advisory or Wait for Definitive Information? A Decision Analysis

PubMed Central

Wagner, Michael M.; Wallstrom, Garrick L.; Onisko, Agnieszka

2005-01-01

Objective Study the decision to issue a boil-water advisory in response to a spike in sales of diarrhea remedies or wait 72 hours for the results of definitive testing of water and people. Methods Decision analysis. Results In the base-case analysis, the optimal decision is test-and-wait. If the cost of issuing a boil-water advisory is less than 13.92 cents per person per day, the optimal decision is to issue the boil-water advisory immediately. Conclusions Decisions based on surveillance data that are suggestive but not conclusive about the existence of a disease outbreak can be modeled. PMID:16779145

Issues and Strategies in Solving Multidisciplinary Optimization Problems

NASA Technical Reports Server (NTRS)

Patnaik, Surya

2013-01-01

Optimization research at NASA Glenn Research Center has addressed the design of structures, aircraft and airbreathing propulsion engines. The accumulated multidisciplinary design activity is collected under a testbed entitled COMETBOARDS. Several issues were encountered during the solution of the problems. Four issues and the strategies adapted for their resolution are discussed. This is followed by a discussion on analytical methods that is limited to structural design application. An optimization process can lead to an inefficient local solution. This deficiency was encountered during design of an engine component. The limitation was overcome through an augmentation of animation into optimization. Optimum solutions obtained were infeasible for aircraft and airbreathing propulsion engine problems. Alleviation of this deficiency required a cascading of multiple algorithms. Profile optimization of a beam produced an irregular shape. Engineering intuition restored the regular shape for the beam. The solution obtained for a cylindrical shell by a subproblem strategy converged to a design that can be difficult to manufacture. Resolution of this issue remains a challenge. The issues and resolutions are illustrated through a set of problems: Design of an engine component, Synthesis of a subsonic aircraft, Operation optimization of a supersonic engine, Design of a wave-rotor-topping device, Profile optimization of a cantilever beam, and Design of a cylindrical shell. This chapter provides a cursory account of the issues. Cited references provide detailed discussion on the topics. Design of a structure can also be generated by traditional method and the stochastic design concept. Merits and limitations of the three methods (traditional method, optimization method and stochastic concept) are illustrated. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the merit function with constraints imposed on failure modes and an optimization algorithm is used to generate the solution. Stochastic design concept accounts for uncertainties in loads, material properties, and other parameters and solution is obtained by solving a design optimization problem for a specified reliability. Acceptable solutions can be produced by all the three methods. The variation in the weight calculated by the methods was found to be modest. Some variation was noticed in designs calculated by the methods. The variation may be attributed to structural indeterminacy. It is prudent to develop design by all three methods prior to its fabrication. The traditional design method can be improved when the simplified sensitivities of the behavior constraint is used. Such sensitivity can reduce design calculations and may have a potential to unify the traditional and optimization methods. Weight versus reliability traced out an inverted-S-shaped graph. The center of the graph corresponded to mean valued design. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for a most failure-prone design. Probabilistic modeling of load and material properties remained a challenge.

Deficit of state-dependent risk attitude modulation in gambling disorder

PubMed Central

Fujimoto, A; Tsurumi, K; Kawada, R; Murao, T; Takeuchi, H; Murai, T; Takahashi, H

2017-01-01

Gambling disorder (GD) is often considered as a problem of trait-like risk preference. However, the symptoms of GD cannot be fully understood by this trait view. In the present study, we hypothesized that GD patients also had problem with a flexible control of risk attitude (state-dependent strategy optimization), and aimed to investigate the mechanisms underlying abnormal risk-taking of GD. To address this issue, we tested GD patients without comorbidity (GD group: n=21) and age-matched healthy control participants (HC group: n=29) in a multi-step gambling task, in which participants needed to clear ‘block quota' (required units to clear a block, 1000–7000 units) in 20 choices, and conducted a task-functional magnetic resonance imaging (fMRI) experiment. Behavioral analysis indeed revealed a less flexible risk-attitude change in the GD group; the GD group failed to avoid risky choice in a specific quota range (low-quota condition), in which risky strategy was not optimal to solve the quota. Accordingly, fMRI analysis highlighted diminished functioning of the dorsolateral prefrontal cortex (dlPFC), which has been heavily implicated in cognitive flexibility. To our knowledge, the present study provided the first empirical evidence of a deficit of state-dependent strategy optimization in GD. Focusing on flexible control of risk attitude under quota may contribute to a better understanding of the psychopathology of GDs. PMID:28375207

Multi-time Scale Coordination of Distributed Energy Resources in Isolated Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayhorn, Ebony; Xie, Le; Butler-Purry, Karen

2016-03-31

In isolated power systems, including microgrids, distributed assets, such as renewable energy resources (e.g. wind, solar) and energy storage, can be actively coordinated to reduce dependency on fossil fuel generation. The key challenge of such coordination arises from significant uncertainty and variability occurring at small time scales associated with increased penetration of renewables. Specifically, the problem is with ensuring economic and efficient utilization of DERs, while also meeting operational objectives such as adequate frequency performance. One possible solution is to reduce the time step at which tertiary controls are implemented and to ensure feedback and look-ahead capability are incorporated tomore » handle variability and uncertainty. However, reducing the time step of tertiary controls necessitates investigating time-scale coupling with primary controls so as not to exacerbate system stability issues. In this paper, an optimal coordination (OC) strategy, which considers multiple time-scales, is proposed for isolated microgrid systems with a mix of DERs. This coordination strategy is based on an online moving horizon optimization approach. The effectiveness of the strategy was evaluated in terms of economics, technical performance, and computation time by varying key parameters that significantly impact performance. The illustrative example with realistic scenarios on a simulated isolated microgrid test system suggests that the proposed approach is generalizable towards designing multi-time scale optimal coordination strategies for isolated power systems.« less

Deficit of state-dependent risk attitude modulation in gambling disorder.

PubMed

Fujimoto, A; Tsurumi, K; Kawada, R; Murao, T; Takeuchi, H; Murai, T; Takahashi, H

2017-04-04

Gambling disorder (GD) is often considered as a problem of trait-like risk preference. However, the symptoms of GD cannot be fully understood by this trait view. In the present study, we hypothesized that GD patients also had problem with a flexible control of risk attitude (state-dependent strategy optimization), and aimed to investigate the mechanisms underlying abnormal risk-taking of GD. To address this issue, we tested GD patients without comorbidity (GD group: n=21) and age-matched healthy control participants (HC group: n=29) in a multi-step gambling task, in which participants needed to clear 'block quota' (required units to clear a block, 1000-7000 units) in 20 choices, and conducted a task-functional magnetic resonance imaging (fMRI) experiment. Behavioral analysis indeed revealed a less flexible risk-attitude change in the GD group; the GD group failed to avoid risky choice in a specific quota range (low-quota condition), in which risky strategy was not optimal to solve the quota. Accordingly, fMRI analysis highlighted diminished functioning of the dorsolateral prefrontal cortex (dlPFC), which has been heavily implicated in cognitive flexibility. To our knowledge, the present study provided the first empirical evidence of a deficit of state-dependent strategy optimization in GD. Focusing on flexible control of risk attitude under quota may contribute to a better understanding of the psychopathology of GDs.

Resources Management Strategy For Mud Crabs (Scylla spp.) In Pemalang Regency

NASA Astrophysics Data System (ADS)

Purnama Fitri, Aristi Dian; Boesono, Herry; Sabdono, Agus; Adlina, Nadia

2017-02-01

The aim of this research is to develop resources management strategies of mud crab (Scylla spp.) in Pemalang Regency. The method used is descriptive survey in a case study. This research used primary data and secondary data. Primary data were collected through field observations and in-depth interviews with key stakeholders. Secondary data were collected from related publications and documents issued by the competent institutions. SWOT Analysis was used to inventory the strengths, weaknesses, opportunities and threats. TOWS matrix was used to develop an alternative of resources management strategies. SWOT analysis was obtained by 6 alternative strategies that can be applied for optimization of fisheries development in Pemalang Regency. The strategies is the control of mud crab fishing gear, restricted size allowable in mud crab, control of mud crab fishing season, catch monitoring of mud crab, needs a management institutions which ensure the implementation of the regulation, and implementation for mud crab aquaculture. Each alternative strategy can be synergized to optimize the resources development in Pemalang Regency.

Control and optimization in the modeling of fibrosis. Comment on "Towards a unified approach in the modeling of fibrosis: A review with research perspectives" by Martine Ben Amar and Carlo Bianca

NASA Astrophysics Data System (ADS)

Sivasundaram, Seenith

2016-07-01

The review paper [1] is devoted to the survey of different structures that have been developed for the modeling and analysis of various types of fibrosis. Biomathematics, bioinformatics, biomechanics and biophysics modeling have been treated by means of a brief description of the different models developed. The review is impressive and clearly written, addressed to a reader interested not only in the theoretical modeling but also in the biological description. The models have been described without recurring to technical statements or mathematical equations thus allowing the non-specialist reader to understand what framework is more suitable at a certain observation scale. The review [1] concludes with the possibility to develop a multiscale approach considering also the definition of a therapeutical strategy for pathological fibrosis. In particular the control and optimization of therapeutics action is an important issue and this article aims at commenting on this topic.

Why don't Practitioners use Reservoir Optimization Methods? Results from a Survey of UK Water Managers

NASA Astrophysics Data System (ADS)

Dobson, B.; Pianosi, F.; Wagener, T.

2016-12-01

Extensive scientific literature exists on the study of how operation decisions in water resource systems can be made more effectively through the use of optimization methods. However, to the best of the authors' knowledge, there is little in the literature on the implementation of these optimization methods by practitioners. We have performed a survey among UK reservoir operators to assess the current state of method implementation in practice. We also ask questions to assess the potential for implementation of operation optimization. This will help academics to target industry in their current research, identify any misconceptions in industry about the area and open new branches of research for which there is an unsatisfied demand. The UK is a good case study because the regulatory framework is changing to impose "no build" solutions for supply issues, as well as planning across entire water resource systems rather than individual components. Additionally there is a high appetite for efficiency due to the water industry's privatization and most operators are part of companies that control multiple water resources, increasing the potential for cooperation and coordination.

Protein nutrition and exercise survival kit for critically ill.

PubMed

Weijs, Peter J M

2017-08-01

Protein delivery as well as exercise of critically ill in clinical practice is still a highly debated issue. Here we discuss only the most recent updates in the literature concerning protein nutrition and exercise of the critically ill. By lack of randomized controlled trial (RCTs) in protein nutrition we discuss four post-hoc analyses of nutrition studies and one experimental study in mice. Studies mainly confirm some insights that protein and energy effects are separate and that the trajectory of the patient in the ICU might change these effects. Exercise has been studied much more extensively with RCTs in the last year, although also here the differences between patient groups and timing of intervention might play their roles. Overall the effects of protein nutrition and exercise appear to be beneficial. However, studies into the differential effects of protein nutrition and/or exercise, and optimization of their combined use, have not been performed yet and are on the research agenda. Optimal protein nutrition, optimal exercise intervention as well as the optimal combination of nutrition, and exercise may help to improve long-term physical performance outcome in the critically ill patients.

Optimization of steam generators of NPP with WWER in operation with variable load

NASA Astrophysics Data System (ADS)

Parchevskii, V. M.; Shchederkina, T. E.; Gur'yanova, V. V.

2017-11-01

The report addresses the issue of the optimal water level in the horizontal steam generators of NPP with WWER. On the one hand, the level needs to be kept at the lower limit of the allowable range, as gravity separation, steam will have the least humidity and the turbine will operate with higher efficiency. On the other hand, the higher the level, the greater the supply of water in the steam generator, and therefore the higher the security level of the unit, because when accidents involving loss of cooling of the reactor core, the water in the steam generators, can be used for cooling. To quantitatively compare the damage from higher level to the benefit of improving the safety was assessed of the cost of one cubic meter of water in the steam generators, the formulated objective function of optimal levels control. This was used two-dimensional separation characteristics of steam generators. It is demonstrated that the security significantly shifts the optimal values of the levels toward the higher values, and this bias is greater the lower the load unit.

Analysis and control of high-speed wheeled vehicles

NASA Astrophysics Data System (ADS)

Velenis, Efstathios

In this work we reproduce driving techniques to mimic expert race drivers and obtain the open-loop control signals that may be used by auto-pilot agents driving autonomous ground wheeled vehicles. Race drivers operate their vehicles at the limits of the acceleration envelope. An accurate characterization of the acceleration capacity of the vehicle is required. Understanding and reproduction of such complex maneuvers also require a physics-based mathematical description of the vehicle dynamics. While most of the modeling issues of ground-vehicles/automobiles are already well established in the literature, lack of understanding of the physics associated with friction generation results in ad-hoc approaches to tire friction modeling. In this work we revisit this aspect of the overall vehicle modeling and develop a tire friction model that provides physical interpretation of the tire forces. The new model is free of those singularities at low vehicle speed and wheel angular rate that are inherent in the widely used empirical static models. In addition, the dynamic nature of the tire model proposed herein allows the study of dynamic effects such as transients and hysteresis. The trajectory-planning problem for an autonomous ground wheeled vehicle is formulated in an optimal control framework aiming to minimize the time of travel and maximize the use of the available acceleration capacity. The first approach to solve the optimal control problem is using numerical techniques. Numerical optimization allows incorporation of a vehicle model of high fidelity and generates realistic solutions. Such an optimization scheme provides an ideal platform to study the limit operation of the vehicle, which would not be possible via straightforward simulation. In this work we emphasize the importance of online applicability of the proposed methodologies. This underlines the need for optimal solutions that require little computational cost and are able to incorporate real, unpredictable environments. A semi-analytic methodology is developed to generate the optimal velocity profile for minimum time travel along a prescribed path. The semi-analytic nature ensures minimal computational cost while a receding horizon implementation allows application of the methodology in uncertain environments. Extensions to increase fidelity of the vehicle model are finally provided.

AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, J.R.; Netrologic, Inc., San Diego, CA)

1988-01-01

Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.

New control concepts for uncertain water resources systems: 1. Theory

NASA Astrophysics Data System (ADS)

Georgakakos, Aris P.; Yao, Huaming

1993-06-01

A major complicating factor in water resources systems management is handling unknown inputs. Stochastic optimization provides a sound mathematical framework but requires that enough data exist to develop statistical input representations. In cases where data records are insufficient (e.g., extreme events) or atypical of future input realizations, stochastic methods are inadequate. This article presents a control approach where input variables are only expected to belong in certain sets. The objective is to determine sets of admissible control actions guaranteeing that the system will remain within desirable bounds. The solution is based on dynamic programming and derived for the case where all sets are convex polyhedra. A companion paper (Yao and Georgakakos, this issue) addresses specific applications and problems in relation to reservoir system management.

Optimizing low impact development (LID) for stormwater runoff treatment in urban area, Korea: Experimental and modeling approach.

PubMed

Baek, Sang-Soo; Choi, Dong-Ho; Jung, Jae-Woon; Lee, Hyung-Jin; Lee, Hyuk; Yoon, Kwang-Sik; Cho, Kyung Hwa

2015-12-01

Currently, continued urbanization and development result in an increase of impervious areas and surface runoff including pollutants. Also one of the greatest issues in pollutant emissions is the first flush effect (FFE), which implies a greater discharge rate of pollutant mass in the early part in the storm. Low impact development (LID) practices have been mentioned as a promising strategy to control urban stormwater runoff and pollution in the urban ecosystem. However, this requires many experimental and modeling efforts to test LID characteristics and propose an adequate guideline for optimizing LID management. In this study, we propose a novel methodology to optimize the sizes of different types of LID by conducting intensive stormwater monitoring and numerical modeling in a commercial site in Korea. The methodology proposed optimizes LID size in an attempt to moderate FFE on a receiving waterbody. Thereby, the main objective of the optimization is to minimize mass first flush (MFF), which is an indicator for quantifying FFE. The optimal sizes of 6 different LIDs ranged from 1.2 mm to 3.0 mm in terms of runoff depths, which significantly moderate the FFE. We hope that the new proposed methodology can be instructive for establishing LID strategies to mitigate FFE. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hearing AIDS and music.

PubMed

Chasin, Marshall; Russo, Frank A

2004-01-01

Historically, the primary concern for hearing aid design and fitting is optimization for speech inputs. However, increasingly other types of inputs are being investigated and this is certainly the case for music. Whether the hearing aid wearer is a musician or merely someone who likes to listen to music, the electronic and electro-acoustic parameters described can be optimized for music as well as for speech. That is, a hearing aid optimally set for music can be optimally set for speech, even though the converse is not necessarily true. Similarities and differences between speech and music as inputs to a hearing aid are described. Many of these lead to the specification of a set of optimal electro-acoustic characteristics. Parameters such as the peak input-limiting level, compression issues-both compression ratio and knee-points-and number of channels all can deleteriously affect music perception through hearing aids. In other cases, it is not clear how to set other parameters such as noise reduction and feedback control mechanisms. Regardless of the existence of a "music program,'' unless the various electro-acoustic parameters are available in a hearing aid, music fidelity will almost always be less than optimal. There are many unanswered questions and hypotheses in this area. Future research by engineers, researchers, clinicians, and musicians will aid in the clarification of these questions and their ultimate solutions.

On-sky validation of an optimal LQG control with vibration mitigation: from the CANARY Multi-Object Adaptive Optics demonstrator to the Gemini Multi-Conjugated Adaptive Optics facility.

NASA Astrophysics Data System (ADS)

Sivo, Gaetano; Kulcsár, Caroline; Conan, Jean-Marc; Raynaud, Henri-François; Gendron, Éric; Basden, Alastair; Gratadour, Damien; Morris, Tim; Petit, Cyril; Meimon, Serge; Rousset, Gérard; Garrel, Vincent; Neichel, Benoit; van Dam, Marcos; Marin, Eduardo; Carrasco, Rodrigo; Schirmer, Mischa; Rambold, William; Moreno, Cristian; Montes, Vanessa; Hardie, Kayla; Trujillo, Chad

2015-01-01

Adaptive optics provides real time correction of wavefront perturbations on ground-based telescopes and allow to reach the diffraction limit performances. Optimizing control and performance is a key issue for ever more demanding instruments on ever larger telescopes affected not only by atmospheric turbulence, but also by vibrations, windshake and tracking errors. Linear Quadratic Gaussian control achieves optimal correction when provided with a temporal model of the disturbance. We present in this paper the first on-sky results of a Kalman filter based LQG control with vibration mitigation on the CANARY instrument at the Nasmyth platform of the 4.2-m William Herschel Telescope (La Palma, Spain). The results demonstrate a clear improvement of performance for full LQG compared with standard integrator control, and assess the additional improvement brought by vibration filtering with a tip-tilt model identified from on-sky data (by 10 points of Strehl ratio), thus validating the strategy retained on the instrument SPHERE (eXtreme-AO system for extra-solar planets detection and characterization) at the VLT. The MOAO on-sky pathfinder CANARY features two AO configurations that have both been tested: single- conjugated AO and multi-object AO with NGS and NGS+ Rayleigh LGS, together with vibration mitigation on tip and tilt modes. We finally present the ongoing development done to commission such a control law on a regular Sodium laser Multi-Conjuagated Adaptive Optics (MCAO) system GeMS at the 8-m Gemini South Telescope. This implementation does not require new hardware and is already available in the real-time computer.

A Traction Control Strategy with an Efficiency Model in a Distributed Driving Electric Vehicle

PubMed Central

Lin, Cheng

2014-01-01

Both active safety and fuel economy are important issues for vehicles. This paper focuses on a traction control strategy with an efficiency model in a distributed driving electric vehicle. In emergency situation, a sliding mode control algorithm was employed to achieve antislip control through keeping the wheels' slip ratios below 20%. For general longitudinal driving cases, an efficiency model aiming at improving the fuel economy was built through an offline optimization stream within the two-dimensional design space composed of the acceleration pedal signal and the vehicle speed. The sliding mode control strategy for the joint roads and the efficiency model for the typical drive cycles were simulated. Simulation results show that the proposed driving control approach has the potential to apply to different road surfaces. It keeps the wheels' slip ratios within the stable zone and improves the fuel economy on the premise of tracking the driver's intention. PMID:25197697

A traction control strategy with an efficiency model in a distributed driving electric vehicle.

PubMed

Lin, Cheng; Cheng, Xingqun

2014-01-01

Both active safety and fuel economy are important issues for vehicles. This paper focuses on a traction control strategy with an efficiency model in a distributed driving electric vehicle. In emergency situation, a sliding mode control algorithm was employed to achieve antislip control through keeping the wheels' slip ratios below 20%. For general longitudinal driving cases, an efficiency model aiming at improving the fuel economy was built through an offline optimization stream within the two-dimensional design space composed of the acceleration pedal signal and the vehicle speed. The sliding mode control strategy for the joint roads and the efficiency model for the typical drive cycles were simulated. Simulation results show that the proposed driving control approach has the potential to apply to different road surfaces. It keeps the wheels' slip ratios within the stable zone and improves the fuel economy on the premise of tracking the driver's intention.

Plant maintenance and advanced reactors issue, 2004

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agnihotri, Newal

2004-09-15

The focus of the September-October issue is on plant maintenance and advanced reactors. Major articles/reports in this issue include: Optimism about the future of nuclear power, by Ruth G. Shaw, Duke Power Company; Licensed in three countries, by GE Energy; Enhancing public acceptance, by Westinghouse Electric Company; Standardized MOV program, by Ted Neckowicz, Exelon; Inservice testing, by Steven Unikewicz, U.S. Nuclear Regulatory Commission; Asian network for education, Fatimah Mohd Amin, Malaysian Institute for Nuclear Technology Research; and, Cooling water intake optimization, by Jeffrey M. Jones and Bert Mayer, P.E., Framatome ANP.

Simulation of a class of hazardous situations in the ICS «INM RAS - Baltic Sea»

NASA Astrophysics Data System (ADS)

Zakharova, Natalia; Agoshkov, Valery; Aseev, Nikita; Parmuzin, Eugene; Sheloput, Tateana; Shutyaev, Victor

2017-04-01

Development of Informational Computational Systems (ICS) for data assimilation procedures is one of multidisciplinary problems. To study and solve these problems one needs to apply modern results from different disciplines and recent developments in mathematical modeling, theory of adjoint equations and optimal control, inverse problems, numerical methods theory, numerical algebra, scientific computing and processing of satellite data. In this work the results on the ICS development for PC-ICS "INM RAS - Baltic Sea" are presented. We discuss practical problems studied by ICS. The System includes numerical model of the Baltic Sea thermodynamics, the new oil spill model describing the propagation of a slick at the Sea surface (Agoshkov, Aseev et al., 2014) and the optimal ship route calculating block (Agoshkov, Zayachkovsky et al., 2014). The ICS is based on the INMOM numerical model of the Baltic Sea thermodynamics (Zalesny et al., 2013). It is possible to calculate main hydrodynamic parameters (temperature, salinity, velocities, sea level) using user-friendly interface of the ICS. The System includes data assimilation procedures (Agoshkov, 2003, Parmuzin, Agoshkov, 2012) and one can use the block of variational assimilation of the sea surface temperature in order to obtain main hydrodynamic parameters. Main possibilities of the ICS and several numerical experiments are presented in the work. By the problem of risk control is meant a problem of determination of optimal resources quantity which are necessary for decreasing the risk to some acceptable value. Mass of oil slick is chosen as a function of control. For the realization of the random variable the quadratic "functional of cost" is introduced. It comprises cleaning costs and deviation of damage of oil pollution from its acceptable value. The problem of minimization of this functional is solved based on the methods of optimal control and the theory of adjoint equations. The solution of this problem is explicitly found. The study was supported by the Russian Foundation for Basic Research (project 16-31-00510) and by the Russian Science Foundation (project №14-11-00609). V. I. Agoshkov, Methods of Optimal Control and Adjoint Equations in Problems of Mathematical Physics. INM RAS, Moscow, 2003 (in Russian). V. B. Zalesny, A. V. Gusev, V. O. Ivchenko, R. Tamsalu, and R. Aps, Numerical model of the Baltic Sea circulation. Russ. J. Numer. Anal. Math. Modelling 28 (2013), No. 1, 85-100. V.I. Agoshkov, A.O. Zayachkovskiy, R. Aps, P. Kujala, and J. Rytkönen. Risk theory based solution to the problem of optimal vessel route // Russian Journal of Numerical Analysis and Mathematical Modelling. 2014. Volume 29, Issue 2, Pages 69-78. Agoshkov, V., Aseev, N., Aps, R., Kujala, P., Rytkönen, J., Zalesny, V. The problem of control of oil pollution risk in the Baltic Sea // Russian Journal of Numerical Analysis and Mathematical Modelling. 2014. Volume 29, Issue 2, Pages 93-105. E. I. Parmuzin and V. I. Agoshkov, Numerical solution of the variational assimilation problem for sea surface temperature in the model of the Black Sea dynamics. Russ. J. Numer. Anal. Math. Modelling 27 (2012), No. 1, 69-94. Olof Liungman and Johan Mattsson. Scientic Documentation of Seatrack Web; physical processes, algorithms and references, 2011.

Intervention in gene regulatory networks with maximal phenotype alteration.

PubMed

Yousefi, Mohammadmahdi R; Dougherty, Edward R

2013-07-15

A basic issue for translational genomics is to model gene interaction via gene regulatory networks (GRNs) and thereby provide an informatics environment to study the effects of intervention (say, via drugs) and to derive effective intervention strategies. Taking the view that the phenotype is characterized by the long-run behavior (steady-state distribution) of the network, we desire interventions to optimally move the probability mass from undesirable to desirable states Heretofore, two external control approaches have been taken to shift the steady-state mass of a GRN: (i) use a user-defined cost function for which desirable shift of the steady-state mass is a by-product and (ii) use heuristics to design a greedy algorithm. Neither approach provides an optimal control policy relative to long-run behavior. We use a linear programming approach to optimally shift the steady-state mass from undesirable to desirable states, i.e. optimization is directly based on the amount of shift and therefore must outperform previously proposed methods. Moreover, the same basic linear programming structure is used for both unconstrained and constrained optimization, where in the latter case, constraints on the optimization limit the amount of mass that may be shifted to 'ambiguous' states, these being states that are not directly undesirable relative to the pathology of interest but which bear some perceived risk. We apply the method to probabilistic Boolean networks, but the theory applies to any Markovian GRN. Supplementary materials, including the simulation results, MATLAB source code and description of suboptimal methods are available at http://gsp.tamu.edu/Publications/supplementary/yousefi13b. edward@ece.tamu.edu Supplementary data are available at Bioinformatics online.

How the Public Engages With Brain Optimization

PubMed Central

O’Connor, Cliodhna

2015-01-01

In the burgeoning debate about neuroscience’s role in contemporary society, the issue of brain optimization, or the application of neuroscientific knowledge and technologies to augment neurocognitive function, has taken center stage. Previous research has characterized media discourse on brain optimization as individualistic in ethos, pressuring individuals to expend calculated effort in cultivating culturally desirable forms of selves and bodies. However, little research has investigated whether the themes that characterize media dialogue are shared by lay populations. This article considers the relationship between the representations of brain optimization that surfaced in (i) a study of British press coverage between 2000 and 2012 and (ii) interviews with forty-eight London residents. Both data sets represented the brain as a resource that could be manipulated by the individual, with optimal brain function contingent on applying self-control in one’s lifestyle choices. However, these ideas emerged more sharply in the media than in the interviews: while most interviewees were aware of brain optimization practices, few were committed to carrying them out. The two data sets diverged in several ways: the media’s intense preoccupation with optimizing children’s brains was not apparent in lay dialogue, while interviewees elaborated beliefs about the underuse of brain tissue that showed no presence in the media. This article considers these continuities and discontinuities in light of their wider cultural significance and their implications for the media–mind relationship in public engagement with neuroscience. PMID:26336326

Optimization of ramp area aircraft push back time windows in the presence of uncertainty

NASA Astrophysics Data System (ADS)

Coupe, William Jeremy

It is well known that airport surface traffic congestion at major airports is responsible for increased taxi-out times, fuel burn and excess emissions and there is potential to mitigate these negative consequences through optimizing airport surface traffic operations. Due to a highly congested voice communication channel between pilots and air traffic controllers and a data communication channel that is used only for limited functions, one of the most viable near-term strategies for improvement of the surface traffic is issuing a push back advisory to each departing aircraft. This dissertation focuses on the optimization of a push back time window for each departing aircraft. The optimization takes into account both spatial and temporal uncertainties of ramp area aircraft trajectories. The uncertainties are described by a stochastic kinematic model of aircraft trajectories, which is used to infer distributions of combinations of push back times that lead to conflict among trajectories from different gates. The model is validated and the distributions are included in the push back time window optimization. Under the assumption of a fixed taxiway spot schedule, the computed push back time windows can be integrated with a higher level taxiway scheduler to optimize the flow of traffic from the gate to the departure runway queue. To enable real-time decision making the computational time of the push back time window optimization is critical and is analyzed throughout.

Cluster-based control of a separating flow over a smoothly contoured ramp

NASA Astrophysics Data System (ADS)

Kaiser, Eurika; Noack, Bernd R.; Spohn, Andreas; Cattafesta, Louis N.; Morzyński, Marek

2017-12-01

The ability to manipulate and control fluid flows is of great importance in many scientific and engineering applications. The proposed closed-loop control framework addresses a key issue of model-based control: The actuation effect often results from slow dynamics of strongly nonlinear interactions which the flow reveals at timescales much longer than the prediction horizon of any model. Hence, we employ a probabilistic approach based on a cluster-based discretization of the Liouville equation for the evolution of the probability distribution. The proposed methodology frames high-dimensional, nonlinear dynamics into low-dimensional, probabilistic, linear dynamics which considerably simplifies the optimal control problem while preserving nonlinear actuation mechanisms. The data-driven approach builds upon a state space discretization using a clustering algorithm which groups kinematically similar flow states into a low number of clusters. The temporal evolution of the probability distribution on this set of clusters is then described by a control-dependent Markov model. This Markov model can be used as predictor for the ergodic probability distribution for a particular control law. This probability distribution approximates the long-term behavior of the original system on which basis the optimal control law is determined. We examine how the approach can be used to improve the open-loop actuation in a separating flow dominated by Kelvin-Helmholtz shedding. For this purpose, the feature space, in which the model is learned, and the admissible control inputs are tailored to strongly oscillatory flows.

Hierarchical Control Using Networks Trained with Higher-Level Forward Models

PubMed Central

Wayne, Greg; Abbott, L.F.

2015-01-01

We propose and develop a hierarchical approach to network control of complex tasks. In this approach, a low-level controller directs the activity of a “plant,” the system that performs the task. However, the low-level controller may only be able to solve fairly simple problems involving the plant. To accomplish more complex tasks, we introduce a higher-level controller that controls the lower-level controller. We use this system to direct an articulated truck to a specified location through an environment filled with static or moving obstacles. The final system consists of networks that have memorized associations between the sensory data they receive and the commands they issue. These networks are trained on a set of optimal associations that are generated by minimizing cost functions. Cost function minimization requires predicting the consequences of sequences of commands, which is achieved by constructing forward models, including a model of the lower-level controller. The forward models and cost minimization are only used during training, allowing the trained networks to respond rapidly. In general, the hierarchical approach can be extended to larger numbers of levels, dividing complex tasks into more manageable sub-tasks. The optimization procedure and the construction of the forward models and controllers can be performed in similar ways at each level of the hierarchy, which allows the system to be modified to perform other tasks, or to be extended for more complex tasks without retraining lower-levels. PMID:25058706

Inventions on baker's yeast storage and activation at the bakery plant.

PubMed

Gélinas, Pierre

2010-01-01

Baker's yeast is the gas-forming ingredient in bakery products. Methods have been invented to properly handle baker's yeast and optimize its activity at the bakery plant. Over the years, incentives for inventions on yeast storage and activation have greatly changed depending on trends in the baking industry. For example, retailer's devices for cutting bulk pressed yeast and techniques for activating dry yeast have now lost their importance. Review of patents for invention indicates that activation of baker's yeast activity has been a very important issue for bakers, for example, with baking ingredients called yeast foods. In the recent years and especially for highly automated bakeries, interest has moved to equipments and processes for optimized storage of liquid cream yeast to thoroughly control dough fermentation and bread quality.

Adaptive quantization-parameter clip scheme for smooth quality in H.264/AVC.

PubMed

Hu, Sudeng; Wang, Hanli; Kwong, Sam

2012-04-01

In this paper, we investigate the issues over the smooth quality and the smooth bit rate during rate control (RC) in H.264/AVC. An adaptive quantization-parameter (Q(p)) clip scheme is proposed to optimize the quality smoothness while keeping the bit-rate fluctuation at an acceptable level. First, the frame complexity variation is studied by defining a complexity ratio between two nearby frames. Second, the range of the generated bits is analyzed to prevent the encoder buffer from overflow and underflow. Third, based on the safe range of the generated bits, an optimal Q(p) clip range is developed to reduce the quality fluctuation. Experimental results demonstrate that the proposed Q(p) clip scheme can achieve excellent performance in quality smoothness and buffer regulation.

A Technical Survey on Optimization of Processing Geo Distributed Data

NASA Astrophysics Data System (ADS)

Naga Malleswari, T. Y. J.; Ushasukhanya, S.; Nithyakalyani, A.; Girija, S.

2018-04-01

With growing cloud services and technology, there is growth in some geographically distributed data centers to store large amounts of data. Analysis of geo-distributed data is required in various services for data processing, storage of essential information, etc., processing this geo-distributed data and performing analytics on this data is a challenging task. The distributed data processing is accompanied by issues in storage, computation and communication. The key issues to be dealt with are time efficiency, cost minimization, utility maximization. This paper describes various optimization methods like end-to-end multiphase, G-MR, etc., using the techniques like Map-Reduce, CDS (Community Detection based Scheduling), ROUT, Workload-Aware Scheduling, SAGE, AMP (Ant Colony Optimization) to handle these issues. In this paper various optimization methods and techniques used are analyzed. It has been observed that end-to end multiphase achieves time efficiency; Cost minimization concentrates to achieve Quality of Service, Computation and reduction of Communication cost. SAGE achieves performance improvisation in processing geo-distributed data sets.

On the Use of CAD and Cartesian Methods for Aerodynamic Optimization

NASA Technical Reports Server (NTRS)

Nemec, M.; Aftosmis, M. J.; Pulliam, T. H.

2004-01-01

The objective for this paper is to present the development of an optimization capability for Curt3D, a Cartesian inviscid-flow analysis package. We present the construction of a new optimization framework and we focus on the following issues: 1) Component-based geometry parameterization approach using parametric-CAD models and CAPRI. A novel geometry server is introduced that addresses the issue of parallel efficiency while only sparingly consuming CAD resources; 2) The use of genetic and gradient-based algorithms for three-dimensional aerodynamic design problems. The influence of noise on the optimization methods is studied. Our goal is to create a responsive and automated framework that efficiently identifies design modifications that result in substantial performance improvements. In addition, we examine the architectural issues associated with the deployment of a CAD-based approach in a heterogeneous parallel computing environment that contains both CAD workstations and dedicated compute engines. We demonstrate the effectiveness of the framework for a design problem that features topology changes and complex geometry.

Performance assessment of deterministic and probabilistic weather predictions for the short-term optimization of a tropical hydropower reservoir

NASA Astrophysics Data System (ADS)

Mainardi Fan, Fernando; Schwanenberg, Dirk; Alvarado, Rodolfo; Assis dos Reis, Alberto; Naumann, Steffi; Collischonn, Walter

2016-04-01

Hydropower is the most important electricity source in Brazil. During recent years, it accounted for 60% to 70% of the total electric power supply. Marginal costs of hydropower are lower than for thermal power plants, therefore, there is a strong economic motivation to maximize its share. On the other hand, hydropower depends on the availability of water, which has a natural variability. Its extremes lead to the risks of power production deficits during droughts and safety issues in the reservoir and downstream river reaches during flood events. One building block of the proper management of hydropower assets is the short-term forecast of reservoir inflows as input for an online, event-based optimization of its release strategy. While deterministic forecasts and optimization schemes are the established techniques for the short-term reservoir management, the use of probabilistic ensemble forecasts and stochastic optimization techniques receives growing attention and a number of researches have shown its benefit. The present work shows one of the first hindcasting and closed-loop control experiments for a multi-purpose hydropower reservoir in a tropical region in Brazil. The case study is the hydropower project (HPP) Três Marias, located in southeast Brazil. The HPP reservoir is operated with two main objectives: (i) hydroelectricity generation and (ii) flood control at Pirapora City located 120 km downstream of the dam. In the experiments, precipitation forecasts based on observed data, deterministic and probabilistic forecasts with 50 ensemble members of the ECMWF are used as forcing of the MGB-IPH hydrological model to generate streamflow forecasts over a period of 2 years. The online optimization depends on a deterministic and multi-stage stochastic version of a model predictive control scheme. Results for the perfect forecasts show the potential benefit of the online optimization and indicate a desired forecast lead time of 30 days. In comparison, the use of actual forecasts with shorter lead times of up to 15 days shows the practical benefit of actual operational data. It appears that the use of stochastic optimization combined with ensemble forecasts leads to a significant higher level of flood protection without compromising the HPP's energy production.

Model Predictive Control application for real time operation of controlled structures for the Water Authority Noorderzijlvest, The Netherlands

NASA Astrophysics Data System (ADS)

van Heeringen, Klaas-Jan; Gooijer, Jan; Knot, Floris; Talsma, Jan

2015-04-01

In the Netherlands, flood protection has always been a key issue to protect settlements against storm surges and riverine floods. Whereas flood protection traditionally focused on structural measures, nowadays the availability of meteorological and hydrological forecasts enable the application of more advanced real-time control techniques for operating the existing hydraulic infrastructure in an anticipatory and more efficient way. Model Predictive Control (MPC) is a powerful technique to derive optimal control variables with the help of model based predictions evaluated against a control objective. In a project for the regional water authority Noorderzijlvest in the north of the Netherlands, it has been shown that MPC can increase the safety level of the system during flood events by an anticipatory pre-release of water. Furthermore, energy costs of pumps can be reduced by making tactical use of the water storage and shifting pump activities during normal operating conditions to off-peak hours. In this way cheap energy is used in combination of gravity flow through gates during low tide periods. MPC has now been implemented for daily operational use of the whole water system of the water authority Noorderzijlvest. The system developed to a real time decision support system which not only supports the daily operation but is able to directly implement the optimal control settings at the structures. We explain how we set-up and calibrated a prediction model (RTC-Tools) that is accurate and fast enough for optimization purposes, and how we integrated it in the operational flood early warning system (Delft-FEWS). Beside the prediction model, the weights and the factors of the objective function are an important element of MPC, since they shape the control objective. We developed special features in Delft-FEWS to allow the operators to adjust the objective function in order to meet changing requirements and to evaluate different control strategies.

Partial Storage Optimization and Load Control Strategy of Cloud Data Centers

PubMed Central

2015-01-01

We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, which provide a good optimization to the cloud storage usage. Only partial replication is used in this algorithm to ensure the reliability and availability of the data. Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud. This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space needed will help in reducing the cost of providing such space. Moreover, performance is also increased since multiple cloud servers will collaborate to provide the data to the cloud clients in a faster manner. PMID:25973444

Partial storage optimization and load control strategy of cloud data centers.

PubMed

Al Nuaimi, Klaithem; Mohamed, Nader; Al Nuaimi, Mariam; Al-Jaroodi, Jameela

2015-01-01

We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, which provide a good optimization to the cloud storage usage. Only partial replication is used in this algorithm to ensure the reliability and availability of the data. Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud. This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space needed will help in reducing the cost of providing such space. Moreover, performance is also increased since multiple cloud servers will collaborate to provide the data to the cloud clients in a faster manner.

Active control of combustion instabilities

NASA Astrophysics Data System (ADS)

Al-Masoud, Nidal A.

A theoretical analysis of active control of combustion thermo-acoustic instabilities is developed in this dissertation. The theoretical combustion model is based on the dynamics of a two-phase flow in a liquid-fueled propulsion system. The formulation is based on a generalized wave equation with pressure as the dependent variable, and accommodates all influences of combustion, mean flow, unsteady motions and control inputs. The governing partial differential equations are converted to an equivalent set of ordinary differential equations using Galerkin's method by expressing the unsteady pressure and velocity fields as functions of normal mode shapes of the chamber. This procedure yields a representation of the unsteady flow field as a system of coupled nonlinear oscillators that is used as a basis for controllers design. Major research attention is focused on the control of longitudinal oscillations with both linear and nonlinear processes being considered. Starting with a linear model using point actuators, the optimal locations of actuators and sensors are developed. The approach relies on the quantitative measures of the degree of controllability and component cost. These criterion are arrived at by considering the energies of the system's inputs and outputs. The optimality criteria for sensor and actuator locations provide a balance between the importance of the lower order (controlled) and the higher (residual) order modes. To address the issue of uncertainties in system's parameter, the minimax principles based controller is used. The minimax corresponds to finding the best controller for the worst parameter deviation. In other words, choosing controller parameters to minimize, and parameter deviation to maximize some quadratic performance metric. Using the minimax-based controller, a remarkable improvement in the control system's ability to handle parameter uncertainties is achieved when compared to the robustness of the regular control schemes such as LQR and LQG. Since the observed instabilities are harmonic, the concept of "harmonic input" is successfully implemented using a parametric controller to eliminate the thermo-acoustic instability. This control scheme relies on the determination of a phase-shift to maximize the energy dissipation and a controller gain to assure stability and minimize a pre-specified performance index. The closed loop control law design is based on finding an optimal phase angle such that the heat release produced by secondary oscillatory fuel injection is out of phase with the mode's pressure oscillations, thus maximizing energy dissipation, and on finding the limits on the controller gain that ensures system stability. The optimal gains are determined using ITA, ISE, ITAE performance indices. Simulations show successful implementation of the proposed technique.

Optimal Output Trajectory Redesign for Invertible Systems

NASA Technical Reports Server (NTRS)

Devasia, S.

1996-01-01

Given a desired output trajectory, inversion-based techniques find input-state trajectories required to exactly track the output. These inversion-based techniques have been successfully applied to the endpoint tracking control of multijoint flexible manipulators and to aircraft control. The specified output trajectory uniquely determines the required input and state trajectories that are found through inversion. These input-state trajectories exactly track the desired output; however, they might not meet acceptable performance requirements. For example, during slewing maneuvers of flexible structures, the structural deformations, which depend on the required state trajectories, may be unacceptably large. Further, the required inputs might cause actuator saturation during an exact tracking maneuver, for example, in the flight control of conventional takeoff and landing aircraft. In such situations, a compromise is desired between the tracking requirement and other goals such as reduction of internal vibrations and prevention of actuator saturation; the desired output trajectory needs to redesigned. Here, we pose the trajectory redesign problem as an optimization of a general quadratic cost function and solve it in the context of linear systems. The solution is obtained as an off-line prefilter of the desired output trajectory. An advantage of our technique is that the prefilter is independent of the particular trajectory. The prefilter can therefore be precomputed, which is a major advantage over other optimization approaches. Previous works have addressed the issue of preshaping inputs to minimize residual and in-maneuver vibrations for flexible structures; Since the command preshaping is computed off-line. Further minimization of optimal quadratic cost functions has also been previously use to preshape command inputs for disturbance rejection. All of these approaches are applicable when the inputs to the system are known a priori. Typically, outputs (not inputs) are specified in tracking problems, and hence the input trajectories have to be computed. The inputs to the system are however, difficult to determine for non-minimum phase systems like flexible structures. One approach to solve this problem is to (1) choose a tracking controller (the desired output trajectory is now an input to the closed-loop system and (2) redesign this input to the closed-loop system. Thus we effectively perform output redesign. These redesigns are however, dependent on the choice of the tracking controllers. Thus the controller optimization and trajectory redesign problems become coupled; this coupled optimization is still an open problem. In contrast, we decouple the trajectory redesign problem from the choice of feedback-based tracking controller. It is noted that our approach remains valid when a particular tracking controller is chosen. In addition, the formulation of our problem not only allows for the minimization of residual vibration as in available techniques but also allows for the optimal reduction fo vibrations during the maneuver, e.g., the altitude control of flexible spacecraft. We begin by formulating the optimal output trajectory redesign problem and then solve it in the context of general linear systems. This theory is then applied to an example flexible structure, and simulation results are provided.

Optimal Reward Functions in Distributed Reinforcement Learning

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan

2000-01-01

We consider the design of multi-agent systems so as to optimize an overall world utility function when (1) those systems lack centralized communication and control, and (2) each agents runs a distinct Reinforcement Learning (RL) algorithm. A crucial issue in such design problems is to initialize/update each agent's private utility function, so as to induce best possible world utility. Traditional 'team game' solutions to this problem sidestep this issue and simply assign to each agent the world utility as its private utility function. In previous work we used the 'Collective Intelligence' framework to derive a better choice of private utility functions, one that results in world utility performance up to orders of magnitude superior to that ensuing from use of the team game utility. In this paper we extend these results. We derive the general class of private utility functions that both are easy for the individual agents to learn and that, if learned well, result in high world utility. We demonstrate experimentally that using these new utility functions can result in significantly improved performance over that of our previously proposed utility, over and above that previous utility's superiority to the conventional team game utility.

Hybrid intelligent control of substrate feeding for industrial fed-batch chlortetracycline fermentation process.

PubMed

Jin, Huaiping; Chen, Xiangguang; Yang, Jianwen; Wu, Lei; Wang, Li

2014-11-01

The lack of accurate process models and reliable online sensors for substrate measurements poses significant challenges for controlling substrate feeding accurately, automatically and optimally in fed-batch fermentation industries. It is still a common practice to regulate the feeding rate based upon manual operations. To address this issue, a hybrid intelligent control method is proposed to enable automatic substrate feeding. The resulting control system consists of three modules: a presetting module for providing initial set-points; a predictive module for estimating substrate concentration online based on a new time interval-varying soft sensing algorithm; and a feedback compensator using expert rules. The effectiveness of the proposed approach is demonstrated through its successful applications to the industrial fed-batch chlortetracycline fermentation process. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Issues in Teaching Mathematics

ERIC Educational Resources Information Center

Ediger, Marlow

2013-01-01

In this article, the author states that there are selected issues in mathematics instruction that educators should be well aware of when planning lessons and units of study. These issues provide a basis for thought and discussion when assisting pupils to attain more optimally. Purposeful studying of issues guides mathematics teachers in…

The technological raw material heating furnaces operation efficiency improving issue

NASA Astrophysics Data System (ADS)

Paramonov, A. M.

2017-08-01

The issue of fuel oil applying efficiency improving in the technological raw material heating furnaces by means of its combustion intensification is considered in the paper. The technical and economic optimization problem of the fuel oil heating before combustion is solved. The fuel oil heating optimal temperature defining method and algorithm analytically considering the correlation of thermal, operating parameters and discounted costs for the heating furnace were developed. The obtained optimization functionality provides the heating furnace appropriate thermal indices achievement at minimum discounted costs. The carried out research results prove the expediency of the proposed solutions using.

Dynamic mobility applications policy analysis : policy and institutional issues for intelligent network flow optimization (INFLO).

DOT National Transportation Integrated Search

2014-12-01

The report documents policy considerations for the Intelligent Network Flow Optimization (INFLO) connected vehicle applications bundle. INFLO aims to optimize network flow on freeways and arterials by informing motorists of existing and impendi...

Data mining for water resource management part 2 - methods and approaches to solving contemporary problems

USGS Publications Warehouse

Roehl, Edwin A.; Conrads, Paul

2010-01-01

This is the second of two papers that describe how data mining can aid natural-resource managers with the difficult problem of controlling the interactions between hydrologic and man-made systems. Data mining is a new science that assists scientists in converting large databases into knowledge, and is uniquely able to leverage the large amounts of real-time, multivariate data now being collected for hydrologic systems. Part 1 gives a high-level overview of data mining, and describes several applications that have addressed major water resource issues in South Carolina. This Part 2 paper describes how various data mining methods are integrated to produce predictive models for controlling surface- and groundwater hydraulics and quality. The methods include: - signal processing to remove noise and decompose complex signals into simpler components; - time series clustering that optimally groups hundreds of signals into "classes" that behave similarly for data reduction and (or) divide-and-conquer problem solving; - classification which optimally matches new data to behavioral classes; - artificial neural networks which optimally fit multivariate data to create predictive models; - model response surface visualization that greatly aids in understanding data and physical processes; and, - decision support systems that integrate data, models, and graphics into a single package that is easy to use.

Randomized controlled trials in dentistry: common pitfalls and how to avoid them.

PubMed

Fleming, Padhraig S; Lynch, Christopher D; Pandis, Nikolaos

2014-08-01

Clinical trials are used to appraise the effectiveness of clinical interventions throughout medicine and dentistry. Randomized controlled trials (RCTs) are established as the optimal primary design and are published with increasing frequency within the biomedical sciences, including dentistry. This review outlines common pitfalls associated with the conduct of randomized controlled trials in dentistry. Common failings in RCT design leading to various types of bias including selection, performance, detection and attrition bias are discussed in this review. Moreover, methods of minimizing and eliminating bias are presented to ensure that maximal benefit is derived from RCTs within dentistry. Well-designed RCTs have both upstream and downstream uses acting as a template for development and populating systematic reviews to permit more precise estimates of treatment efficacy and effectiveness. However, there is increasing awareness of waste in clinical research, whereby resource-intensive studies fail to provide a commensurate level of scientific evidence. Waste may stem either from inappropriate design or from inadequate reporting of RCTs; the importance of robust conduct of RCTs within dentistry is clear. Optimal reporting of randomized controlled trials within dentistry is necessary to ensure that trials are reliable and valid. Common shortcomings leading to important forms or bias are discussed and approaches to minimizing these issues are outlined. Copyright © 2014 Elsevier Ltd. All rights reserved.

Learning Grasp Strategies Composed of Contact Relative Motions

NASA Technical Reports Server (NTRS)

Platt, Robert, Jr.

2007-01-01

Of central importance to grasp synthesis algorithms are the assumptions made about the object to be grasped and the sensory information that is available. Many approaches avoid the issue of sensing entirely by assuming that complete information is available. In contrast, this paper proposes an approach to grasp synthesis expressed in terms of units of control that simultaneously change the contact configuration and sense information about the object and the relative manipulator-object pose. These units of control, known as contact relative motions (CRMs), allow the grasp synthesis problem to be recast as an optimal control problem where the goal is to find a strategy for executing CRMs that leads to a grasp in the shortest number of steps. An experiment is described that uses Robonaut, the NASA-JSC space humanoid, to show that CRMs are a viable means of synthesizing grasps. However, because of the limited amount of information that a single CRM can sense, the optimal control problem may be partially observable. This paper proposes expressing the problem as a k-order Markov Decision Process (MDP) and solving it using Reinforcement Learning. This approach is tested in a simulation of a two-contact manipulator that learns to grasp an object. Grasp strategies learned in simulation are tested on the physical Robonaut platform and found to lead to grasp configurations consistently.

Reconciling divergent results of the latest parenteral nutrition studies in the ICU.

PubMed

Singer, Pierre; Pichard, Claude

2013-03-01

Recent studies on the optimal modalities to feed patients during the ICU stay show divergent results. The level and the timing of energy provision is a critical issue, associated with the clinical outcome. These results questioned the clinical relevance of the recent guidelines issued by American, Canadian and European academic societies. Four recent prospective randomized studies enrolled critically ill patients who received various nutritional regimens and tested the effect of nutritional support on outcome. The Tight Calorie balance Control Study (TICACOS) targeted on calorie administration according to measured energy expenditure and found increased ICU morbidity but improved hospital mortality. The large EpaNIC study compared 'early' with 'late' (parenteral nutrition) nutrition, mostly in patients after cardiac surgery, and found an increased morbidity associated with early parenteral nutrition. The supplemental parenteral nutrition (SPN) study randomized the patients after 3 days and targeted the calories administered by parenteral nutrition as a complement to unsuccessful enteral nutrition using indirect calorimetry. The SPN resulted in less nosocomial infections and shorter duration of mechanical ventilation. Finally, a recent Australian study enrolled patients unable to be early fed enterally to receive, or not, parenteral nutrition targeted at 1500 kcal. No complications were noted in the parenteral nutrition group. Lessons from all these studies are summarized and should help in designing better studies and guidelines. The critical analysis of recent prospective studies comparing various levels of calorie administration, enteral versus parenteral nutrition and enteral versus SPN confirms the recommendations to avoid underfeeding and overfeeding. Parenteral nutrition, required if enteral feeding is failing, and if adjusted up to a measured optimal level, may improve outcome. More studies on the optimal level of energy and protein administration to optimize the clinical outcome are required to fine tune current guidelines.

Improved ATLAS HammerCloud Monitoring for Local Site Administration

NASA Astrophysics Data System (ADS)

Böhler, M.; Elmsheuser, J.; Hönig, F.; Legger, F.; Mancinelli, V.; Sciacca, G.

2015-12-01

Every day hundreds of tests are run on the Worldwide LHC Computing Grid for the ATLAS, and CMS experiments in order to evaluate the performance and reliability of the different computing sites. All this activity is steered, controlled, and monitored by the HammerCloud testing infrastructure. Sites with failing functionality tests are auto-excluded from the ATLAS computing grid, therefore it is essential to provide a detailed and well organized web interface for the local site administrators such that they can easily spot and promptly solve site issues. Additional functionality has been developed to extract and visualize the most relevant information. The site administrators can now be pointed easily to major site issues which lead to site blacklisting as well as possible minor issues that are usually not conspicuous enough to warrant the blacklisting of a specific site, but can still cause undesired effects such as a non-negligible job failure rate. This paper summarizes the different developments and optimizations of the HammerCloud web interface and gives an overview of typical use cases.

From nonlinear optimization to convex optimization through firefly algorithm and indirect approach with applications to CAD/CAM.

PubMed

Gálvez, Akemi; Iglesias, Andrés

2013-01-01

Fitting spline curves to data points is a very important issue in many applied fields. It is also challenging, because these curves typically depend on many continuous variables in a highly interrelated nonlinear way. In general, it is not possible to compute these parameters analytically, so the problem is formulated as a continuous nonlinear optimization problem, for which traditional optimization techniques usually fail. This paper presents a new bioinspired method to tackle this issue. In this method, optimization is performed through a combination of two techniques. Firstly, we apply the indirect approach to the knots, in which they are not initially the subject of optimization but precomputed with a coarse approximation scheme. Secondly, a powerful bioinspired metaheuristic technique, the firefly algorithm, is applied to optimization of data parameterization; then, the knot vector is refined by using De Boor's method, thus yielding a better approximation to the optimal knot vector. This scheme converts the original nonlinear continuous optimization problem into a convex optimization problem, solved by singular value decomposition. Our method is applied to some illustrative real-world examples from the CAD/CAM field. Our experimental results show that the proposed scheme can solve the original continuous nonlinear optimization problem very efficiently.

From Nonlinear Optimization to Convex Optimization through Firefly Algorithm and Indirect Approach with Applications to CAD/CAM

PubMed Central

Gálvez, Akemi; Iglesias, Andrés

2013-01-01

Fitting spline curves to data points is a very important issue in many applied fields. It is also challenging, because these curves typically depend on many continuous variables in a highly interrelated nonlinear way. In general, it is not possible to compute these parameters analytically, so the problem is formulated as a continuous nonlinear optimization problem, for which traditional optimization techniques usually fail. This paper presents a new bioinspired method to tackle this issue. In this method, optimization is performed through a combination of two techniques. Firstly, we apply the indirect approach to the knots, in which they are not initially the subject of optimization but precomputed with a coarse approximation scheme. Secondly, a powerful bioinspired metaheuristic technique, the firefly algorithm, is applied to optimization of data parameterization; then, the knot vector is refined by using De Boor's method, thus yielding a better approximation to the optimal knot vector. This scheme converts the original nonlinear continuous optimization problem into a convex optimization problem, solved by singular value decomposition. Our method is applied to some illustrative real-world examples from the CAD/CAM field. Our experimental results show that the proposed scheme can solve the original continuous nonlinear optimization problem very efficiently. PMID:24376380

Soundscape elaboration from anthrophonic adaptation of community noise

NASA Astrophysics Data System (ADS)

Teddy Badai Samodra, FX

2018-03-01

Under the situation of an urban environment, noise has been a critical issue in affecting the indoor environment. A reliable approach is required for evaluation of the community noise as one factor of anthrophonic in the urban environment. This research investigates the level of noise exposure from different community noise sources and elaborates the advantage of the noise disadvantages for soundscape innovation. Integrated building element design as a protector for noise control and speech intelligibility compliance using field experiment and MATLAB programming and modeling are also carried out. Meanwhile, for simulation analysis and building acoustic optimization, Sound Reduction-Speech Intelligibility and Reverberation Time are the main parameters for identifying tropical building model as case study object. The results show that the noise control should consider its integration with the other critical issue, thermal control, in an urban environment. The 1.1 second of reverberation time for speech activities and noise reduction more than 28.66 dBA for critical frequency (20 Hz), the speech intelligibility index could be reached more than fair assessment, 0.45. Furthermore, the environmental psychology adaptation result “Close The Opening” as the best method in high noise condition and personal adjustment as the easiest and the most adaptable way.

Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints

NASA Astrophysics Data System (ADS)

Kmet', Tibor; Kmet'ová, Mária

2009-09-01

A feed forward neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The paper extends adaptive critic neural network architecture proposed by [5] to the optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.

Introduction.

PubMed

Ellerbroek, Brent L

2006-08-21

The OSA 2005 Special Topical Meeting on "Adaptive Optics: Analysis and Methods" was held in Charlotte, North Carolina, on June 8th and 9th of that year. The papers presented during those two days provided an overview of recent progress in the theory and application of adaptive optics (AO) for real-time atmospheric turbulence compensation. This Focus Issue is devoted to a further exploration of seven of these topics, ranging from formal analytical treatments of optimal estimation and control methods for AO, to recent field tests of wave front sensing and reconstruction using multiple laser guide stars.

Ascent Guidance for a Winged Boost Vehicle. M.S. Thesis

NASA Technical Reports Server (NTRS)

Corvin, Michael Alexander

1988-01-01

The objective of the advanced ascent guidance study was to investigate guidance concepts which could contribute to increased autonomy during ascent operations in a winged boost vehicle such as the proposed Shuttle II. The guidance scheme was required to yield near a full-optimal ascent in the presence of vehicle system and environmental dispersions. The study included consideration of trajectory shaping issues, trajectory design, closed loop and predictive adaptive guidance techniques and control of dynamic pressure by throttling. An extensive ascent vehicle simulation capability was developed for use in the study.

Current trends in the design of scaffolds for computer-aided tissue engineering.

PubMed

Giannitelli, S M; Accoto, D; Trombetta, M; Rainer, A

2014-02-01

Advances introduced by additive manufacturing have significantly improved the ability to tailor scaffold architecture, enhancing the control over microstructural features. This has led to a growing interest in the development of innovative scaffold designs, as testified by the increasing amount of research activities devoted to the understanding of the correlation between topological features of scaffolds and their resulting properties, in order to find architectures capable of optimal trade-off between often conflicting requirements (such as biological and mechanical ones). The main aim of this paper is to provide a review and propose a classification of existing methodologies for scaffold design and optimization in order to address key issues and help in deciphering the complex link between design criteria and resulting scaffold properties. Copyright © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Youssef, Tarek A.; El Hariri, Mohamad; Elsayed, Ahmed T.

The smart grid is seen as a power system with realtime communication and control capabilities between the consumer and the utility. This modern platform facilitates the optimization in energy usage based on several factors including environmental, price preferences, and system technical issues. In this paper a real-time energy management system (EMS) for microgrids or nanogrids was developed. The developed system involves an online optimization scheme to adapt its parameters based on previous, current, and forecasted future system states. The communication requirements for all EMS modules were analyzed and are all integrated over a data distribution service (DDS) Ethernet network withmore » appropriate quality of service (QoS) profiles. In conclusion, the developed EMS was emulated with actual residential energy consumption and irradiance data from Miami, Florida and proved its effectiveness in reducing consumers’ bills and achieving flat peak load profiles.« less

Methodological optimization of tinnitus assessment using prepulse inhibition of the acoustic startle reflex.

PubMed

Longenecker, R J; Galazyuk, A V

2012-11-16

Recently prepulse inhibition of the acoustic startle reflex (ASR) became a popular technique for tinnitus assessment in laboratory animals. This method confers a significant advantage over the previously used time-consuming behavioral approaches utilizing basic mechanisms of conditioning. Although this technique has been successfully used to assess tinnitus in different laboratory animals, many of the finer details of this methodology have not been described enough to be replicated, but are critical for tinnitus assessment. Here we provide detail description of key procedures and methodological issues that provide guidance for newcomers with the process of learning to correctly apply gap detection techniques for tinnitus assessment in laboratory animals. The major categories of these issues include: refinement of hardware for best performance, optimization of stimulus parameters, behavioral considerations, and identification of optimal strategies for data analysis. This article is part of a Special Issue entitled: Tinnitus Neuroscience. Copyright © 2012. Published by Elsevier B.V.

An optimized routing algorithm for the automated assembly of standard multimode ribbon fibers in a full-mesh optical backplane

NASA Astrophysics Data System (ADS)

Basile, Vito; Guadagno, Gianluca; Ferrario, Maddalena; Fassi, Irene

2018-03-01

In this paper a parametric, modular and scalable algorithm allowing a fully automated assembly of a backplane fiber-optic interconnection circuit is presented. This approach guarantees the optimization of the optical fiber routing inside the backplane with respect to specific criteria (i.e. bending power losses), addressing both transmission performance and overall costs issues. Graph theory has been exploited to simplify the complexity of the NxN full-mesh backplane interconnection topology, firstly, into N independent sub-circuits and then, recursively, into a limited number of loops easier to be generated. Afterwards, the proposed algorithm selects a set of geometrical and architectural parameters whose optimization allows to identify the optimal fiber optic routing for each sub-circuit of the backplane. The topological and numerical information provided by the algorithm are then exploited to control a robot which performs the automated assembly of the backplane sub-circuits. The proposed routing algorithm can be extended to any array architecture and number of connections thanks to its modularity and scalability. Finally, the algorithm has been exploited for the automated assembly of an 8x8 optical backplane realized with standard multimode (MM) 12-fiber ribbons.

Biomimetics of human movement: functional or aesthetic?

PubMed

Harris, Christopher M

2009-09-01

How should robotic or prosthetic arms be programmed to move? Copying human smooth movements is popular in synthetic systems, but what does this really achieve? We cannot address these biomimetic issues without a deep understanding of why natural movements are so stereotyped. In this article, we distinguish between 'functional' and 'aesthetic' biomimetics. Functional biomimetics requires insight into the problem that nature has solved and recognition that a similar problem exists in the synthetic system. In aesthetic biomimetics, nature is copied for its own sake and no insight is needed. We examine the popular minimum jerk (MJ) model that has often been used to generate smooth human-like point-to-point movements in synthetic arms. The MJ model was originally justified as maximizing 'smoothness'; however, it is also the limiting optimal trajectory for a wide range of cost functions for brief movements, including the minimum variance (MV) model, where smoothness is a by-product of optimizing the speed-accuracy trade-off imposed by proportional noise (PN: signal-dependent noise with the standard deviation proportional to mean). PN is unlikely to be dominant in synthetic systems, and the control objectives of natural movements (speed and accuracy) would not be optimized in synthetic systems by human-like movements. Thus, employing MJ or MV controllers in robotic arms is just aesthetic biomimetics. For prosthetic arms, the goal is aesthetic by definition, but it is still crucial to recognize that MV trajectories and PN are deeply embedded in the human motor system. Thus, PN arises at the neural level, as a recruitment strategy of motor units and probably optimizes motor neuron noise. Human reaching is under continuous adaptive control. For prosthetic devices that do not have this natural architecture, natural plasticity would drive the system towards unnatural movements. We propose that a truly neuromorphic system with parallel force generators (muscle fibres) and noisy drivers (motor neurons) would permit plasticity to adapt the control of a prosthetic limb towards human-like movement.

Image management research

NASA Technical Reports Server (NTRS)

Watson, Andrew B.

1988-01-01

Two types of research issues are involved in image management systems with space station applications: image processing research and image perception research. The image processing issues are the traditional ones of digitizing, coding, compressing, storing, analyzing, and displaying, but with a new emphasis on the constraints imposed by the human perceiver. Two image coding algorithms have been developed that may increase the efficiency of image management systems (IMS). Image perception research involves a study of the theoretical and practical aspects of visual perception of electronically displayed images. Issues include how rapidly a user can search through a library of images, how to make this search more efficient, and how to present images in terms of resolution and split screens. Other issues include optimal interface to an IMS and how to code images in a way that is optimal for the human perceiver. A test-bed within which such issues can be addressed has been designed.

RNA-SeQC: RNA-seq metrics for quality control and process optimization.

PubMed

DeLuca, David S; Levin, Joshua Z; Sivachenko, Andrey; Fennell, Timothy; Nazaire, Marc-Danie; Williams, Chris; Reich, Michael; Winckler, Wendy; Getz, Gad

2012-06-01

RNA-seq, the application of next-generation sequencing to RNA, provides transcriptome-wide characterization of cellular activity. Assessment of sequencing performance and library quality is critical to the interpretation of RNA-seq data, yet few tools exist to address this issue. We introduce RNA-SeQC, a program which provides key measures of data quality. These metrics include yield, alignment and duplication rates; GC bias, rRNA content, regions of alignment (exon, intron and intragenic), continuity of coverage, 3'/5' bias and count of detectable transcripts, among others. The software provides multi-sample evaluation of library construction protocols, input materials and other experimental parameters. The modularity of the software enables pipeline integration and the routine monitoring of key measures of data quality such as the number of alignable reads, duplication rates and rRNA contamination. RNA-SeQC allows investigators to make informed decisions about sample inclusion in downstream analysis. In summary, RNA-SeQC provides quality control measures critical to experiment design, process optimization and downstream computational analysis. See www.genepattern.org to run online, or www.broadinstitute.org/rna-seqc/ for a command line tool.

Edge control in CNC polishing, paper 2: simulation and validation of tool influence functions on edges.

PubMed

Li, Hongyu; Walker, David; Yu, Guoyu; Sayle, Andrew; Messelink, Wilhelmus; Evans, Rob; Beaucamp, Anthony

2013-01-14

Edge mis-figure is regarded as one of the most difficult technical issues for manufacturing the segments of extremely large telescopes, which can dominate key aspects of performance. A novel edge-control technique has been developed, based on 'Precessions' polishing technique and for which accurate and stable edge tool influence functions (TIFs) are crucial. In the first paper in this series [D. Walker Opt. Express 20, 19787-19798 (2012)], multiple parameters were experimentally optimized using an extended set of experiments. The first purpose of this new work is to 'short circuit' this procedure through modeling. This also gives the prospect of optimizing local (as distinct from global) polishing for edge mis-figure, now under separate development. This paper presents a model that can predict edge TIFs based on surface-speed profiles and pressure distributions over the polishing spot at the edge of the part, the latter calculated by finite element analysis and verified by direct force measurement. This paper also presents a hybrid-measurement method for edge TIFs to verify the simulation results. Experimental and simulation results show good agreement.

Scheduling Aircraft Landings under Constrained Position Shifting

NASA Technical Reports Server (NTRS)

Balakrishnan, Hamsa; Chandran, Bala

2006-01-01

Optimal scheduling of airport runway operations can play an important role in improving the safety and efficiency of the National Airspace System (NAS). Methods that compute the optimal landing sequence and landing times of aircraft must accommodate practical issues that affect the implementation of the schedule. One such practical consideration, known as Constrained Position Shifting (CPS), is the restriction that each aircraft must land within a pre-specified number of positions of its place in the First-Come-First-Served (FCFS) sequence. We consider the problem of scheduling landings of aircraft in a CPS environment in order to maximize runway throughput (minimize the completion time of the landing sequence), subject to operational constraints such as FAA-specified minimum inter-arrival spacing restrictions, precedence relationships among aircraft that arise either from airline preferences or air traffic control procedures that prevent overtaking, and time windows (representing possible control actions) during which each aircraft landing can occur. We present a Dynamic Programming-based approach that scales linearly in the number of aircraft, and describe our computational experience with a prototype implementation on realistic data for Denver International Airport.

How Can We Mobilize Action to Realize UHC in Asia?

PubMed

Akaza, Hideyuki; Kawahara, Norie; Fukuda, Takashi; Horie, Shigeo; Thabrany, Hasbullah; Nozaki, Shinjiro

2017-11-26

The 2016 World Cancer Congress, organised by UICC, was held in Paris in November 2016, under the theme “Mobilizing action – Inspiring Change.” As part of Track 4 presentations on the theme of “Strengthening cancer control: optimizing outcomes of health systems,” UICC-Asian Regional Office (UICC-ARO) held a symposium to discuss the issue of mobilizing action to realize UHC in Asia. Introducing the symposium, Hideyuki Akaza noted that universal health coverage (UHC) is included in the Sustainable Development Goals and one of the key issues for achieving UHC will be how to balance patient needs with the economic burden of cancer. Speakers from Japan and Indonesia addressed various issues, including the current status and challenges for medical economic evaluation in Asia, the importance of resource stratification, prospects for precision medicine, and the outlook for cancer control and UHC in developing and emerging countries in Asia. Key issues raised included how to respond to the rising costs of treating cancer as new and increasingly expensive drugs come to the market. Speakers and participants noted that health technology assessment programs are being developed around Asia in order to evaluate the cost-effectiveness of drugs in the face of budgetary constraints within increasingly pressurized national health systems. The importance of screening and early detection was also noted as effective means that have the potential to reduce reliance on expensive drugs for advanced cancers. The symposium was chaired jointly by Hideyuki Akaza and Shinjiro Nozaki (WHO Kobe Centre). Creative Commons Attribution License

A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems

DOE PAGES

Molzahn, Daniel K.; Dorfler, Florian K.; Sandberg, Henrik; ...

2017-07-25

Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed energy resources requiring optimization and control of power systems with many controllable devices, distributed algorithms have been the subject of significant research interest. Here, this paper surveys the literature of distributed algorithms with applications to optimization and control of power systems. In particular, this paper reviews distributed algorithms for offline solution of optimal power flow (OPF) problems as well as online algorithms for real-time solution of OPF, optimal frequency control, optimal voltage control, and optimal wide-area control problems.

A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Molzahn, Daniel K.; Dorfler, Florian K.; Sandberg, Henrik

Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed energy resources requiring optimization and control of power systems with many controllable devices, distributed algorithms have been the subject of significant research interest. Here, this paper surveys the literature of distributed algorithms with applications to optimization and control of power systems. In particular, this paper reviews distributed algorithms for offline solution of optimal power flow (OPF) problems as well as online algorithms for real-time solution of OPF, optimal frequency control, optimal voltage control, and optimal wide-area control problems.

Theory, simulation and experiments for precise deflection control of radiotherapy electron beams.

PubMed

Figueroa, R; Leiva, J; Moncada, R; Rojas, L; Santibáñez, M; Valente, M; Velásquez, J; Young, H; Zelada, G; Yáñez, R; Guillen, Y

2018-03-08

Conventional radiotherapy is mainly applied by linear accelerators. Although linear accelerators provide dual (electron/photon) radiation beam modalities, both of them are intrinsically produced by a megavoltage electron current. Modern radiotherapy treatment techniques are based on suitable devices inserted or attached to conventional linear accelerators. Thus, precise control of delivered beam becomes a main key issue. This work presents an integral description of electron beam deflection control as required for novel radiotherapy technique based on convergent photon beam production. Theoretical and Monte Carlo approaches were initially used for designing and optimizing device´s components. Then, dedicated instrumentation was developed for experimental verification of electron beam deflection due to the designed magnets. Both Monte Carlo simulations and experimental results support the reliability of electrodynamics models used to predict megavoltage electron beam control. Copyright © 2018 Elsevier Ltd. All rights reserved.

Design Issues of GaAs and AlGaAs Delta-Doped p-i-n Quantum-Well APD's

NASA Technical Reports Server (NTRS)

Wang, Yang

1994-01-01

We examine the basic design issues in the optimization of GaAs delta-doped and AlGAs delta-doped quantum-well avalanche photodiode (APD) structures using a theoretical analysis based on an ensemble Monte Carlo simulation. The devices are variations of the p-i-n doped quantum-well structure previously described in the literature. They have the same low-noise, high-gain and high-bandwidth features as the p-i-n doped quantum-well device. However, the use of delta doping provides far greater control or the doping concentrations within each stage possibly enhancing the extent to which the device can be depleted. As a result, it is expected that the proposed devices will operate at higher gain levels (at very low noise) than devices previously developed.

The Additional Value of an E-Mail to Inform Healthcare Professionals of a Drug Safety Issue: A Randomized Controlled Trial in the Netherlands.

PubMed

Piening, Sigrid; de Graeff, Pieter A; Straus, Sabine M J M; Haaijer-Ruskamp, Flora M; Mol, Peter G M

2013-09-01

The usefulness and the impact of Direct Healthcare Professional Communications (DHPCs, or 'Dear Doctor letters') in changing the clinical behaviour of physicians have been debated. Changes in the current risk communication methods should preferably be based on the preferences of the healthcare professionals, to optimize the uptake of the message. The aim of this study was to assess whether safety issues are communicated more effectively with an additional e-mail sent by the Dutch Medicines Evaluation Board (MEB) than with the DHPC only. A randomized controlled trial was conducted amongst ophthalmologists and hospital pharmacists in the Netherlands, who were the target group of a DHPC that was issued for pegaptanib, a drug that is administered intra-ocularly in patients with macular degeneration. The intervention group (N = 110) received the pegaptanib DHPC, as well as the MEB e-mail. The control group (N = 105) received the traditional paper-based DHPC only. Two weeks later, the study population received an invitation to fill out an online questionnaire. Questions were asked about the respondents' knowledge and attitude regarding the pegaptanib issue, and any action they had consequently taken. Additional questions were asked about their satisfaction with the DHPC and the e-mail, and their preferred source of such information. Forty respondents (18.6%) completed the questionnaire. Eighty-one percent of the respondents in the intervention group (N = 21) and 47% of the control group (N = 19) correctly indicated that a serious increase in intra-ocular pressure could be caused by pegaptanib injections (Fishers' exact test, p = 0.046). Nine respondents in the intervention group versus none of the control group respondents indicated that they had taken action in response to the pegaptanib safety issue (Fishers' exact test, p = 0.01). The majority of both the intervention group and the control group confirmed that they would like to receive an MEB e-mail with safety information about drugs in the future (90 and 95 %, respectively). The results of this study indicate that an additional e-mail might strengthen the uptake of the safety information provided to healthcare professionals, who prefer to receive an e-mail from the MEB as a source of such information, as well as the DHPC. This study may serve as a starting point for new strategies to improve risk communication regarding safety issues associated with drugs and its impact on prescribing.

Optimization and standardization of pavement management processes.

DOT National Transportation Integrated Search

2004-08-01

This report addresses issues related to optimization and standardization of current pavement management processes in Kentucky. Historical pavement management records were analyzed, which indicates that standardization is necessary in future pavement ...

Optimal Assembly of Psychological and Educational Tests.

ERIC Educational Resources Information Center

van der Linden, Wim J.

1998-01-01

Reviews optimal test-assembly literature and introduces the contributions to this special issue. Discusses four approaches to computerized test assembly: (1) heuristic-based test assembly; (2) 0-1 linear programming; (3) network-flow programming; and (4) an optimal design approach. Contains a bibliography of 90 sources on test assembly.…

Experience with an integrated control and monitoring system at the El Segundo generating station

DOE Office of Scientific and Technical Information (OSTI.GOV)

Papilla, R.P.; McKinley, J.H.; Blanco, M.A.

1992-01-01

This paper describes the EPRI/Southern California Edison (SCE) El Segundo Integrated Control and Monitoring System (ICMS) project and relates key project experiences. The ICMS project is a cost-shared effort between EPRI and SCE designed to address the issues involved with integrating power plant diagnostic and condition monitoring with control. A digital distributed control system retrofit for SCE's El Segundo Units 3 and 4 provided the case study. although many utilities have retrofitted power plant units with distributed control systems (DCS's) and have applied diagnostics and monitoring programs to improve operations and performance, the approach taken in this project, that is,more » integrating the monitoring function with the control function, is profoundly new and unique. Over the life of the El Segundo ICMS, SCE expects to realize savings form life optimization, increased operating flexibility, improved heat rate, reduced NO{sub x} emissions, and lower maintenance costs. These savings are expected to be significant over the life of the system.« less

LDRD Final Report: Global Optimization for Engineering Science Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

HART,WILLIAM E.

1999-12-01

For a wide variety of scientific and engineering problems the desired solution corresponds to an optimal set of objective function parameters, where the objective function measures a solution's quality. The main goal of the LDRD ''Global Optimization for Engineering Science Problems'' was the development of new robust and efficient optimization algorithms that can be used to find globally optimal solutions to complex optimization problems. This SAND report summarizes the technical accomplishments of this LDRD, discusses lessons learned and describes open research issues.

Centralized mission planning and scheduling system for the Landsat Data Continuity Mission

USGS Publications Warehouse

Kavelaars, Alicia; Barnoy, Assaf M.; Gregory, Shawna; Garcia, Gonzalo; Talon, Cesar; Greer, Gregory; Williams, Jason; Dulski, Vicki

2014-01-01

Satellites in Low Earth Orbit provide missions with closer range for studying aspects such as geography and topography, but often require efficient utilization of space and ground assets. Optimizing schedules for these satellites amounts to a complex planning puzzle since it requires operators to face issues such as discontinuous ground contacts, limited onboard memory storage, constrained downlink margin, and shared ground antenna resources. To solve this issue for the Landsat Data Continuity Mission (LDCM, Landsat 8), all the scheduling exchanges for science data request, ground/space station contact, and spacecraft maintenance and control will be coordinated through a centralized Mission Planning and Scheduling (MPS) engine, based upon GMV’s scheduling system flexplan9 . The synchronization between all operational functions must be strictly maintained to ensure efficient mission utilization of ground and spacecraft activities while working within the bounds of the space and ground resources, such as Solid State Recorder (SSR) and available antennas. This paper outlines the functionalities that the centralized planning and scheduling system has in its operational control and management of the Landsat 8 spacecraft.

Existence and characterization of optimal control in mathematics model of diabetics population

NASA Astrophysics Data System (ADS)

Permatasari, A. H.; Tjahjana, R. H.; Udjiani, T.

2018-03-01

Diabetes is a chronic disease with a huge burden affecting individuals and the whole society. In this paper, we constructed the optimal control mathematical model by applying a strategy to control the development of diabetic population. The constructed mathematical model considers the dynamics of disabled people due to diabetes. Moreover, an optimal control approach is proposed in order to reduce the burden of pre-diabetes. Implementation of control is done by preventing the pre-diabetes develop into diabetics with and without complications. The existence of optimal control and characterization of optimal control is discussed in this paper. Optimal control is characterized by applying the Pontryagin minimum principle. The results indicate that there is an optimal control in optimization problem in mathematics model of diabetic population. The effect of the optimal control variable (prevention) is strongly affected by the number of healthy people.

Data Acquisition and Preprocessing in Studies on Humans: What Is Not Taught in Statistics Classes?

PubMed

Zhu, Yeyi; Hernandez, Ladia M; Mueller, Peter; Dong, Yongquan; Forman, Michele R

2013-01-01

The aim of this paper is to address issues in research that may be missing from statistics classes and important for (bio-)statistics students. In the context of a case study, we discuss data acquisition and preprocessing steps that fill the gap between research questions posed by subject matter scientists and statistical methodology for formal inference. Issues include participant recruitment, data collection training and standardization, variable coding, data review and verification, data cleaning and editing, and documentation. Despite the critical importance of these details in research, most of these issues are rarely discussed in an applied statistics program. One reason for the lack of more formal training is the difficulty in addressing the many challenges that can possibly arise in the course of a study in a systematic way. This article can help to bridge this gap between research questions and formal statistical inference by using an illustrative case study for a discussion. We hope that reading and discussing this paper and practicing data preprocessing exercises will sensitize statistics students to these important issues and achieve optimal conduct, quality control, analysis, and interpretation of a study.

Understanding medical group financial and operational performance: the synergistic effect of linking statistical process control and profit and loss.

PubMed

Smolko, J R; Greisler, D S

2001-01-01

There is ongoing pressure for medical groups owned by not-for-profit health care systems or for-profit entrepreneurs to generate profit. The fading promise of superior strategy through health care integration has boards of directors clamoring for bottom-line performance. While prudent, sole focus on the bottom line through the lens of the profit-and-loss (P&L) statement provides incomplete information upon which to base executive decisions. The purpose of this paper is to suggest that placing statistical process control (SPC) charts in tandem with the P&L statement provides a more complete picture of medical group performance thereby optimizing decision making as executives deal with the whitewater issues surrounding physician practice ownership.

Fly ash system technology improves opacity

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

2007-06-15

Unit 3 of the Dave Johnston Power Plant east of Glenrock, WY, USA had problems staying at or below the opacity limits set by the state. The unit makes use of a Lodge Cottrell precipitator. When the plant changed to burning Power River Basin coal, ash buildup became a significant issue as the fly ash control system was unable to properly evacuate hoppers on the unit. To overcome the problem, the PLC on the unit was replaced with a software optimization package called SmartAsh for the precipitator fly ash control system, at a cost of $500,000. After the upgrade, theremore » have been no plugged hoppers and the opacity has been reduced from around 20% to 3-5%. 2 figs.« less

Aerothermodynamic heating and performance analysis of a high-lift aeromaneuvering AOTV concept

NASA Technical Reports Server (NTRS)

Menees, G. P.; Brown, K. G.; Wilson, J. F.; Davies, C. B.

1985-01-01

The thermal-control requirements for design-optimized aeromaneuvering performance are determined for space-based applications and low-earth orbit sorties involving large, multiple plane-inclination changes. The leading-edge heating analysis is the most advanced developed for hypersonic-rarefied flow over lifting surfaces at incidence. The effects of leading-edge bluntness, low-density viscous phenomena, and finite-rate flow-field chemistry and surface catalysis are accounted for. The predicted aerothermodynamic heating characteristics are correlated with thermal-control and flight-performance capabilities. The mission payload capability for delivery, retrieval, and combined operations is determined for round-trip sorties extending to polar orbits. Recommendations are given for future design refinements. The results help to identify technology issues required to develop prototype operational systems.

Expanding integrated vector management to promote healthy environments

PubMed Central

Lizzi, Karina M.; Qualls, Whitney A.; Brown, Scott C.; Beier, John C.

2014-01-01

Integrated Vector Management (IVM) strategies are intended to protect communities from pathogen transmission by arthropods. These strategies target multiple vectors and different ecological and socioeconomic settings, but the aggregate benefits of IVM are limited by the narrow focus of its approach; IVM strategies only aim to control arthropod vectors. We argue that IVM should encompass environmental modifications at early stages, for instance, infrastructural development and sanitation services, to regulate not only vectors but also nuisance-biting arthropods. An additional focus on nuisance-biting arthropods will improve public health, quality of life, and minimize social disparity issues fostered by pests. Optimally, IVM could incorporate environmental awareness and promotion of control methods in order to proactively reduce threats of serious pest situations. PMID:25028090

EDITORIAL: Quantum control theory for coherence and information dynamics Quantum control theory for coherence and information dynamics

NASA Astrophysics Data System (ADS)

Viola, Lorenza; Tannor, David

2011-08-01

Precisely characterizing and controlling the dynamics of realistic open quantum systems has emerged in recent years as a key challenge across contemporary quantum sciences and technologies, with implications ranging from physics, chemistry and applied mathematics to quantum information processing (QIP) and quantum engineering. Quantum control theory aims to provide both a general dynamical-system framework and a constructive toolbox to meet this challenge. The purpose of this special issue of Journal of Physics B: Atomic, Molecular and Optical Physics is to present a state-of-the-art account of recent advances and current trends in the field, as reflected in two international meetings that were held on the subject over the last summer and which motivated in part the compilation of this volume—the Topical Group: Frontiers in Open Quantum Systems and Quantum Control Theory, held at the Institute for Theoretical Atomic, Molecular and Optical Physics (ITAMP) in Cambridge, Massachusetts (USA), from 1-14 August 2010, and the Safed Workshop on Quantum Decoherence and Thermodynamics Control, held in Safed (Israel), from 22-27 August 2010. Initial developments in quantum control theory date back to (at least) the early 1980s, and have been largely inspired by the well-established mathematical framework for classical dynamical systems. As the above-mentioned meetings made clear, and as the burgeoning body of literature on the subject testifies, quantum control has grown since then well beyond its original boundaries, and has by now evolved into a highly cross-disciplinary field which, while still fast-moving, is also entering a new phase of maturity, sophistication, and integration. Two trends deserve special attention: on the one hand, a growing emphasis on control tasks and methodologies that are specifically motivated by QIP, in addition and in parallel to applications in more traditional areas where quantum coherence is nevertheless vital (such as, for instance, quantum control of chemical reactions or high-resolution magnetic resonance spectroscopy); on the other hand, an unprecedented demand for close coupling between theory and experiment, with theoretical developments becoming more and more attuned to and driven by experimental advances as different quantum technologies continue to evolve at an impressive pace in the laboratory. Altogether, these two trends account for several of the recurrent themes in this volume, as well as in the current quantum control literature as a whole: namely, the quest for control strategies that can attain the highest degree of precision and robustness possible, while striving for efficiency and, ultimately, optimality in achieving the intended control task under realistic operational constraints. From a theory standpoint, this makes it imperative to take into account increasingly more realistic control settings; to assess the quantitative impact of limited control resources and/or system knowledge; and to provide a rigorous and general foundation for existing experimental approaches in order to further enhance applicability and performance. From an experimental standpoint, renewed emphasis is in turn placed on validating theoretical predictions and benchmarking performance, so that the limiting constraints can be singled out for additional theoretical analysis and guidance. This ongoing cross-talk is clearly reflected in this collection, which brings together theoreticians and experimentalists, with a significant fraction of the papers reporting on combined quantum control theory-experiment efforts. While a precise categorization would neither be possible nor desirable, contributions to this volume have been loosely grouped into five broad sections. This grouping has been made in the hope that connections between different problems and/or technical approaches will become more transparent, facilitating the transfer of concepts and methods. The special issue opens with a section devoted to open-loop control methods, with special emphasis on dynamical decoupling (DD), which is becoming an increasingly important tool for decoherence control at the physical 'quantum firmware' level. In addition to including original research results, the first two articles, by Brion et al and Biercuk et al, also serve to pedagogically review some background in their respective subjects. In particular, Brion et al revisit one of the conceptually simplest approaches to open-loop manipulation of both closed and open quantum systems, nonholonomic control, motivated by its broad applicability to QIP settings. A special instance of open-loop control based on sequences of (nearly) instantaneous `bang-bang' pulses is addressed by Biercuk et al, who reformulate the simplest DD scenario, suppression of phase decoherence in a single qubit, as a filter-design problem. Peng et al report on the implementation of 'concatenated' DD for arbitrary single-qubit decoherence in the context of nuclear magnetic resonance QIP. A dedicated analysis of the performance of different DD schemes in the presence of realistic pulse errors is given by Wang and Dobrovitski. DD is also one of the strategies used by Lucamarini et al to reduce polarization decoherence in a photon qubit. These authors additionally report on the use of active feedback to counter transmission noise, effectively setting the stage for the second section, which is centered on closed-loop control. Unlike in open-loop control, measurement is an essential ingredient in closed-loop schemes aimed at both reliably identifying features of the target quantum system and further modifying its dynamics. The importance of directly measuring the spectrum of the underlying system-environment coupling is stressed by Almog et al, who show how this knowledge is crucial, in particular, for predicting the performance of DD sequences in experiments and for optimizing performance. Riofrio et al address a weak-measurement protocol for implementing quantum state tomography, which is a necessary 'primitive' for inferring the target quantum state and thereby diagnosing the control performance. Next, the impact of realistic control and system imperfections in continuous-time Markovian feedback strategies for rapid state preparation is analyzed by Combes and Wiseman. A prominent role is played in the special issue by optimal control (OC) approaches, reflecting their central importance for quantum control and QIP. The OC contributions have been divided into two separate sections, depending on whether the target dynamics is modeled as Hamiltonian (section 3) or dissipative (section 4), respectively. The contribution by Beltrani et al deals with `control landscapes', which provide a foundation for analyzing the performance of numerical OC algorithms and their robustness against control errors. Specifically, this paper characterizes geometric properties of the control landscape, relevant to the optimal control of state-to-state transitions. Application of OC theory to the problem of population transfer and coherence enhancement in Λ-systems is studied by Kumar et al, whereas Goerz et al report on the OC-design of a high-fidelity controlled phase-gate in atomic qubits. The robustness of an OC solution is specifically addressed by Negretti et al, along with an approach for identifying easily implementable while still 'close-to-optimal' control pulses. Powerful relaxation-optimized OC schemes (based on so-called opengrape algorithms) for generating unitary target gates in the presence of known dissipation parameters are discussed by Schulte-Herbrüggen et al. Next, Lapert et al report on the problem of time-optimal control of spin-1/2 systems undergoing Bloch relaxation dynamics, highlighting the crucial role played by singular extremals in the control synthesis. Alternative approaches for optimized control of qubits exposed to various decoherence processes are developed by Esher et al and Xue et al, based on a perturbative 'bath-optimized' formalism and on numerical optimization via a genetic algorithm, respectively. Testifying to the richness of the field, the volume concludes with four contributions that address a diverse range of problems. The exploitation of properties of adiabatic quantum evolutions is common to the first two papers. In particular, Legthtas et al offer a rigorous explanation for the robustness of a control protocol, chirped pulsing, that is widely employed in 'adiabatic rapid passage' experiments, while Han et al present a theoretical framework for adiabatic Raman photo-association schemes relevant to ultracold atomic systems. In the context of cavity quantum electrodynamics, Montenegro and Orszag describe how to engineer a system of two atoms coupled to distant lossy cavities so that stable atomic entanglement is generated. Finally, still very little is known about the physical mechanisms that are responsible for and control the experimentally observed 'coherent' features of transport phenomena in biological systems. The last contribution by Alicki and Giraldi analyzes energy transport in dynamical systems that can be modeled as 'quantum networks', and points to this fascinating emerging frontier. It is our hope that the above papers may help readers to gain an overview of some of the main trends in current quantum control efforts, both theoretical and experimental. In closing, we take the opportunity to thank the organizations which sponsored the above-mentioned ITAMP Topical Group (the United States National Science Foundation and Harvard University) and the Safed Workshop (the Israeli Science Foundation, the Safed Scientific Workshop program, CECAM and ACAM). Last but not least our sincere gratitude goes to all of the contributors to the volume and the reviewers as well as the J. Phys. B staff, for their respective efforts in preparing the papers and ensuring the overall quality of this special issue.

Performance Optimizing Multi-Objective Adaptive Control with Time-Varying Model Reference Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

2017-01-01

This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks.

PubMed

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-04-19

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs. However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%.

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks

PubMed Central

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-01-01

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs). However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%. PMID:28422062

Optimization of proximity ligation assay (PLA) for detection of protein interactions and fusion proteins in non-adherent cells: application to pre-B lymphocytes.

PubMed

Debaize, Lydie; Jakobczyk, Hélène; Rio, Anne-Gaëlle; Gandemer, Virginie; Troadec, Marie-Bérengère

2017-01-01

Genetic abnormalities, including chromosomal translocations, are described for many hematological malignancies. From the clinical perspective, detection of chromosomal abnormalities is relevant not only for diagnostic and treatment purposes but also for prognostic risk assessment. From the translational research perspective, the identification of fusion proteins and protein interactions has allowed crucial breakthroughs in understanding the pathogenesis of malignancies and consequently major achievements in targeted therapy. We describe the optimization of the Proximity Ligation Assay (PLA) to ascertain the presence of fusion proteins, and protein interactions in non-adherent pre-B cells. PLA is an innovative method of protein-protein colocalization detection by molecular biology that combines the advantages of microscopy with the advantages of molecular biology precision, enabling detection of protein proximity theoretically ranging from 0 to 40 nm. We propose an optimized PLA procedure. We overcome the issue of maintaining non-adherent hematological cells by traditional cytocentrifugation and optimized buffers, by changing incubation times, and modifying washing steps. Further, we provide convincing negative and positive controls, and demonstrate that optimized PLA procedure is sensitive to total protein level. The optimized PLA procedure allows the detection of fusion proteins and protein interactions on non-adherent cells. The optimized PLA procedure described here can be readily applied to various non-adherent hematological cells, from cell lines to patients' cells. The optimized PLA protocol enables detection of fusion proteins and their subcellular expression, and protein interactions in non-adherent cells. Therefore, the optimized PLA protocol provides a new tool that can be adopted in a wide range of applications in the biological field.

A mixed methods approach to assess animal vaccination programmes: The case of rabies control in Bamako, Mali.

PubMed

Mosimann, Laura; Traoré, Abdallah; Mauti, Stephanie; Léchenne, Monique; Obrist, Brigit; Véron, René; Hattendorf, Jan; Zinsstag, Jakob

2017-01-01

In the framework of the research network on integrated control of zoonoses in Africa (ICONZ) a dog rabies mass vaccination campaign was carried out in two communes of Bamako (Mali) in September 2014. A mixed method approach, combining quantitative and qualitative tools, was developed to evaluate the effectiveness of the intervention towards optimization for future scale-up. Actions to control rabies occur on one level in households when individuals take the decision to vaccinate their dogs. However, control also depends on provision of vaccination services and community participation at the intermediate level of social resilience. Mixed methods seem necessary as the problem-driven transdisciplinary project includes epidemiological components in addition to social dynamics and cultural, political and institutional issues. Adapting earlier effectiveness models for health intervention to rabies control, we propose a mixed method assessment of individual effectiveness parameters like availability, affordability, accessibility, adequacy or acceptability. Triangulation of quantitative methods (household survey, empirical coverage estimation and spatial analysis) with qualitative findings (participant observation, focus group discussions) facilitate a better understanding of the weight of each effectiveness determinant, and the underlying reasons embedded in the local understandings, cultural practices, and social and political realities of the setting. Using this method, a final effectiveness of 33% for commune Five and 28% for commune Six was estimated, with vaccination coverage of 27% and 20%, respectively. Availability was identified as the most sensitive effectiveness parameter, attributed to lack of information about the campaign. We propose a mixed methods approach to optimize intervention design, using an "intervention effectiveness optimization cycle" with the aim of maximizing effectiveness. Empirical vaccination coverage estimation is compared to the effectiveness model with its determinants. In addition, qualitative data provide an explanatory framework for deeper insight, validation and interpretation of results which should improve the intervention design while involving all stakeholders and increasing community participation. This work contributes vital information for the optimization and scale-up of future vaccination campaigns in Bamako, Mali. The proposed mixed method, although incompletely applied in this case study, should be applicable to similar rabies interventions targeting elimination in other settings. Copyright © 2016 Elsevier B.V. All rights reserved.

Critical Care Management Focused on Optimizing Brain Function After Cardiac Arrest.

PubMed

Nakashima, Ryuta; Hifumi, Toru; Kawakita, Kenya; Okazaki, Tomoya; Egawa, Satoshi; Inoue, Akihiko; Seo, Ryutaro; Inagaki, Nobuhiro; Kuroda, Yasuhiro

2017-03-24

The discussion of neurocritical care management in post-cardiac arrest syndrome (PCAS) has generally focused on target values used for targeted temperature management (TTM). There has been less attention paid to target values for systemic and cerebral parameters to minimize secondary brain damage in PCAS. And the neurologic indications for TTM to produce a favorable neurologic outcome remain to be determined. Critical care management of PCAS patients is fundamental and essential for both cardiologists and general intensivists to improve neurologic outcome, because definitive therapy of PCAS includes both special management of the cause of cardiac arrest, such as coronary intervention to ischemic heart disease, and intensive management of the results of cardiac arrest, such as ventilation strategies to avoid brain ischemia. We reviewed the literature and the latest research about the following issues and propose practical care recommendations. Issues are (1) prediction of TTM candidate on admission, (2) cerebral blood flow and metabolism and target value of them, (3) seizure management using continuous electroencephalography, (4) target value of hemodynamic stabilization and its method, (5) management and analysis of respiration, (6) sedation and its monitoring, (7) shivering control and its monitoring, and (8) glucose management. We hope to establish standards of neurocritical care to optimize brain function and produce a favorable neurologic outcome.

Geometric modeling of space-optimal unit-cell-based tissue engineering scaffolds

NASA Astrophysics Data System (ADS)

Rajagopalan, Srinivasan; Lu, Lichun; Yaszemski, Michael J.; Robb, Richard A.

2005-04-01

Tissue engineering involves regenerating damaged or malfunctioning organs using cells, biomolecules, and synthetic or natural scaffolds. Based on their intended roles, scaffolds can be injected as space-fillers or be preformed and implanted to provide mechanical support. Preformed scaffolds are biomimetic "trellis-like" structures which, on implantation and integration, act as tissue/organ surrogates. Customized, computer controlled, and reproducible preformed scaffolds can be fabricated using Computer Aided Design (CAD) techniques and rapid prototyping devices. A curved, monolithic construct with minimal surface area constitutes an efficient substrate geometry that promotes cell attachment, migration and proliferation. However, current CAD approaches do not provide such a biomorphic construct. We address this critical issue by presenting one of the very first physical realizations of minimal surfaces towards the construction of efficient unit-cell based tissue engineering scaffolds. Mask programmability, and optimal packing density of triply periodic minimal surfaces are used to construct the optimal pore geometry. Budgeted polygonization, and progressive minimal surface refinement facilitate the machinability of these surfaces. The efficient stress distributions, as deduced from the Finite Element simulations, favor the use of these scaffolds for orthopedic applications.

Spontaneous revisitation during visual exploration as a link among strategic behavior, learning, and the hippocampus.

PubMed

Voss, Joel L; Warren, David E; Gonsalves, Brian D; Federmeier, Kara D; Tranel, Dan; Cohen, Neal J

2011-08-02

Effective exploratory behaviors involve continuous updating of sensory sampling to optimize the efficacy of information gathering. Despite some work on this issue in animals, little information exists regarding the cognitive or neural mechanisms for this sort of behavioral optimization in humans. Here we examined a visual exploration phenomenon that occurred when human subjects studying an array of objects spontaneously looked "backward" in their scanning paths to view recently seen objects again. This "spontaneous revisitation" of recently viewed objects was associated with enhanced hippocampal activity and superior subsequent memory performance in healthy participants, but occurred only rarely in amnesic patients with severe damage to the hippocampus. These findings demonstrate the necessity of the hippocampus not just in the aspects of long-term memory with which it has been associated previously, but also in the short-term adaptive control of behavior. Functional neuroimaging showed hippocampal engagement occurring in conjunction with frontocerebellar circuits, thereby revealing some of the larger brain circuitry essential for the strategic deployment of information-seeking behaviors that optimize learning.

Toward industrial production of isoprenoids in Escherichia coli: Lessons learned from CRISPR-Cas9 based optimization of a chromosomally integrated mevalonate pathway.

PubMed

Alonso-Gutierrez, Jorge; Koma, Daisuke; Hu, Qijun; Yang, Yuchen; Chan, Leanne J G; Petzold, Christopher J; Adams, Paul D; Vickers, Claudia E; Nielsen, Lars K; Keasling, Jay D; Lee, Taek S

2018-04-01

Escherichia coli has been the organism of choice for the production of different chemicals by engineering native and heterologous pathways. In the present study, we simultaneously address some of the main issues associated with E. coli as an industrial platform for isoprenoids, including an inability to grow on sucrose, a lack of endogenous control over toxic mevalonate (MVA) pathway intermediates, and the limited pathway engineering into the chromosome. As a proof of concept, we generated an E. coli DH1 strain able to produce the isoprenoid bisabolene from sucrose by integrating the cscAKB operon into the chromosome and by expressing a heterologous MVA pathway under stress-responsive control. Production levels dropped dramatically relative to plasmid-mediated expression when the entire pathway was integrated into the chromosome. In order to optimize the chromosomally integrated MVA pathway, we established a CRISPR-Cas9 system to rapidly and systematically replace promoter sequences. This strategy led to higher pathway expression and a fivefold improvement in bisabolene production. More interestingly, we analyzed proteomics data sets to understand and address some of the challenges associated with metabolic engineering of the chromosomally integrated pathway. This report shows that integrating plasmid-optimized operons into the genome and making them work optimally is not a straightforward task and any poor engineering choices on the chromosome may lead to cell death rather than just resulting in low titers. Based on these results, we also propose directions for chromosomal metabolic engineering. © 2017 Wiley Periodicals, Inc.

Branch target buffer design and optimization

NASA Technical Reports Server (NTRS)

Perleberg, Chris H.; Smith, Alan J.

1993-01-01

Consideration is given to two major issues in the design of branch target buffers (BTBs), with the goal of achieving maximum performance for a given number of bits allocated to the BTB design. The first issue is BTB management; the second is what information to keep in the BTB. A number of solutions to these problems are reviewed, and various optimizations in the design of BTBs are discussed. Design target miss ratios for BTBs are developed, making it possible to estimate the performance of BTBs for real workloads.

A proposal of optimal sampling design using a modularity strategy

NASA Astrophysics Data System (ADS)

Simone, A.; Giustolisi, O.; Laucelli, D. B.

2016-08-01

In real water distribution networks (WDNs) are present thousands nodes and optimal placement of pressure and flow observations is a relevant issue for different management tasks. The planning of pressure observations in terms of spatial distribution and number is named sampling design and it was faced considering model calibration. Nowadays, the design of system monitoring is a relevant issue for water utilities e.g., in order to manage background leakages, to detect anomalies and bursts, to guarantee service quality, etc. In recent years, the optimal location of flow observations related to design of optimal district metering areas (DMAs) and leakage management purposes has been faced considering optimal network segmentation and the modularity index using a multiobjective strategy. Optimal network segmentation is the basis to identify network modules by means of optimal conceptual cuts, which are the candidate locations of closed gates or flow meters creating the DMAs. Starting from the WDN-oriented modularity index, as a metric for WDN segmentation, this paper proposes a new way to perform the sampling design, i.e., the optimal location of pressure meters, using newly developed sampling-oriented modularity index. The strategy optimizes the pressure monitoring system mainly based on network topology and weights assigned to pipes according to the specific technical tasks. A multiobjective optimization minimizes the cost of pressure meters while maximizing the sampling-oriented modularity index. The methodology is presented and discussed using the Apulian and Exnet networks.

Optimal control and optimal trajectories of regional macroeconomic dynamics based on the Pontryagin maximum principle

NASA Astrophysics Data System (ADS)

Bulgakov, V. K.; Strigunov, V. V.

2009-05-01

The Pontryagin maximum principle is used to prove a theorem concerning optimal control in regional macroeconomics. A boundary value problem for optimal trajectories of the state and adjoint variables is formulated, and optimal curves are analyzed. An algorithm is proposed for solving the boundary value problem of optimal control. The performance of the algorithm is demonstrated by computing an optimal control and the corresponding optimal trajectories.

"Optimal" Size and Schooling: A Relative Concept.

ERIC Educational Resources Information Center

Swanson, Austin D.

Issues in economies of scale and optimal school size are discussed in this paper, which seeks to explain the curvilinear nature of the educational cost curve as a function of "transaction costs" and to establish "optimal size" as a relative concept. Based on the argument that educational consolidation has facilitated diseconomies of scale, the…

Development of an RNA-based kit for easy generation of TCR-engineered lymphocytes to control T-cell assay performance.

PubMed

Bidmon, Nicole; Kind, Sonja; Welters, Marij J P; Joseph-Pietras, Deborah; Laske, Karoline; Maurer, Dominik; Hadrup, Sine Reker; Schreibelt, Gerty; Rae, Richard; Sahin, Ugur; Gouttefangeas, Cécile; Britten, Cedrik M; van der Burg, Sjoerd H

2018-07-01

Cell-based assays to monitor antigen-specific T-cell responses are characterized by their high complexity and should be conducted under controlled conditions to lower multiple possible sources of assay variation. However, the lack of standard reagents makes it difficult to directly compare results generated in one lab over time and across institutions. Therefore TCR-engineered reference samples (TERS) that contain a defined number of antigen-specific T cells and continuously deliver stable results are urgently needed. We successfully established a simple and robust TERS technology that constitutes a useful tool to overcome this issue for commonly used T-cell immuno-assays. To enable users to generate large-scale TERS, on-site using the most commonly used electroporation (EP) devices, an RNA-based kit approach, providing stable TCR mRNA and an optimized manufacturing protocol were established. In preparation for the release of this immuno-control kit, we established optimal EP conditions on six devices and initiated an extended RNA stability study. Furthermore, we coordinated on-site production of TERS with 4 participants. Finally, a proficiency panel was organized to test the unsupervised production of TERS at different laboratories using the kit approach. The results obtained show the feasibility and robustness of the kit approach for versatile in-house production of cellular control samples. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Surrogate-based Analysis and Optimization

NASA Technical Reports Server (NTRS)

Queipo, Nestor V.; Haftka, Raphael T.; Shyy, Wei; Goel, Tushar; Vaidyanathan, Raj; Tucker, P. Kevin

2005-01-01

A major challenge to the successful full-scale development of modem aerospace systems is to address competing objectives such as improved performance, reduced costs, and enhanced safety. Accurate, high-fidelity models are typically time consuming and computationally expensive. Furthermore, informed decisions should be made with an understanding of the impact (global sensitivity) of the design variables on the different objectives. In this context, the so-called surrogate-based approach for analysis and optimization can play a very valuable role. The surrogates are constructed using data drawn from high-fidelity models, and provide fast approximations of the objectives and constraints at new design points, thereby making sensitivity and optimization studies feasible. This paper provides a comprehensive discussion of the fundamental issues that arise in surrogate-based analysis and optimization (SBAO), highlighting concepts, methods, techniques, as well as practical implications. The issues addressed include the selection of the loss function and regularization criteria for constructing the surrogates, design of experiments, surrogate selection and construction, sensitivity analysis, convergence, and optimization. The multi-objective optimal design of a liquid rocket injector is presented to highlight the state of the art and to help guide future efforts.

A stochastic discrete optimization model for designing container terminal facilities

NASA Astrophysics Data System (ADS)

Zukhruf, Febri; Frazila, Russ Bona; Burhani, Jzolanda Tsavalista

2017-11-01

As uncertainty essentially affect the total transportation cost, it remains important in the container terminal that incorporates several modes and transshipments process. This paper then presents a stochastic discrete optimization model for designing the container terminal, which involves the decision of facilities improvement action. The container terminal operation model is constructed by accounting the variation of demand and facilities performance. In addition, for illustrating the conflicting issue that practically raises in the terminal operation, the model also takes into account the possible increment delay of facilities due to the increasing number of equipment, especially the container truck. Those variations expectantly reflect the uncertainty issue in the container terminal operation. A Monte Carlo simulation is invoked to propagate the variations by following the observed distribution. The problem is constructed within the framework of the combinatorial optimization problem for investigating the optimal decision of facilities improvement. A new variant of glow-worm swarm optimization (GSO) is thus proposed for solving the optimization, which is rarely explored in the transportation field. The model applicability is tested by considering the actual characteristics of the container terminal.

Application of Decision Tree to Obtain Optimal Operation Rules for Reservoir Flood Control Considering Sediment Desilting-Case Study of Tseng Wen Reservoir

NASA Astrophysics Data System (ADS)

ShiouWei, L.

2014-12-01

Reservoirs are the most important water resources facilities in Taiwan.However,due to the steep slope and fragile geological conditions in the mountain area,storm events usually cause serious debris flow and flood,and the flood then will flush large amount of sediment into reservoirs.The sedimentation caused by flood has great impact on the reservoirs life.Hence,how to operate a reservoir during flood events to increase the efficiency of sediment desilting without risk the reservoir safety and impact the water supply afterward is a crucial issue in Taiwan. 　Therefore,this study developed a novel optimization planning model for reservoir flood operation considering flood control and sediment desilting,and proposed easy to use operating rules represented by decision trees.The decision trees rules have considered flood mitigation,water supply and sediment desilting.The optimal planning model computes the optimal reservoir release for each flood event that minimum water supply impact and maximum sediment desilting without risk the reservoir safety.Beside the optimal flood operation planning model,this study also proposed decision tree based flood operating rules that were trained by the multiple optimal reservoir releases to synthesis flood scenarios.The synthesis flood scenarios consists of various synthesis storm events,reservoir's initial storage and target storages at the end of flood operating. 　Comparing the results operated by the decision tree operation rules(DTOR) with that by historical operation for Krosa Typhoon in 2007,the DTOR removed sediment 15.4% more than that of historical operation with reservoir storage only8.38×106m3 less than that of historical operation.For Jangmi Typhoon in 2008,the DTOR removed sediment 24.4% more than that of historical operation with reservoir storage only 7.58×106m3 less than that of historical operation.The results show that the proposed DTOR model can increase the sediment desilting efficiency and extend the reservoir life.

Subsystem Analysis/Optimization for the X-34 Main Propulsion System

NASA Technical Reports Server (NTRS)

McDonald, J. P.; Hedayat, A.; Brown, T. M.; Knight, K. C.; Champion, R. H., Jr.

1998-01-01

The Orbital Sciences Corporation X-34 vehicle demonstrates technologies and operations key to future reusable launch vehicles. The general flight performance goal of this unmanned rocket plane is Mach 8 flight at an altitude of 250,000 feet. The Main Propulsion System (MPS) supplies liquid propellants to the main engine, which provides the primary thrust for attaining mission goals. Major MPS design and operational goals are aircraft-like ground operations, quick turnaround between missions, and low initial/operational costs. Analyses related to optimal MPS subsystem design are reviewed in this paper. A pressurization system trade weighs maintenance/reliability concerns against those for safety in a comparison of designs using pressure regulators versus orifices to control pressurant flow. A propellant dump/feed system analysis weighs the issues of maximum allowable vehicle landing weight, trajectory, and MPS complexity to arrive at a final configuration for propellant dump/feed systems.

A Computational Intelligence (CI) Approach to the Precision Mars Lander Problem

NASA Technical Reports Server (NTRS)

Birge, Brian; Walberg, Gerald

2002-01-01

A Mars precision landing requires a landed footprint of no more than 100 meters. Obstacles to reducing the landed footprint include trajectory dispersions due to initial atmospheric entry conditions such as entry angle, parachute deployment height, environment parameters such as wind, atmospheric density, parachute deployment dynamics, unavoidable injection error or propagated error from launch, etc. Computational Intelligence (CI) techniques such as Artificial Neural Nets and Particle Swarm Optimization have been shown to have great success with other control problems. The research period extended previous work on investigating applicability of the computational intelligent approaches. The focus of this investigation was on Particle Swarm Optimization and basic Neural Net architectures. The research investigating these issues was performed for the grant cycle from 5/15/01 to 5/15/02. Matlab 5.1 and 6.0 along with NASA's POST were the primary computational tools.

A Global Optimization Methodology for Rocket Propulsion Applications

NASA Technical Reports Server (NTRS)

2001-01-01

While the response surface method is an effective method in engineering optimization, its accuracy is often affected by the use of limited amount of data points for model construction. In this chapter, the issues related to the accuracy of the RS approximations and possible ways of improving the RS model using appropriate treatments, including the iteratively re-weighted least square (IRLS) technique and the radial-basis neural networks, are investigated. A main interest is to identify ways to offer added capabilities for the RS method to be able to at least selectively improve the accuracy in regions of importance. An example is to target the high efficiency region of a fluid machinery design space so that the predictive power of the RS can be maximized when it matters most. Analytical models based on polynomials, with controlled level of noise, are used to assess the performance of these techniques.

Use of the Collaborative Optimization Architecture for Launch Vehicle Design

NASA Technical Reports Server (NTRS)

Braun, R. D.; Moore, A. A.; Kroo, I. M.

1996-01-01

Collaborative optimization is a new design architecture specifically created for large-scale distributed-analysis applications. In this approach, problem is decomposed into a user-defined number of subspace optimization problems that are driven towards interdisciplinary compatibility and the appropriate solution by a system-level coordination process. This decentralized design strategy allows domain-specific issues to be accommodated by disciplinary analysts, while requiring interdisciplinary decisions to be reached by consensus. The present investigation focuses on application of the collaborative optimization architecture to the multidisciplinary design of a single-stage-to-orbit launch vehicle. Vehicle design, trajectory, and cost issues are directly modeled. Posed to suit the collaborative architecture, the design problem is characterized by 5 design variables and 16 constraints. Numerous collaborative solutions are obtained. Comparison of these solutions demonstrates the influence which an priori ascent-abort criterion has on development cost. Similarly, objective-function selection is discussed, demonstrating the difference between minimum weight and minimum cost concepts. The operational advantages of the collaborative optimization

Planning of water resources management and pollution control for Heshui River watershed, China: A full credibility-constrained programming approach.

PubMed

Zhang, Y M; Huang, G; Lu, H W; He, Li

2015-08-15

A key issue facing integrated water resources management and water pollution control is to address the vague parametric information. A full credibility-based chance-constrained programming (FCCP) method is thus developed by introducing the new concept of credibility into the modeling framework. FCCP can deal with fuzzy parameters appearing concurrently in the objective and both sides of the constraints of the model, but also provide a credibility level indicating how much confidence one can believe the optimal modeling solutions. The method is applied to Heshui River watershed in the south-central China for demonstration. Results from the case study showed that groundwater would make up for the water shortage in terms of the shrinking surface water and rising water demand, and the optimized total pumpage of groundwater from both alluvial and karst aquifers would exceed 90% of its maximum allowable levels when credibility level is higher than or equal to 0.9. It is also indicated that an increase in credibility level would induce a reduction in cost for surface water acquisition, a rise in cost from groundwater withdrawal, and negligible variation in cost for water pollution control. Copyright © 2015 Elsevier B.V. All rights reserved.

Self-balancing dynamic scheduling of electrical energy for energy-intensive enterprises

NASA Astrophysics Data System (ADS)

Gao, Yunlong; Gao, Feng; Zhai, Qiaozhu; Guan, Xiaohong

2013-06-01

Balancing production and consumption with self-generation capacity in energy-intensive enterprises has huge economic and environmental benefits. However, balancing production and consumption with self-generation capacity is a challenging task since the energy production and consumption must be balanced in real time with the criteria specified by power grid. In this article, a mathematical model for minimising the production cost with exactly realisable energy delivery schedule is formulated. And a dynamic programming (DP)-based self-balancing dynamic scheduling algorithm is developed to obtain the complete solution set for such a multiple optimal solutions problem. For each stage, a set of conditions are established to determine whether a feasible control trajectory exists. The state space under these conditions is partitioned into subsets and each subset is viewed as an aggregate state, the cost-to-go function is then expressed as a function of initial and terminal generation levels of each stage and is proved to be a staircase function with finite steps. This avoids the calculation of the cost-to-go of every state to resolve the issue of dimensionality in DP algorithm. In the backward sweep process of the algorithm, an optimal policy is determined to maximise the realisability of energy delivery schedule across the entire time horizon. And then in the forward sweep process, the feasible region of the optimal policy with the initial and terminal state at each stage is identified. Different feasible control trajectories can be identified based on the region; therefore, optimising for the feasible control trajectory is performed based on the region with economic and reliability objectives taken into account.

Adaptive hybrid optimal quantum control for imprecisely characterized systems.

PubMed

Egger, D J; Wilhelm, F K

2014-06-20

Optimal quantum control theory carries a huge promise for quantum technology. Its experimental application, however, is often hindered by imprecise knowledge of the input variables, the quantum system's parameters. We show how to overcome this by adaptive hybrid optimal control, using a protocol named Ad-HOC. This protocol combines open- and closed-loop optimal control by first performing a gradient search towards a near-optimal control pulse and then an experimental fidelity estimation with a gradient-free method. For typical settings in solid-state quantum information processing, adaptive hybrid optimal control enhances gate fidelities by an order of magnitude, making optimal control theory applicable and useful.

Set-Based Discrete Particle Swarm Optimization Based on Decomposition for Permutation-Based Multiobjective Combinatorial Optimization Problems.

PubMed

Yu, Xue; Chen, Wei-Neng; Gu, Tianlong; Zhang, Huaxiang; Yuan, Huaqiang; Kwong, Sam; Zhang, Jun

2018-07-01

This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class and they can be very different. However, as the permutation-based MOCOPs share the inherent similarity that the structure of their search space is usually in the shape of a permutation tree, this paper proposes a generic multiobjective set-based particle swarm optimization methodology based on decomposition, termed MS-PSO/D. In order to coordinate with the property of permutation-based MOCOPs, MS-PSO/D utilizes an element-based representation and a constructive approach. Through this, feasible solutions under constraints can be generated step by step following the permutation-tree-shaped structure. And problem-related heuristic information is introduced in the constructive approach for efficiency. In order to address the multiobjective optimization issues, the decomposition strategy is employed, in which the problem is converted into multiple single-objective subproblems according to a set of weight vectors. Besides, a flexible mechanism for diversity control is provided in MS-PSO/D. Extensive experiments have been conducted to study MS-PSO/D on two permutation-based MOCOPs, namely the MOTSP and the MOPSP. Experimental results validate that the proposed methodology is promising.

Stoichiometry control in quantum dots: a viable analog to impurity doping of bulk materials.

PubMed

Luther, Joseph M; Pietryga, Jeffrey M

2013-03-26

A growing body of research indicates that the stoichiometry of compound semiconductor quantum dots (QDs) may offer control over the materials' optoelectronic properties in ways that could be invaluable in electronic devices. Quantum dots have been characterized as having a stoichiometric bulk-like core with a highly reconstructed surface of a more flexible composition, consisting essentially of ligated, weakly bound ions. As such, many efforts toward stoichiometry-based control over material properties have focused on ligand manipulation. In this issue of ACS Nano, Murray and Kagan's groups instead demonstrate control of the conductive properties of QD arrays by altering the stoichiometry via atomic infusion using a thermal evaporation technique. In this work, PbSe and PbS QD films are made to show controlled n- or p-type behavior, which is key to developing optimized QD-based electronics. In this Perspective, we discuss recent developments and the future outlook in using stoichiometry as a tool to further manipulate QD material properties in this context.

A review of fault tolerant control strategies applied to proton exchange membrane fuel cell systems

NASA Astrophysics Data System (ADS)

Dijoux, Etienne; Steiner, Nadia Yousfi; Benne, Michel; Péra, Marie-Cécile; Pérez, Brigitte Grondin

2017-08-01

Fuel cells are powerful systems for power generation. They have a good efficiency and do not generate greenhouse gases. This technology involves a lot of scientific fields, which leads to the appearance of strongly inter-dependent parameters. This makes the system particularly hard to control and increases fault's occurrence frequency. These two issues call for the necessity to maintain the system performance at the expected level, even in faulty operating conditions. It is called "fault tolerant control" (FTC). The present paper aims to give the state of the art of FTC applied to the proton exchange membrane fuel cell (PEMFC). The FTC approach is composed of two parts. First, a diagnosis part allows the identification and the isolation of a fault; it requires a good a priori knowledge of all the possible faults. Then, a control part allows an optimal control strategy to find the best operating point to recover/mitigate the fault; it requires the knowledge of the degradation phenomena and their mitigation strategies.

Software defined network architecture based research on load balancing strategy

NASA Astrophysics Data System (ADS)

You, Xiaoqian; Wu, Yang

2018-05-01

As a new type network architecture, software defined network has the key idea of separating the control place of the network from the transmission plane, to manage and control the network in a concentrated way; in addition, the network interface is opened on the control layer and the data layer, so as to achieve programmable control of the network. Considering that only the single shortest route is taken into the calculation of traditional network data flow transmission, and congestion and resource consumption caused by excessive load of link circuits are ignored, a link circuit load based flow media business QoS gurantee system is proposed in this article to divide the flow in the network into ordinary data flow and QoS flow. In this way, it supervises the link circuit load with the controller so as to calculate reasonable route rapidly and issue the flow table to the exchanger, to finish rapid data transmission. In addition, it establishes a simulation platform to acquire optimized result through simulation experiment.

Analytical design of an industrial two-term controller for optimal regulatory control of open-loop unstable processes under operational constraints.

PubMed

Tchamna, Rodrigue; Lee, Moonyong

2018-01-01

This paper proposes a novel optimization-based approach for the design of an industrial two-term proportional-integral (PI) controller for the optimal regulatory control of unstable processes subjected to three common operational constraints related to the process variable, manipulated variable and its rate of change. To derive analytical design relations, the constrained optimal control problem in the time domain was transformed into an unconstrained optimization problem in a new parameter space via an effective parameterization. The resulting optimal PI controller has been verified to yield optimal performance and stability of an open-loop unstable first-order process under operational constraints. The proposed analytical design method explicitly takes into account the operational constraints in the controller design stage and also provides useful insights into the optimal controller design. Practical procedures for designing optimal PI parameters and a feasible constraint set exclusive of complex optimization steps are also proposed. The proposed controller was compared with several other PI controllers to illustrate its performance. The robustness of the proposed controller against plant-model mismatch has also been investigated. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal solution and optimality condition of the Hunter-Saxton equation

NASA Astrophysics Data System (ADS)

Shen, Chunyu

2018-02-01

This paper is devoted to the optimal distributed control problem governed by the Hunter-Saxton equation with constraints on the control. We first investigate the existence and uniqueness of weak solution for the controlled system with appropriate initial value and boundary conditions. In contrast with our previous research, the proof of solution mapping is local Lipschitz continuous, which is one big improvement. Second, based on the well-posedness result, we find a unique optimal control and optimal solution for the controlled system with the quadratic cost functional. Moreover, we establish the sufficient and necessary optimality condition of an optimal control by means of the optimal control theory, not limited to the necessary condition, which is another major novelty of this paper. We also discuss the optimality conditions corresponding to two physical meaningful distributed observation cases.

Optimal input shaping for Fisher identifiability of control-oriented lithium-ion battery models

NASA Astrophysics Data System (ADS)

Rothenberger, Michael J.

This dissertation examines the fundamental challenge of optimally shaping input trajectories to maximize parameter identifiability of control-oriented lithium-ion battery models. Identifiability is a property from information theory that determines the solvability of parameter estimation for mathematical models using input-output measurements. This dissertation creates a framework that exploits the Fisher information metric to quantify the level of battery parameter identifiability, optimizes this metric through input shaping, and facilitates faster and more accurate estimation. The popularity of lithium-ion batteries is growing significantly in the energy storage domain, especially for stationary and transportation applications. While these cells have excellent power and energy densities, they are plagued with safety and lifespan concerns. These concerns are often resolved in the industry through conservative current and voltage operating limits, which reduce the overall performance and still lack robustness in detecting catastrophic failure modes. New advances in automotive battery management systems mitigate these challenges through the incorporation of model-based control to increase performance, safety, and lifespan. To achieve these goals, model-based control requires accurate parameterization of the battery model. While many groups in the literature study a variety of methods to perform battery parameter estimation, a fundamental issue of poor parameter identifiability remains apparent for lithium-ion battery models. This fundamental challenge of battery identifiability is studied extensively in the literature, and some groups are even approaching the problem of improving the ability to estimate the model parameters. The first approach is to add additional sensors to the battery to gain more information that is used for estimation. The other main approach is to shape the input trajectories to increase the amount of information that can be gained from input-output measurements, and is the approach used in this dissertation. Research in the literature studies optimal current input shaping for high-order electrochemical battery models and focuses on offline laboratory cycling. While this body of research highlights improvements in identifiability through optimal input shaping, each optimal input is a function of nominal parameters, which creates a tautology. The parameter values must be known a priori to determine the optimal input for maximizing estimation speed and accuracy. The system identification literature presents multiple studies containing methods that avoid the challenges of this tautology, but these methods are absent from the battery parameter estimation domain. The gaps in the above literature are addressed in this dissertation through the following five novel and unique contributions. First, this dissertation optimizes the parameter identifiability of a thermal battery model, which Sergio Mendoza experimentally validates through a close collaboration with this dissertation's author. Second, this dissertation extends input-shaping optimization to a linear and nonlinear equivalent-circuit battery model and illustrates the substantial improvements in Fisher identifiability for a periodic optimal signal when compared against automotive benchmark cycles. Third, this dissertation presents an experimental validation study of the simulation work in the previous contribution. The estimation study shows that the automotive benchmark cycles either converge slower than the optimized cycle, or not at all for certain parameters. Fourth, this dissertation examines how automotive battery packs with additional power electronic components that dynamically route current to individual cells/modules can be used for parameter identifiability optimization. While the user and vehicle supervisory controller dictate the current demand for these packs, the optimized internal allocation of current still improves identifiability. Finally, this dissertation presents a robust Bayesian sequential input shaping optimization study to maximize the conditional Fisher information of the battery model parameters without prior knowledge of the nominal parameter set. This iterative algorithm only requires knowledge of the prior parameter distributions to converge to the optimal input trajectory.

Optimal Path Determination for Flying Vehicle to Search an Object

NASA Astrophysics Data System (ADS)

Heru Tjahjana, R.; Heri Soelistyo U, R.; Ratnasari, L.; Irawanto, B.

2018-01-01

In this paper, a method to determine optimal path for flying vehicle to search an object is proposed. Background of the paper is controlling air vehicle to search an object. Optimal path determination is one of the most popular problem in optimization. This paper describe model of control design for a flying vehicle to search an object, and focus on the optimal path that used to search an object. In this paper, optimal control model is used to control flying vehicle to make the vehicle move in optimal path. If the vehicle move in optimal path, then the path to reach the searched object also optimal. The cost Functional is one of the most important things in optimal control design, in this paper the cost functional make the air vehicle can move as soon as possible to reach the object. The axis reference of flying vehicle uses N-E-D (North-East-Down) coordinate system. The result of this paper are the theorems which say that the cost functional make the control optimal and make the vehicle move in optimal path are proved analytically. The other result of this paper also shows the cost functional which used is convex. The convexity of the cost functional is use for guarantee the existence of optimal control. This paper also expose some simulations to show an optimal path for flying vehicle to search an object. The optimization method which used to find the optimal control and optimal path vehicle in this paper is Pontryagin Minimum Principle.

Lineament analysis of mineral areas of interest in Afghanistan

USGS Publications Warehouse

Hubbard, Bernard E.; Mack, Thomas J.; Thompson, Allyson L.

2012-01-01

The purpose of this report and accompanying GIS data is to provide lineament maps that give one indication of areas that warrant further investigation for optimal bedrock water-well placement within 24 target areas for mineral resources (Peters and others, 2011). These data may also support the identification of faults related to modern seismic hazards (for example, Wheeler and others, 2005; Ruleman and others, 2007), as well as support studies attempting to understand the relationship between tectonic and structural controls on hydrothermal fluid flow, subsequent mineralization, and water-quality issues near mined and unmined mineral deposits (for example, Eppinger and others, 2007).

An integrated modeling and design tool for advanced optical spacecraft

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

1992-01-01

Consideration is given to the design and status of the Integrated Modeling of Optical Systems (IMOS) tool and to critical design issues. A multidisciplinary spacecraft design and analysis tool with support for structural dynamics, controls, thermal analysis, and optics, IMOS provides rapid and accurate end-to-end performance analysis, simulations, and optimization of advanced space-based optical systems. The requirements for IMOS-supported numerical arrays, user defined data structures, and a hierarchical data base are outlined, and initial experience with the tool is summarized. A simulation of a flexible telescope illustrates the integrated nature of the tools.

Multicutter machining of compound parametric surfaces

NASA Astrophysics Data System (ADS)

Hatna, Abdelmadjid; Grieve, R. J.; Broomhead, P.

2000-10-01

Parametric free forms are used in industries as disparate as footwear, toys, sporting goods, ceramics, digital content creation, and conceptual design. Optimizing tool path patterns and minimizing the total machining time is a primordial issue in numerically controlled (NC) machining of free form surfaces. We demonstrate in the present work that multi-cutter machining can achieve as much as 60% reduction in total machining time for compound sculptured surfaces. The given approach is based upon the pre-processing as opposed to the usual post-processing of surfaces for the detection and removal of interference followed by precise tracking of unmachined areas.

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

NASA Technical Reports Server (NTRS)

Shyy, Wei; Papila, Nilay; Vaidyanathan, Rajkumar; Tucker, Kevin; Turner, James E. (Technical Monitor)

2000-01-01

Modern computational and experimental tools for aerodynamics and propulsion applications have matured to a stage where they can provide substantial insight into engineering processes involving fluid flows, and can be fruitfully utilized to help improve the design of practical devices. In particular, rapid and continuous development in aerospace engineering demands that new design concepts be regularly proposed to meet goals for increased performance, robustness and safety while concurrently decreasing cost. To date, the majority of the effort in design optimization of fluid dynamics has relied on gradient-based search algorithms. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space, can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables, and methods for predicting the model performance. In this article, we review recent progress made in establishing suitable global optimization techniques employing neural network and polynomial-based response surface methodologies. Issues addressed include techniques for construction of the response surface, design of experiment techniques for supplying information in an economical manner, optimization procedures and multi-level techniques, and assessment of relative performance between polynomials and neural networks. Examples drawn from wing aerodynamics, turbulent diffuser flows, gas-gas injectors, and supersonic turbines are employed to help demonstrate the issues involved in an engineering design context. Both the usefulness of the existing knowledge to aid current design practices and the need for future research are identified.

Prescriber-pharmacist collaboration: re-engineering the partnership to optimize pain patient care.

PubMed

Ruble, James H

2013-12-01

The Walgreen Companies recently settled a Drug Enforcement Administration (DEA) administrative action and other investigations arising in connection with a controlled substance distribution facility in Florida and several of its retail pharmacies. These DEA enforcement actions upon a national chain pharmacy have resulted in a series of policies and professional practices that appear to functionally disrupt continuity of patient care. The policy issues transcend the professions and go to the core of our responsibilities to patients. It is unfortunate that regulations intended to prevent diversion also dramatically disrupt interprofessional relations. Based on public statements of professional organizations, unification on this issue seems possible. This presents an opportunity to revisit collaboration among prescribers and pharmacists in legislative and regulatory advocacy. A uniform definition of "legitimate medical purpose" is needed to maximize patient access to needed pharmacotherapy while remaining vigilant for diversion.

Space/ground systems as cooperating agents

NASA Technical Reports Server (NTRS)

Grant, T. J.

1994-01-01

Within NASA and the European Space Agency (ESA) it is agreed that autonomy is an important goal for the design of future spacecraft and that this requires on-board artificial intelligence. NASA emphasizes deep space and planetary rover missions, while ESA considers on-board autonomy as an enabling technology for missions that must cope with imperfect communications. ESA's attention is on the space/ground system. A major issue is the optimal distribution of intelligent functions within the space/ground system. This paper describes the multi-agent architecture for space/ground systems (MAASGS) which would enable this issue to be investigated. A MAASGS agent may model a complete spacecraft, a spacecraft subsystem or payload, a ground segment, a spacecraft control system, a human operator, or an environment. The MAASGS architecture has evolved through a series of prototypes. The paper recommends that the MAASGS architecture should be implemented in the operational Dutch Utilization Center.

76 FR 78929 - Establishing Timeframes for Implementation of Product Safety Labeling Changes; Request for Comments

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-20

... labeling; (2) supply chain issues; and, (3) other issues. FDA may use the information received to develop...? B. Supply Chain Issues 3. What are the supply chain factors (including storage, shipping, and... the optimal point in the supply chain (e.g., newly manufactured product, newly shipped product) and...

Implementation and Performance Issues in Collaborative Optimization

NASA Technical Reports Server (NTRS)

Braun, Robert; Gage, Peter; Kroo, Ilan; Sobieski, Ian

1996-01-01

Collaborative optimization is a multidisciplinary design architecture that is well-suited to large-scale multidisciplinary optimization problems. This paper compares this approach with other architectures, examines the details of the formulation, and some aspects of its performance. A particular version of the architecture is proposed to better accommodate the occurrence of multiple feasible regions. The use of system level inequality constraints is shown to increase the convergence rate. A series of simple test problems, demonstrated to challenge related optimization architectures, is successfully solved with collaborative optimization.

Implementation of object-oriented programming in study of electrical race car

NASA Astrophysics Data System (ADS)

Nowak, M.; Baier, M.

2016-08-01

The paper covers issue of conducting advanced research of electrical race car participating in international competition called Sileverline Corporate Challenge. Process of designing race cars in Silesian Greenpower team is aided by a professional engine test stand built particularly in purpose of this research. Phase of testing and simulation is an important part of the implementation of new technologies. Properly developed solutions and test procedures are able to significantly shorten development time and reduce design costs. Testing process must be controlled by a modular and flexible application, easy to modify and ensuring safety. This paper describes the concept of object-oriented programming in LabVIEW and exemplary architecture of object-oriented control application designed to control engine test stand of the electrical race car. Eventually, the task of application will be to steer the electromagnetic brake and the engine load torque to perform according to data from the actual race track. During the designing process of the car, minimizing energy losses and maximizing powertrain efficiency are the main aspects taken into consideration. One of the crucial issues to accomplish these goals is to maintain optimal performance of the motor by applying effective cooling. The paper covers the research verifying the effectiveness of the cooling system.

Honoring the Past and Looking to the Future: Updates on Seminal Behavior Therapy Publications on Etiology and Mechanisms of Change.

PubMed

Newman, Michelle G

2016-09-01

This is the introduction to the first of two special issues in honor of the 50th anniversary of the Association for Behavioral and Cognitive Therapies. The goal of this issue is to pay tribute to prior seminal Behavior Therapy publications on etiology and mechanisms of change, to provide an updated review of important topics covered by these papers, and to make recommendations for the future. Each invited paper highlights a particular Behavior Therapy publication's contribution to our understanding and also provides an updated review or meta-analysis on the topic of the original paper. The topics covered here include mechanisms of etiology such as preparedness, reinforcement, and control. In terms of papers on mechanisms of change, we cover mechanisms related to extinction including fear activation, within- and between-session extinction, safety behaviors, and variables related to imagery. In addition, we examine principles related to generalization of learning and optimizing the impact of homework. With the two special issues of Behavior Therapy, we hope to inspire additional research and discussion. Copyright © 2016. Published by Elsevier Ltd.

Optimal experimental designs for fMRI when the model matrix is uncertain.

PubMed

Kao, Ming-Hung; Zhou, Lin

2017-07-15

This study concerns optimal designs for functional magnetic resonance imaging (fMRI) experiments when the model matrix of the statistical model depends on both the selected stimulus sequence (fMRI design), and the subject's uncertain feedback (e.g. answer) to each mental stimulus (e.g. question) presented to her/him. While practically important, this design issue is challenging. This mainly is because that the information matrix cannot be fully determined at the design stage, making it difficult to evaluate the quality of the selected designs. To tackle this challenging issue, we propose an easy-to-use optimality criterion for evaluating the quality of designs, and an efficient approach for obtaining designs optimizing this criterion. Compared with a previously proposed method, our approach requires a much less computing time to achieve designs with high statistical efficiencies. Copyright © 2017 Elsevier Inc. All rights reserved.

Practical synchronization on complex dynamical networks via optimal pinning control

NASA Astrophysics Data System (ADS)

Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

2015-07-01

We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

Parametric optimal control of uncertain systems under an optimistic value criterion

NASA Astrophysics Data System (ADS)

Li, Bo; Zhu, Yuanguo

2018-01-01

It is well known that the optimal control of a linear quadratic model is characterized by the solution of a Riccati differential equation. In many cases, the corresponding Riccati differential equation cannot be solved exactly such that the optimal feedback control may be a complex time-oriented function. In this article, a parametric optimal control problem of an uncertain linear quadratic model under an optimistic value criterion is considered for simplifying the expression of optimal control. Based on the equation of optimality for the uncertain optimal control problem, an approximation method is presented to solve it. As an application, a two-spool turbofan engine optimal control problem is given to show the utility of the proposed model and the efficiency of the presented approximation method.

Robust Neighboring Optimal Guidance for the Advanced Launch System

NASA Technical Reports Server (NTRS)

Hull, David G.

1993-01-01

In recent years, optimization has become an engineering tool through the availability of numerous successful nonlinear programming codes. Optimal control problems are converted into parameter optimization (nonlinear programming) problems by assuming the control to be piecewise linear, making the unknowns the nodes or junction points of the linear control segments. Once the optimal piecewise linear control (suboptimal) control is known, a guidance law for operating near the suboptimal path is the neighboring optimal piecewise linear control (neighboring suboptimal control). Research conducted under this grant has been directed toward the investigation of neighboring suboptimal control as a guidance scheme for an advanced launch system.

Thermal control systems for low-temperature heat rejection on a lunar base

NASA Technical Reports Server (NTRS)

Sridhar, K. R.; Gottmann, Matthias; Nanjundan, Ashok

1993-01-01

One of the important issues in the design of a lunar base is the thermal control system (TCS) used to reject low-temperature heat from the base. The TCS ensures that the base and the components inside are maintained within an acceptable temperature range. The temperature of the lunar surface peaks at 400 K during the 336-hour lunar day. Under these circumstances, direct dissipation of waste heat from the lunar base using passive radiators would be impractical. Thermal control systems based on thermal storage, shaded radiators, and heat pumps have been proposed. Based on proven technology, innovation, realistic complexity, reliability, and near-term applicability, a heat pump-based TCS was selected as a candidate for early missions. In this report, Rankine-cycle heat pumps and absorption heat pumps (ammonia water and lithium bromide-water) have been analyzed and optimized for a lunar base cooling load of 100 kW.

Humidity control and hydrophilic glue coating applied to mounted protein crystals improves X-ray diffraction experiments

PubMed Central

Baba, Seiki; Hoshino, Takeshi; Ito, Len; Kumasaka, Takashi

2013-01-01

Protein crystals are fragile, and it is sometimes difficult to find conditions suitable for handling and cryocooling the crystals before conducting X-ray diffraction experiments. To overcome this issue, a protein crystal-mounting method has been developed that involves a water-soluble polymer and controlled humid air that can adjust the moisture content of a mounted crystal. By coating crystals with polymer glue and exposing them to controlled humid air, the crystals were stable at room temperature and were cryocooled under optimized humidity. Moreover, the glue-coated crystals reproducibly showed gradual transformations of their lattice constants in response to a change in humidity; thus, using this method, a series of isomorphous crystals can be prepared. This technique is valuable when working on fragile protein crystals, including membrane proteins, and will also be useful for multi-crystal data collection. PMID:23999307

Closed-Loop Optimal Control Implementations for Space Applications

DTIC Science & Technology

2016-12-01

analyses of a series of optimal control problems, several real- time optimal control algorithms are developed that continuously adapt to feedback on the...through the analyses of a series of optimal control problems, several real- time optimal control algorithms are developed that continuously adapt to...information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering

Quantum optimal control with automatic differentiation using graphics processors

NASA Astrophysics Data System (ADS)

Leung, Nelson; Abdelhafez, Mohamed; Chakram, Srivatsan; Naik, Ravi; Groszkowski, Peter; Koch, Jens; Schuster, David

We implement quantum optimal control based on automatic differentiation and harness the acceleration afforded by graphics processing units (GPUs). Automatic differentiation allows us to specify advanced optimization criteria and incorporate them into the optimization process with ease. We will describe efficient techniques to optimally control weakly anharmonic systems that are commonly encountered in circuit QED, including coupled superconducting transmon qubits and multi-cavity circuit QED systems. These systems allow for a rich variety of control schemes that quantum optimal control is well suited to explore.

Adjoint Algorithm for CAD-Based Shape Optimization Using a Cartesian Method

NASA Technical Reports Server (NTRS)

Nemec, Marian; Aftosmis, Michael J.

2004-01-01

Adjoint solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape optimization. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (geometric parameters that control the shape). More recently, emerging adjoint applications focus on the analysis problem, where the adjoint solution is used to drive mesh adaptation, as well as to provide estimates of functional error bounds and corrections. The attractive feature of this approach is that the mesh-adaptation procedure targets a specific functional, thereby localizing the mesh refinement and reducing computational cost. Our focus is on the development of adjoint-based optimization techniques for a Cartesian method with embedded boundaries.12 In contrast t o implementations on structured and unstructured grids, Cartesian methods decouple the surface discretization from the volume mesh. This feature makes Cartesian methods well suited for the automated analysis of complex geometry problems, and consequently a promising approach to aerodynamic optimization. Melvin et developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the Euler equations. In both approaches, a boundary condition is introduced to approximate the effects of the evolving surface shape that results in accurate gradient computation. Central to automated shape optimization algorithms is the issue of geometry modeling and control. The need to optimize complex, "real-life" geometry provides a strong incentive for the use of parametric-CAD systems within the optimization procedure. In previous work, we presented an effective optimization framework that incorporates a direct-CAD interface. In this work, we enhance the capabilities of this framework with efficient gradient computations using the discrete adjoint method. We present details of the adjoint numerical implementation, which reuses the domain decomposition, multigrid, and time-marching schemes of the flow solver. Furthermore, we explain and demonstrate the use of CAD in conjunction with the Cartesian adjoint approach. The final paper will contain a number of complex geometry, industrially relevant examples with many design variables to demonstrate the effectiveness of the adjoint method on Cartesian meshes.

Concepts and clinical use of ultra-long basal insulin.

PubMed

Eliaschewitz, Freddy Goldberg; Barreto, Tânia

2016-01-01

Diabetes mellitus (DM) is a public health issue, affecting around 382 million people worldwide. In order to achieve glycemic goals, insulin therapy is the frontline therapy for type 1 DM patients; for patients with type 2 DM, use of insulin therapy is an option as initial or add-on therapy for those not achieving glycemic control. Despite insulin therapy developments seen in the last decades, several barriers remain for insulin initiation and optimal maintenance in clinical practice. Fear of hypoglycemia, weight gain, pain associated with blood testing and injection-related pain are the most cited reasons for not starting insulin therapy. However, new generation of basal insulin formulations, with longer length of action, have shown the capability of providing adequate glycemic control with lower risk of hypoglycemia.

Micropatterning strategies to engineer controlled cell and tissue architecture in vitro.

PubMed

D'Arcangelo, Elisa; McGuigan, Alison P

2015-01-01

Micropatterning strategies, which enable control over cell and tissue architecture in vitro, have emerged as powerful platforms for modelling tissue microenvironments at different scales and complexities. Here, we provide an overview of popular micropatterning techniques, along with detailed descriptions, to guide new users through the decision making process of which micropatterning procedure to use, and how to best obtain desired tissue patterns. Example techniques and the types of biological observations that can be made are provided from the literature. A focus is placed on microcontact printing to obtain co-cultures of patterned, confluent sheets, and the challenges associated with optimizing this protocol. Many issues associated with microcontact printing, however, are relevant to all micropatterning methodologies. Finally, we briefly discuss challenges in addressing key limitations associated with current micropatterning technologies.

Economic modeling of fault tolerant flight control systems in commercial applications

NASA Technical Reports Server (NTRS)

Finelli, G. B.

1982-01-01

This paper describes the current development of a comprehensive model which will supply the assessment and analysis capability to investigate the economic viability of Fault Tolerant Flight Control Systems (FTFCS) for commercial aircraft of the 1990's and beyond. An introduction to the unique attributes of fault tolerance and how they will influence aircraft operations and consequent airline costs and benefits is presented. Specific modeling issues and elements necessary for accurate assessment of all costs affected by ownership and operation of FTFCS are delineated. Trade-off factors are presented, aimed at exposing economically optimal realizations of system implementations, resource allocation, and operating policies. A trade-off example is furnished to graphically display some of the analysis capabilities of the comprehensive simulation model now being developed.

Unsolved Problems of Intracellular Noise

NASA Astrophysics Data System (ADS)

Paulsson, Johan

2003-05-01

Many molecules are present at so low numbers per cell that significant fluctuations arise spontaneously. Such `noise' can randomize developmental pathways, disrupt cell cycle control or force metabolites away from their optimal levels. It can also be exploited for non-genetic individuality or, surprisingly, for more reliable and deterministic control. However, in spite of the mechanistic and evolutionary significance of noise, both explicit modeling and implicit verbal reasoning in molecular biology are completely dominated by macroscopic kinetics. Here I discuss some particularly under-addressed issues of noise in genetic and metabolic networks: 1) relations between systematic macro- and mesoscopic approaches; 2) order and disorder in gene expression; 3) autorepression for checking fluctuations; 4) noise suppression by noise; 5) phase-transitions in metabolic systems; 6) effects of cell growth and division; and 7) mono- and bistable bimodal switches.

Chopped random-basis quantum optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caneva, Tommaso; Calarco, Tommaso; Montangero, Simone

2011-08-15

In this work, we describe in detail the chopped random basis (CRAB) optimal control technique recently introduced to optimize time-dependent density matrix renormalization group simulations [P. Doria, T. Calarco, and S. Montangero, Phys. Rev. Lett. 106, 190501 (2011)]. Here, we study the efficiency of this control technique in optimizing different quantum processes and we show that in the considered cases we obtain results equivalent to those obtained via different optimal control methods while using less resources. We propose the CRAB optimization as a general and versatile optimal control technique.

Formulation and Stability of Solutions.

PubMed

Akers, Michael J

2016-01-01

Ready-to-use solutions are the most preferable and most common dosage forms for injectable and topical ophthalmic products. Drugs formulated as solution almost always have chemical and physical stability challenges as well as solubility limitations and the need to prevent inadvertent microbial contamination issues. The first in this series of articles took us through a discussion of optimizing the physical stability of solutions. This article concludes this series of articles with a discussion on foreign particles, protein aggregation, and immunogenicity; optimizing microbiological activity; and osmolality (tonicity) agents, and discusses how these challenges and issues are addressed.

Optimizing Dynamical Network Structure for Pinning Control

NASA Astrophysics Data System (ADS)

Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo

2016-04-01

Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights.

Environmental optimal control strategies based on plant canopy photosynthesis responses and greenhouse climate model

NASA Astrophysics Data System (ADS)

Deng, Lujuan; Xie, Songhe; Cui, Jiantao; Liu, Tao

2006-11-01

It is the essential goal of intelligent greenhouse environment optimal control to enhance income of cropper and energy save. There were some characteristics such as uncertainty, imprecision, nonlinear, strong coupling, bigger inertia and different time scale in greenhouse environment control system. So greenhouse environment optimal control was not easy and especially model-based optimal control method was more difficult. So the optimal control problem of plant environment in intelligent greenhouse was researched. Hierarchical greenhouse environment control system was constructed. In the first level data measuring was carried out and executive machine was controlled. Optimal setting points of climate controlled variable in greenhouse was calculated and chosen in the second level. Market analysis and planning were completed in third level. The problem of the optimal setting point was discussed in this paper. Firstly the model of plant canopy photosynthesis responses and the model of greenhouse climate model were constructed. Afterwards according to experience of the planting expert, in daytime the optimal goals were decided according to the most maximal photosynthesis rate principle. In nighttime on plant better growth conditions the optimal goals were decided by energy saving principle. Whereafter environment optimal control setting points were computed by GA. Compared the optimal result and recording data in real system, the method is reasonable and can achieve energy saving and the maximal photosynthesis rate in intelligent greenhouse

Let's get technical! Gaming and technology for weight control and health promotion in children.

PubMed

Baranowski, Tom; Frankel, Leslie

2012-02-01

Most children, including lower socioeconomic status and ethnic minority children, play video games, use computers, and have cell phones, and growing numbers have smart phones and electronic tablets. They are comfortable with, even prefer, electronic media. Many expect to be entertained and have a low tolerance for didactic methods. Thus, health promotion with children needs to incorporate more interactive media. Interactive media for weight control and health promotion among children can be broadly classified into web-based educational/therapeutic programs, tailored motivational messaging systems, data monitoring and feedback systems, active video games, and diverse forms of interactive multimedia experiences involving games. This article describes the primary characteristics of these different technological methods; presents the strengths and weaknesses of each in meeting the needs of children of different ages; emphasizes that we are in the earliest stages of knowing how best to design these systems, including selecting the optimal requisite behavioral change theories; and identifies high-priority research issues. Gaming and technology offer many exciting, innovative opportunities for engaging children and promoting diet and physical activity changes that can contribute to obesity prevention and weight loss maintenance. Research needs to clarify optimal procedures for effectively promoting change with each change procedure.

Nutritional models for a Controlled Ecological Life Support System (CELSS): Linear mathematical modeling

NASA Technical Reports Server (NTRS)

Wade, Rose C.

1989-01-01

The NASA Controlled Ecological Life Support System (CELSS) Program is involved in developing a biogenerative life support system that will supply food, air, and water to space crews on long-duration missions. An important part of this effort is in development of the knowledge and technological capability of producing and processing foods to provide optimal diets for space crews. This involves such interrelated factors as determination of the diet, based on knowledge of nutrient needs of humans and adjustments in those needs that may be required as a result of the conditions of long-duration space flight; determination of the optimal mixture of crops required to provide nutrients at levels that are sufficient but not excessive or toxic; and consideration of the critical issues of spacecraft space and power limitations, which impose a phytomass minimization requirement. The complex interactions among these factors are examined with the goal of supplying a diet that will satisfy human needs while minimizing the total phytomass requirement. The approach taken was to collect plant nutritional composition and phytomass production data, identify human nutritional needs and estimate the adjustments to the nutrient requirements likely to result from space flight, and then to generate mathematical models from these data.

Recent developments in large-scale structural optimization

NASA Technical Reports Server (NTRS)

Venkayya, Vipperla B.

1989-01-01

A brief discussion is given of mathematical optimization and the motivation for the development of more recent numerical search procedures. A review of recent developments and issues in multidisciplinary optimization is also presented. These developments are discussed in the context of the preliminary design of aircraft structures. A capability description of programs FASTOP, TSO, STARS, LAGRANGE, ELFINI and ASTROS is included.

Informing efficient randomised controlled trials: exploration of challenges in developing progression criteria for internal pilot studies.

PubMed

Avery, Kerry N L; Williamson, Paula R; Gamble, Carrol; O'Connell Francischetto, Elaine; Metcalfe, Chris; Davidson, Peter; Williams, Hywel; Blazeby, Jane M

2017-02-17

Designing studies with an internal pilot phase may optimise the use of pilot work to inform more efficient randomised controlled trials (RCTs). Careful selection of preagreed decision or 'progression' criteria at the juncture between the internal pilot and main trial phases provides a valuable opportunity to evaluate the likely success of the main trial and optimise its design or, if necessary, to make the decision not to proceed with the main trial. Guidance on the appropriate selection and application of progression criteria is, however, lacking. This paper outlines the key issues to consider in the optimal development and review of operational progression criteria for RCTs with an internal pilot phase. A structured literature review and exploration of stakeholders' opinions at a Medical Research Council (MRC) Hubs for Trials Methodology Research workshop. Key stakeholders included triallists, methodologists, statisticians and funders. There is considerable variation in the use of progression criteria for RCTs with an internal pilot phase, although 3 common issues predominate: trial recruitment, protocol adherence and outcome data. Detailed and systematic reporting around the decision-making process for stopping, amending or proceeding to a main trial is uncommon, which may hamper understanding in the research community about the appropriate and optimal use of RCTs with an internal pilot phase. 10 top tips for the development, use and reporting of progression criteria for internal pilot studies are presented. Systematic and transparent reporting of the design, results and evaluation of internal pilot trials in the literature should be encouraged in order to facilitate understanding in the research community and to inform future trials. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Informing efficient randomised controlled trials: exploration of challenges in developing progression criteria for internal pilot studies

PubMed Central

Williamson, Paula R; Gamble, Carrol; O'Connell Francischetto, Elaine; Metcalfe, Chris; Davidson, Peter; Williams, Hywel; Blazeby, Jane M

2017-01-01

Objectives Designing studies with an internal pilot phase may optimise the use of pilot work to inform more efficient randomised controlled trials (RCTs). Careful selection of preagreed decision or ‘progression’ criteria at the juncture between the internal pilot and main trial phases provides a valuable opportunity to evaluate the likely success of the main trial and optimise its design or, if necessary, to make the decision not to proceed with the main trial. Guidance on the appropriate selection and application of progression criteria is, however, lacking. This paper outlines the key issues to consider in the optimal development and review of operational progression criteria for RCTs with an internal pilot phase. Design A structured literature review and exploration of stakeholders' opinions at a Medical Research Council (MRC) Hubs for Trials Methodology Research workshop. Key stakeholders included triallists, methodologists, statisticians and funders. Results There is considerable variation in the use of progression criteria for RCTs with an internal pilot phase, although 3 common issues predominate: trial recruitment, protocol adherence and outcome data. Detailed and systematic reporting around the decision-making process for stopping, amending or proceeding to a main trial is uncommon, which may hamper understanding in the research community about the appropriate and optimal use of RCTs with an internal pilot phase. 10 top tips for the development, use and reporting of progression criteria for internal pilot studies are presented. Conclusions Systematic and transparent reporting of the design, results and evaluation of internal pilot trials in the literature should be encouraged in order to facilitate understanding in the research community and to inform future trials. PMID:28213598

Finite element approximation of an optimal control problem for the von Karman equations

NASA Technical Reports Server (NTRS)

Hou, L. Steven; Turner, James C.

1994-01-01

This paper is concerned with optimal control problems for the von Karman equations with distributed controls. We first show that optimal solutions exist. We then show that Lagrange multipliers may be used to enforce the constraints and derive an optimality system from which optimal states and controls may be deduced. Finally we define finite element approximations of solutions for the optimality system and derive error estimates for the approximations.

An express method for optimally tuning an analog controller with respect to integral quality criteria

NASA Astrophysics Data System (ADS)

Golinko, I. M.; Kovrigo, Yu. M.; Kubrak, A. I.

2014-03-01

An express method for optimally tuning analog PI and PID controllers is considered. An integral quality criterion with minimizing the control output is proposed for optimizing control systems. The suggested criterion differs from existing ones in that the control output applied to the technological process is taken into account in a correct manner, due to which it becomes possible to maximally reduce the expenditure of material and/or energy resources in performing control of industrial equipment sets. With control organized in such manner, smaller wear and longer service life of control devices are achieved. A unimodal nature of the proposed criterion for optimally tuning a controller is numerically demonstrated using the methods of optimization theory. A functional interrelation between the optimal controller parameters and dynamic properties of a controlled plant is numerically determined for a single-loop control system. The results obtained from simulation of transients in a control system carried out using the proposed and existing functional dependences are compared with each other. The proposed calculation formulas differ from the existing ones by a simple structure and highly accurate search for the optimal controller tuning parameters. The obtained calculation formulas are recommended for being used by specialists in automation for design and optimization of control systems.

Performance Optimizing Adaptive Control with Time-Varying Reference Model Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Hashemi, Kelley E.

2017-01-01

This paper presents a new adaptive control approach that involves a performance optimization objective. The control synthesis involves the design of a performance optimizing adaptive controller from a subset of control inputs. The resulting effect of the performance optimizing adaptive controller is to modify the initial reference model into a time-varying reference model which satisfies the performance optimization requirement obtained from an optimal control problem. The time-varying reference model modification is accomplished by the real-time solutions of the time-varying Riccati and Sylvester equations coupled with the least-squares parameter estimation of the sensitivities of the performance metric. The effectiveness of the proposed method is demonstrated by an application of maneuver load alleviation control for a flexible aircraft.

SU-E-T-270: Optimized Shielding Calculations for Medical Linear Accelerators (LINACs).

PubMed

Muhammad, W; Lee, S; Hussain, A

2012-06-01

The purpose of radiation shielding is to reduce the effective equivalent dose from a medical linear accelerator (LINAC) to a point outside the room to a level determined by individual state/international regulations. The study was performed to design LINAC's room for newly planned radiotherapy centers. Optimized shielding calculations were performed for LINACs having maximum photon energy of 20 MV based on NCRP 151. The maximum permissible dose limits were kept 0.04 mSv/week and 0.002 mSv/week for controlled and uncontrolled areas respectively by following ALARA principle. The planned LINAC's room was compared to the already constructed (non-optimized) LINAC's room to evaluate the shielding costs and the other facilities those are directly related to the room design. In the evaluation process it was noted that the non-optimized room size (i.e., 610 × 610 cm 2 or 20 feet × 20 feet) is not suitable for total body irradiation (TBI) although the machine installed inside was having not only the facility of TBI but the license was acquired. By keeping this point in view, the optimized INAC's room size was kept 762 × 762 cm 2. Although, the area of the optimized rooms was greater than the non-planned room (i.e., 762 × 762 cm 2 instead of 610 × 610 cm 2), the shielding cost for the optimized LINAC's rooms was reduced by 15%. When optimized shielding calculations were re-performed for non-optimized shielding room (i.e., keeping room size, occupancy factors, workload etc. same), it was found that the shielding cost may be lower to 41 %. In conclusion, non- optimized LINAC's room can not only put extra financial burden on the hospital but also can cause of some serious issues related to providing health care facilities for patients. © 2012 American Association of Physicists in Medicine.

Training Recurrent Neural Networks With the Levenberg-Marquardt Algorithm for Optimal Control of a Grid-Connected Converter.

PubMed

Fu, Xingang; Li, Shuhui; Fairbank, Michael; Wunsch, Donald C; Alonso, Eduardo

2015-09-01

This paper investigates how to train a recurrent neural network (RNN) using the Levenberg-Marquardt (LM) algorithm as well as how to implement optimal control of a grid-connected converter (GCC) using an RNN. To successfully and efficiently train an RNN using the LM algorithm, a new forward accumulation through time (FATT) algorithm is proposed to calculate the Jacobian matrix required by the LM algorithm. This paper explores how to incorporate FATT into the LM algorithm. The results show that the combination of the LM and FATT algorithms trains RNNs better than the conventional backpropagation through time algorithm. This paper presents an analytical study on the optimal control of GCCs, including theoretically ideal optimal and suboptimal controllers. To overcome the inapplicability of the optimal GCC controller under practical conditions, a new RNN controller with an improved input structure is proposed to approximate the ideal optimal controller. The performance of an ideal optimal controller and a well-trained RNN controller was compared in close to real-life power converter switching environments, demonstrating that the proposed RNN controller can achieve close to ideal optimal control performance even under low sampling rate conditions. The excellent performance of the proposed RNN controller under challenging and distorted system conditions further indicates the feasibility of using an RNN to approximate optimal control in practical applications.

Real-Time Optimization and Control of Next-Generation Distribution

Science.gov Websites

Infrastructure | Grid Modernization | NREL Real-Time Optimization and Control of Next -Generation Distribution Infrastructure Real-Time Optimization and Control of Next-Generation Distribution Infrastructure This project develops innovative, real-time optimization and control methods for next-generation

Approximate approach for optimization space flights with a low thrust on the basis of sufficient optimality conditions

NASA Astrophysics Data System (ADS)

Salmin, Vadim V.

2017-01-01

Flight mechanics with a low-thrust is a new chapter of mechanics of space flight, considered plurality of all problems trajectory optimization and movement control laws and the design parameters of spacecraft. Thus tasks associated with taking into account the additional factors in mathematical models of the motion of spacecraft becomes increasingly important, as well as additional restrictions on the possibilities of the thrust vector control. The complication of the mathematical models of controlled motion leads to difficulties in solving optimization problems. Author proposed methods of finding approximate optimal control and evaluating their optimality based on analytical solutions. These methods are based on the principle of extending the class of admissible states and controls and sufficient conditions for the absolute minimum. Developed procedures of the estimation enabling to determine how close to the optimal founded solution, and indicate ways to improve them. Authors describes procedures of estimate for approximately optimal control laws for space flight mechanics problems, in particular for optimization flight low-thrust between the circular non-coplanar orbits, optimization the control angle and trajectory movement of the spacecraft during interorbital flights, optimization flights with low-thrust between arbitrary elliptical orbits Earth satellites.

A fuzzy reinforcement learning approach to power control in wireless transmitters.

PubMed

Vengerov, David; Bambos, Nicholas; Berenji, Hamid R

2005-08-01

We address the issue of power-controlled shared channel access in wireless networks supporting packetized data traffic. We formulate this problem using the dynamic programming framework and present a new distributed fuzzy reinforcement learning algorithm (ACFRL-2) capable of adequately solving a class of problems to which the power control problem belongs. Our experimental results show that the algorithm converges almost deterministically to a neighborhood of optimal parameter values, as opposed to a very noisy stochastic convergence of earlier algorithms. The main tradeoff facing a transmitter is to balance its current power level with future backlog in the presence of stochastically changing interference. Simulation experiments demonstrate that the ACFRL-2 algorithm achieves significant performance gains over the standard power control approach used in CDMA2000. Such a large improvement is explained by the fact that ACFRL-2 allows transmitters to learn implicit coordination policies, which back off under stressful channel conditions as opposed to engaging in escalating "power wars."

Low thrust spacecraft transfers optimization method with the stepwise control structure in the Earth-Moon system in terms of the L1-L2 transfer

NASA Astrophysics Data System (ADS)

Fain, M. K.; Starinova, O. L.

2016-04-01

The paper outlines the method for determination of the locally optimal stepwise control structure in the problem of the low thrust spacecraft transfer optimization in the Earth-Moon system, including the L1-L2 transfer. The total flight time as an optimization criterion is considered. The optimal control programs were obtained by using the Pontryagin's maximum principle. As a result of optimization, optimal control programs, corresponding trajectories, and minimal total flight times were determined.

The optimal location of piezoelectric actuators and sensors for vibration control of plates

NASA Astrophysics Data System (ADS)

Kumar, K. Ramesh; Narayanan, S.

2007-12-01

This paper considers the optimal placement of collocated piezoelectric actuator-sensor pairs on a thin plate using a model-based linear quadratic regulator (LQR) controller. LQR performance is taken as objective for finding the optimal location of sensor-actuator pairs. The problem is formulated using the finite element method (FEM) as multi-input-multi-output (MIMO) model control. The discrete optimal sensor and actuator location problem is formulated in the framework of a zero-one optimization problem. A genetic algorithm (GA) is used to solve the zero-one optimization problem. Different classical control strategies like direct proportional feedback, constant-gain negative velocity feedback and the LQR optimal control scheme are applied to study the control effectiveness.

Enhanced power quality based single phase photovoltaic distributed generation system

NASA Astrophysics Data System (ADS)

Panda, Aurobinda; Pathak, M. K.; Srivastava, S. P.

2016-08-01

This article presents a novel control strategy for a 1-ϕ 2-level grid-tie photovoltaic (PV) inverter to enhance the power quality (PQ) of a PV distributed generation (PVDG) system. The objective is to obtain the maximum benefits from the grid-tie PV inverter by introducing current harmonics as well as reactive power compensation schemes in its control strategy, thereby controlling the PV inverter to achieve multiple functions in the PVDG system such as: (1) active power flow control between the PV inverter and the grid, (2) reactive power compensation, and (3) grid current harmonics compensation. A PQ enhancement controller (PQEC) has been designed to achieve the aforementioned objectives. The issue of underutilisation of the PV inverter in nighttime has also been addressed in this article and for the optimal use of the system; the PV inverter is used as a shunt active power filter in nighttime. A prototype model of the proposed system is developed in the laboratory, to validate the effectiveness of the control scheme, and is tested with the help of the dSPACE DS1104 platform.

Modeling and sliding mode predictive control of the ultra-supercritical boiler-turbine system with uncertainties and input constraints.

PubMed

Tian, Zhen; Yuan, Jingqi; Zhang, Xiang; Kong, Lei; Wang, Jingcheng

2018-05-01

The coordinated control system (CCS) serves as an important role in load regulation, efficiency optimization and pollutant reduction for coal-fired power plants. The CCS faces with tough challenges, such as the wide-range load variation, various uncertainties and constraints. This paper aims to improve the load tacking ability and robustness for boiler-turbine units under wide-range operation. To capture the key dynamics of the ultra-supercritical boiler-turbine system, a nonlinear control-oriented model is developed based on mechanism analysis and model reduction techniques, which is validated with the history operation data of a real 1000 MW unit. To simultaneously address the issues of uncertainties and input constraints, a discrete-time sliding mode predictive controller (SMPC) is designed with the dual-mode control law. Moreover, the input-to-state stability and robustness of the closed-loop system are proved. Simulation results are presented to illustrate the effectiveness of the proposed control scheme, which achieves good tracking performance, disturbance rejection ability and compatibility to input constraints. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Steering Quantum Dynamics of a Two-Qubit System via Optimal Bang-Bang Control

NASA Astrophysics Data System (ADS)

Hu, Juju; Ke, Qiang; Ji, Yinghua

2018-02-01

The optimization of control time for quantum systems has been an important field of control science attracting decades of focus, which is beneficial for efficiency improvement and decoherence suppression caused by the environment. Based on analyzing the advantages and disadvantages of the existing Lyapunov control, using a bang-bang optimal control technique, we investigate the fast state control in a closed two-qubit quantum system, and give three optimized control field design methods. Numerical simulation experiments indicate the effectiveness of the methods. Compared to the standard Lyapunov control or standard bang-bang control method, the optimized control field design methods effectively shorten the state control time and avoid high-frequency oscillation that occurs in bang-bang control.

Optimal control of HIV/AIDS dynamic: Education and treatment

NASA Astrophysics Data System (ADS)

Sule, Amiru; Abdullah, Farah Aini

2014-07-01

A mathematical model which describes the transmission dynamics of HIV/AIDS is developed. The optimal control representing education and treatment for this model is explored. The existence of optimal Control is established analytically by the use of optimal control theory. Numerical simulations suggest that education and treatment for the infected has a positive impact on HIV/AIDS control.

Developing a Fundamental Model for an Integrated GPS/INS State Estimation System with Kalman Filtering

NASA Technical Reports Server (NTRS)

Canfield, Stephen

1999-01-01

This work will demonstrate the integration of sensor and system dynamic data and their appropriate models using an optimal filter to create a robust, adaptable, easily reconfigurable state (motion) estimation system. This state estimation system will clearly show the application of fundamental modeling and filtering techniques. These techniques are presented at a general, first principles level, that can easily be adapted to specific applications. An example of such an application is demonstrated through the development of an integrated GPS/INS navigation system. This system acquires both global position data and inertial body data, to provide optimal estimates of current position and attitude states. The optimal states are estimated using a Kalman filter. The state estimation system will include appropriate error models for the measurement hardware. The results of this work will lead to the development of a "black-box" state estimation system that supplies current motion information (position and attitude states) that can be used to carry out guidance and control strategies. This black-box state estimation system is developed independent of the vehicle dynamics and therefore is directly applicable to a variety of vehicles. Issues in system modeling and application of Kalman filtering techniques are investigated and presented. These issues include linearized models of equations of state, models of the measurement sensors, and appropriate application and parameter setting (tuning) of the Kalman filter. The general model and subsequent algorithm is developed in Matlab for numerical testing. The results of this system are demonstrated through application to data from the X-33 Michael's 9A8 mission and are presented in plots and simple animations.

Design of the Experimental Exposure Conditions to Simulate Ionizing Radiation Effects on Candidate Replacement Materials for the Hubble Space Telescope

NASA Technical Reports Server (NTRS)

Smith, L. Montgomery

1998-01-01

In this effort, experimental exposure times for monoenergetic electrons and protons were determined to simulate the space radiation environment effects on Teflon components of the Hubble Space Telescope. Although the energy range of the available laboratory particle accelerators was limited, optimal exposure times for 50 keV, 220 keV, 350 keV, and 500 KeV electrons were calculated that produced a dose-versus-depth profile that approximated the full spectrum profile, and were realizable with existing equipment. For the case of proton exposure, the limited energy range of the laboratory accelerator restricted simulation of the dose to a depth of .5 mil. Also, while optimal exposure times were found for 200 keV, 500 keV and 700 keV protons that simulated the full spectrum dose-versus-depth profile to this depth, they were of such short duration that the existing laboratory could not be controlled to within the required accuracy. In addition to the obvious experimental issues, other areas exist in which the analytical work could be advanced. Improved computer codes for the dose prediction- along with improved methodology for data input and output- would accelerate and make more accurate the calculational aspects. This is particularly true in the case of proton fluxes where a paucity of available predictive software appears to exist. The dated nature of many of the existing Monte Carlo particle/radiation transport codes raises the issue as to whether existing codes are sufficient for this type of analysis. Other areas that would result in greater fidelity of laboratory exposure effects to the space environment is the use of a larger number of monoenergetic particle fluxes and improved optimization algorithms to determine the weighting values.

Optimal Control Design Advantages Utilizing Two-Degree-of-Freedom Controllers

DTIC Science & Technology

1993-12-01

AFrTIGAE/ENYIV3D-27 AD--A273 839 D"TIC OPTIMAL CONTROL DESIGN ADVANTAGES UTILIZING TWO-DEGREE-OF-FREEDOM CONTROLLERS THESIS Michael J. Stephens...AFIT/GAE/ENY/93D-27 OPTIMAL CONTROL DESIGN ADVANTAGES UTILIZING TWO-DEGREE-OF-FREEDOM CONTROLLERS THESIS Presented to the Faculty of the Graduate...measurement noises compared to the I- DOF model. xvii OPTIMAL CONTROL DESIGN ADVANTAGES UTILIZING TWO-DEGREE-OF-FREEDOM CONTROLLERS I. Introduction L1

Optimization of armored fighting vehicle crew performance in a net-centric battlefield

NASA Astrophysics Data System (ADS)

McKeen, William P.; Espenant, Mark

2002-08-01

Traditional display, control and situational awareness technologies may not allow the fighting vehicle commander to take full advantage of the rich data environment made available in the net-centric battle field of the future. Indeed, the sheer complexity and volume of available data, if not properly managed, may actually reduce crew performance by overloading or confusing the commander with irrelevant information. New techniques must be explored to understand how to present battlefield information and provide the commander with continuous high quality situational awareness without significant cognitive overhead. Control of the vehicle's many complex systems must also be addressed the entire Soldier Machine Interface must be optimized if we are to realize the potential performance improvements. Defence Research and Development Canada (DRDC) and General Dynamics Canada Ltd. have embarked on a joint program called Future Armoured Fighting Vehicle Systems Technology Demonstrator, to explore these issues. The project is based on man-in-the-loop experimentation using virtual reality technology on a six degree-of-freedom motion platform that simulates the motion, sights and sounds inside a future armoured vehicle. The vehicle commander is provided with a virtual reality vision system to view a simulated 360 degree multi-spectrum representation of the battlespace, thus providing enhanced situational awareness. Graphic overlays with decision aid information will be added to reduce cognitive loading. Experiments will be conducted to evaluate the effectiveness of virtual control systems. The simulations are carried out in a virtual battlefield created by linking our simulation system with other simulation centers to provide a net-centric battlespace where enemy forces can be engaged in fire fights. Survivability and lethality will be measured in successive test sequences using real armoured fighting vehicle crews to optimize overall system effectiveness.

Optimizing Glycemic Control Through Titration of Insulin Glargine 100 U/mL: A Review of Current and Future Approaches with a Focus on Asian Populations.

PubMed

Deerochanawong, Chaicharn; Bajpai, Shailendra; Dwipayana, I Made Pande; Hussein, Zanariah; Mabunay, Maria Aileen; Rosales, Reynaldo; Tsai, Shih-Tzer; Tsang, Man Wo

2017-12-01

Various data have demonstrated inadequate glycemic control amongst Asians with type 2 diabetes mellitus (T2DM), possibly on account of suboptimal titration of basal insulin-an issue which needs to be further examined. Here we review the available global and Asia-specific data on titration of basal insulin, with a focus on the use of insulin glargine 100 U/mL (Gla-100). We also discuss clinical evidence on the efficacy and safety of titrating Gla-100, different approaches to titration, including some of the latest technological advancements, and guidance on the titration of basal insulin from international and local Asian guidelines. The authors also provide their recommendations for the initiation and titration of basal insulin for Asian populations. Discussion of the data included in this review and in relation to the authors' clinical experience with treating T2DM in Asian patients is also included. Briefly, clinical studies demonstrate the achievement of adequate glycemic control in adults with T2DM through titration of Gla-100. However, studies investigating approaches to titration, specifically in Asian populations, are lacking and need to be conducted. Given that the management of insulin therapy is a multidisciplinary team effort involving endocrinologists, primary care physicians, nurse educators, and patients, greater resources and education targeted at these groups are needed regarding the optimal titration of basal insulin. Technological advancements in the form of mobile or web-based applications for automated dose adjustment can aid different stakeholders in optimizing the dose of basal insulin, enabling a larger number of patients in Asia to reach their target glycemic goals with improved outcomes.

Contingency planning for a deliberate release of smallpox in Great Britain--the role of geographical scale and contact structure.

PubMed

House, Thomas; Hall, Ian; Danon, Leon; Keeling, Matt J

2010-02-14

In the event of a release of a pathogen such as smallpox, which is human-to-human transmissible and has high associated mortality, a key question is how best to deploy containment and control strategies. Given the general uncertainty surrounding this issue, mathematical modelling has played an important role in informing the likely optimal response, in particular defining the conditions under which mass-vaccination would be appropriate. In this paper, we consider two key questions currently unanswered in the literature: firstly, what is the optimal spatial scale for intervention; and secondly, how sensitive are results to the modelling assumptions made about the pattern of human contacts? Here we develop a novel mathematical model for smallpox that incorporates both information on individual contact structure (which is important if the effects of contact tracing are to be captured accurately) and large-scale patterns of movement across a range of spatial scales in Great Britain. Analysis of this model confirms previous work suggesting that a locally targeted 'ring' vaccination strategy is optimal, and that this conclusion is actually quite robust for different socio-demographic and epidemiological assumptions. Our method allows for intuitive understanding of the reasons why national mass vaccination is typically predicted to be suboptimal. As such, we present a general framework for fast calculation of expected outcomes during the attempted control of diverse emerging infections; this is particularly important given that parameters would need to be interactively estimated and modelled in any release scenario.

Traffic Management for Satellite-ATM Networks

NASA Technical Reports Server (NTRS)

Goyal, Rohit; Jain, Raj; Fahmy, Sonia; Vandalore, Bobby; Goyal, Mukul

1998-01-01

Various issues associated with "Traffic Management for Satellite-ATM Networks" are presented in viewgraph form. Specific topics include: 1) Traffic management issues for TCP/IP based data services over satellite-ATM networks; 2) Design issues for TCP/IP over ATM; 3) Optimization of the performance of TCP/IP over ATM for long delay networks; and 4) Evaluation of ATM service categories for TCP/IP traffic.

Control and optimization system

DOEpatents

Xinsheng, Lou

2013-02-12

A system for optimizing a power plant includes a chemical loop having an input for receiving an input parameter (270) and an output for outputting an output parameter (280), a control system operably connected to the chemical loop and having a multiple controller part (230) comprising a model-free controller. The control system receives the output parameter (280), optimizes the input parameter (270) based on the received output parameter (280), and outputs an optimized input parameter (270) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.

Gene-environment interactions and construct validity in preclinical models of psychiatric disorders.

PubMed

Burrows, Emma L; McOmish, Caitlin E; Hannan, Anthony J

2011-08-01

The contributions of genetic risk factors to susceptibility for brain disorders are often so closely intertwined with environmental factors that studying genes in isolation cannot provide the full picture of pathogenesis. With recent advances in our understanding of psychiatric genetics and environmental modifiers we are now in a position to develop more accurate animal models of psychiatric disorders which exemplify the complex interaction of genes and environment. Here, we consider some of the insights that have emerged from studying the relationship between defined genetic alterations and environmental factors in rodent models. A key issue in such animal models is the optimization of construct validity, at both genetic and environmental levels. Standard housing of laboratory mice and rats generally includes ad libitum food access and limited opportunity for physical exercise, leading to metabolic dysfunction under control conditions, and thus reducing validity of animal models with respect to clinical populations. A related issue, of specific relevance to neuroscientists, is that most standard-housed rodents have limited opportunity for sensory and cognitive stimulation, which in turn provides reduced incentive for complex motor activity. Decades of research using environmental enrichment has demonstrated beneficial effects on brain and behavior in both wild-type and genetically modified rodent models, relative to standard-housed littermate controls. One interpretation of such studies is that environmentally enriched animals more closely approximate average human levels of cognitive and sensorimotor stimulation, whereas the standard housing currently used in most laboratories models a more sedentary state of reduced mental and physical activity and abnormal stress levels. The use of such standard housing as a single environmental variable may limit the capacity for preclinical models to translate into successful clinical trials. Therefore, there is a need to optimize 'environmental construct validity' in animal models, while maintaining comparability between laboratories, so as to ensure optimal scientific and medical outcomes. Utilizing more sophisticated models to elucidate the relative contributions of genetic and environmental factors will allow for improved construct, face and predictive validity, thus facilitating the identification of novel therapeutic targets. Copyright © 2010 Elsevier Inc. All rights reserved.

Frontiers in Distributed Optimization and Control of Sustainable Power

Science.gov Websites

Optimization and Control of Sustainable Power Systems Workshop Frontiers in Distributed Optimization and Control of Sustainable Power Systems Workshop In January 2016, NREL's energy systems integration team hosted a workshop on frontiers in distributed optimization and control of sustainable power systems. The

Coordinated control of active and reactive power of distribution network with distributed PV cluster via model predictive control

NASA Astrophysics Data System (ADS)

Ji, Yu; Sheng, Wanxing; Jin, Wei; Wu, Ming; Liu, Haitao; Chen, Feng

2018-02-01

A coordinated optimal control method of active and reactive power of distribution network with distributed PV cluster based on model predictive control is proposed in this paper. The method divides the control process into long-time scale optimal control and short-time scale optimal control with multi-step optimization. The models are transformed into a second-order cone programming problem due to the non-convex and nonlinear of the optimal models which are hard to be solved. An improved IEEE 33-bus distribution network system is used to analyse the feasibility and the effectiveness of the proposed control method

Methodological issues in negative symptom trials.

PubMed

Marder, Stephen R; Daniel, David G; Alphs, Larry; Awad, A George; Keefe, Richard S E

2011-03-01

Individuals from academia, the pharmaceutical industry, and the US Food and Drug Administration used a workshop format to discuss important methodological issues in the design of trials of pharmacological agents for improving negative symptoms in schizophrenia. The issues addressed included the need for a coprimary functional measure for registration trials; the characteristics of individuals who should enter negative symptom trials; the optimal duration for a proof-of-concept or registration trial; the optimal design of a study of a broad-spectrum agent that treats both positive and negative symptoms or a co-medication that is added to an antipsychotic; the relative strengths and weaknesses of available instruments for measuring negative symptoms; the definition of clinically meaningful improvement for these trials; and whether drugs can be approved for a subdomain of negative symptoms.

Methodological Issues in Negative Symptom Trials

PubMed Central

Marder, Stephen R.; Daniel, David G.; Alphs, Larry; Awad, A. George; Keefe, Richard S. E.

2011-01-01

Individuals from academia, the pharmaceutical industry, and the US Food and Drug Administration used a workshop format to discuss important methodological issues in the design of trials of pharmacological agents for improving negative symptoms in schizophrenia. The issues addressed included the need for a coprimary functional measure for registration trials; the characteristics of individuals who should enter negative symptom trials; the optimal duration for a proof-of-concept or registration trial; the optimal design of a study of a broad-spectrum agent that treats both positive and negative symptoms or a co-medication that is added to an antipsychotic; the relative strengths and weaknesses of available instruments for measuring negative symptoms; the definition of clinically meaningful improvement for these trials; and whether drugs can be approved for a subdomain of negative symptoms. PMID:21270473

An optimal merging technique for high-resolution precipitation products: OPTIMAL MERGING OF PRECIPITATION METHOD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shrestha, Roshan; Houser, Paul R.; Anantharaj, Valentine G.

2011-04-01

Precipitation products are currently available from various sources at higher spatial and temporal resolution than any time in the past. Each of the precipitation products has its strengths and weaknesses in availability, accuracy, resolution, retrieval techniques and quality control. By merging the precipitation data obtained from multiple sources, one can improve its information content by minimizing these issues. However, precipitation data merging poses challenges of scale-mismatch, and accurate error and bias assessment. In this paper we present Optimal Merging of Precipitation (OMP), a new method to merge precipitation data from multiple sources that are of different spatial and temporal resolutionsmore » and accuracies. This method is a combination of scale conversion and merging weight optimization, involving performance-tracing based on Bayesian statistics and trend-analysis, which yields merging weights for each precipitation data source. The weights are optimized at multiple scales to facilitate multiscale merging and better precipitation downscaling. Precipitation data used in the experiment include products from the 12-km resolution North American Land Data Assimilation (NLDAS) system, the 8-km resolution CMORPH and the 4-km resolution National Stage-IV QPE. The test cases demonstrate that the OMP method is capable of identifying a better data source and allocating a higher priority for them in the merging procedure, dynamically over the region and time period. This method is also effective in filtering out poor quality data introduced into the merging process.« less

Fuzzy Adaptive Decentralized Optimal Control for Strict Feedback Nonlinear Large-Scale Systems.

PubMed

Sun, Kangkang; Sui, Shuai; Tong, Shaocheng

2018-04-01

This paper considers the optimal decentralized fuzzy adaptive control design problem for a class of interconnected large-scale nonlinear systems in strict feedback form and with unknown nonlinear functions. The fuzzy logic systems are introduced to learn the unknown dynamics and cost functions, respectively, and a state estimator is developed. By applying the state estimator and the backstepping recursive design algorithm, a decentralized feedforward controller is established. By using the backstepping decentralized feedforward control scheme, the considered interconnected large-scale nonlinear system in strict feedback form is changed into an equivalent affine large-scale nonlinear system. Subsequently, an optimal decentralized fuzzy adaptive control scheme is constructed. The whole optimal decentralized fuzzy adaptive controller is composed of a decentralized feedforward control and an optimal decentralized control. It is proved that the developed optimal decentralized controller can ensure that all the variables of the control system are uniformly ultimately bounded, and the cost functions are the smallest. Two simulation examples are provided to illustrate the validity of the developed optimal decentralized fuzzy adaptive control scheme.

Feedback Implementation of Zermelo's Optimal Control by Sugeno Approximation

NASA Technical Reports Server (NTRS)

Clifton, C.; Homaifax, A.; Bikdash, M.

1997-01-01

This paper proposes an approach to implement optimal control laws of nonlinear systems in real time. Our methodology does not require solving two-point boundary value problems online and may not require it off-line either. The optimal control law is learned using the original Sugeno controller (OSC) from a family of optimal trajectories. We compare the trajectories generated by the OSC and the trajectories yielded by the optimal feedback control law when applied to Zermelo's ship steering problem.

Discrete-time Markovian-jump linear quadratic optimal control

NASA Technical Reports Server (NTRS)

Chizeck, H. J.; Willsky, A. S.; Castanon, D.

1986-01-01

This paper is concerned with the optimal control of discrete-time linear systems that possess randomly jumping parameters described by finite-state Markov processes. For problems having quadratic costs and perfect observations, the optimal control laws and expected costs-to-go can be precomputed from a set of coupled Riccati-like matrix difference equations. Necessary and sufficient conditions are derived for the existence of optimal constant control laws which stabilize the controlled system as the time horizon becomes infinite, with finite optimal expected cost.

Optimal robust control strategy of a solid oxide fuel cell system

NASA Astrophysics Data System (ADS)

Wu, Xiaojuan; Gao, Danhui

2018-01-01

Optimal control can ensure system safe operation with a high efficiency. However, only a few papers discuss optimal control strategies for solid oxide fuel cell (SOFC) systems. Moreover, the existed methods ignore the impact of parameter uncertainty on system instantaneous performance. In real SOFC systems, several parameters may vary with the variation of operation conditions and can not be identified exactly, such as load current. Therefore, a robust optimal control strategy is proposed, which involves three parts: a SOFC model with parameter uncertainty, a robust optimizer and robust controllers. During the model building process, boundaries of the uncertain parameter are extracted based on Monte Carlo algorithm. To achieve the maximum efficiency, a two-space particle swarm optimization approach is employed to obtain optimal operating points, which are used as the set points of the controllers. To ensure the SOFC safe operation, two feed-forward controllers and a higher-order robust sliding mode controller are presented to control fuel utilization ratio, air excess ratio and stack temperature afterwards. The results show the proposed optimal robust control method can maintain the SOFC system safe operation with a maximum efficiency under load and uncertainty variations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaitsgory, Vladimir, E-mail: vladimir.gaitsgory@mq.edu.au; Rossomakhine, Sergey, E-mail: serguei.rossomakhine@flinders.edu.au

The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite time horizon. We mostly focus on problems with time discounting criteria but a possibility of the extension of results to periodic optimization problems is discussed as well. Our consideration is based on earlier results on averaging of SP control systems and on linear programming formulations of optimal control problems. The idea that we exploit is to first asymptotically approximate a given problem ofmore » optimal control of the SP system by a certain averaged optimal control problem, then reformulate this averaged problem as an infinite-dimensional linear programming (LP) problem, and then approximate the latter by semi-infinite LP problems. We show that the optimal solution of these semi-infinite LP problems and their duals (that can be found with the help of a modification of an available LP software) allow one to construct near optimal controls of the SP system. We demonstrate the construction with two numerical examples.« less

Inhalation devices: from basic science to practical use, innovative vs generic products.

PubMed

Pirozynski, Michal; Sosnowski, Tomasz R

2016-11-01

Inhalation therapy is a convenient method of treating respiratory diseases. The key factors required for inhalation are the preparation of drug carriers (aerosol particles) allowing reproducible dosing during administration. These technical challenges are accomplished with a variety of inhalation devices (inhalers) and medicinal formulations, which are optimized to be easily converted into inhalable aerosols. Areas covered: This review is focused on the most important, but often overlooked, effects, which are required for the reliable and reproducible inhalable drug administration. The effects of patient-related issues that influence inhalation therapy, such as proper selection of inhalers for specific cases is discussed. We also discuss factors that are the most essential if generic inhalation product should be considered equivalent to the drugs with the clinically confirmed efficacy. Expert opinion: Proper device selection is crucial in clinical results of inhalation therapy. The patients' ability to coordinate inhalation with actuation, generation of optimal flow through the device, use of optimal inspiratory volume, all produces crucial effects on disease control. Also the severity of the disease process effects proper use of inhalers. Interchanging of inhalers can produce potentially conflicting problem regarding efficacy and safety of inhalation therapy.

Identification of optimal feedback control rules from micro-quadrotor and insect flight trajectories.

PubMed

Faruque, Imraan A; Muijres, Florian T; Macfarlane, Kenneth M; Kehlenbeck, Andrew; Humbert, J Sean

2018-06-01

This paper presents "optimal identification," a framework for using experimental data to identify the optimality conditions associated with the feedback control law implemented in the measurements. The technique compares closed loop trajectory measurements against a reduced order model of the open loop dynamics, and uses linear matrix inequalities to solve an inverse optimal control problem as a convex optimization that estimates the controller optimality conditions. In this study, the optimal identification technique is applied to two examples, that of a millimeter-scale micro-quadrotor with an engineered controller on board, and the example of a population of freely flying Drosophila hydei maneuvering about forward flight. The micro-quadrotor results show that the performance indices used to design an optimal flight control law for a micro-quadrotor may be recovered from the closed loop simulated flight trajectories, and the Drosophila results indicate that the combined effect of the insect longitudinal flight control sensing and feedback acts principally to regulate pitch rate.

Design and implementation of digital controllers for smart structures using field-programmable gate arrays

NASA Astrophysics Data System (ADS)

Kelly, Jamie S.; Bowman, Hiroshi C.; Rao, Vittal S.; Pottinger, Hardy J.

1997-06-01

Implementation issues represent an unfamiliar challenge to most control engineers, and many techniques for controller design ignore these issues outright. Consequently, the design of controllers for smart structural systems usually proceeds without regard for their eventual implementation, thus resulting either in serious performance degradation or in hardware requirements that squander power, complicate integration, and drive up cost. The level of integration assumed by the Smart Patch further exacerbates these difficulties, and any design inefficiency may render the realization of a single-package sensor-controller-actuator system infeasible. The goal of this research is to automate the controller implementation process and to relieve the design engineer of implementation concerns like quantization, computational efficiency, and device selection. We specifically target Field Programmable Gate Arrays (FPGAs) as our hardware platform because these devices are highly flexible, power efficient, and reprogrammable. The current study develops an automated implementation sequence that minimizes hardware requirements while maintaining controller performance. Beginning with a state space representation of the controller, the sequence automatically generates a configuration bitstream for a suitable FPGA implementation. MATLAB functions optimize and simulate the control algorithm before translating it into the VHSIC hardware description language. These functions improve power efficiency and simplify integration in the final implementation by performing a linear transformation that renders the controller computationally friendly. The transformation favors sparse matrices in order to reduce multiply operations and the hardware necessary to support them; simultaneously, the remaining matrix elements take on values that minimize limit cycles and parameter sensitivity. The proposed controller design methodology is implemented on a simple cantilever beam test structure using FPGA hardware. The experimental closed loop response is compared with that of an automated FPGA controller implementation. Finally, we explore the integration of FPGA based controllers into a multi-chip module, which we believe represents the next step towards the realization of the Smart Patch.

Thruster Limitation Consideration for Formation Flight Control

NASA Technical Reports Server (NTRS)

Xu, Yunjun; Fitz-Coy, Norman; Mason, Paul

2003-01-01

Physical constraints of any real system can have a drastic effect on its performance. Some of the more recognized constraints are actuator and sensor saturation and bandwidth, power consumption, sampling rate (sensor and control-loop) and computation limits. These constraints can degrade system s performance, such as settling time, overshoot, rising time, and stability margins. In order to address these issues, researchers have investigated the use of robust and nonlinear controllers that can incorporate uncertainty and constraints into a controller design. For instance, uncertainties can be addressed in the synthesis model used in such algorithms as H(sub infinity), or mu. There is a significant amount of literature addressing this type of problem. However, there is one constraint that has not often been considered; that is, actuator authority resolution. In this work, thruster resolution and controller schemes to compensate for this effect are investigated for position and attitude control of a Low Earth Orbit formation flight system In many academic problems, actuators are assumed to have infinite resolution. In real system applications, such as formation flight systems, the system actuators will not have infinite resolution. High-precision formation flying requires the relative position and the relative attitude to be controlled on the order of millimeters and arc-seconds, respectively. Therefore, the minimum force resolution is a significant concern in this application. Without the sufficient actuator resolution, the system may be unable to attain the required pointing and position precision control. Furthermore, fuel may be wasted due to high-frequency chattering phenomena when attempting to provide a fine control with inadequate actuators. To address this issue, a Sliding Mode Controller is developed along with the boundary Layer Control to provide the best control resolution constraints. A Genetic algorithm is used to optimize the controller parameters according to the states error and fuel consumption criterion. The tradeoffs and effects of the minimum force limitation on performance are studied and compared to the case without the limitation. Furthermore, two methods are proposed to reduce chattering and improve precision.

Optimal control of nonlinear continuous-time systems in strict-feedback form.

PubMed

Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani

2015-10-01

This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.

Warpage investigation on side arms using response surface methodology (RSM) and glow-worm swarm optimizations (GSO)

NASA Astrophysics Data System (ADS)

Sow, C. K.; Fathullah, M.; Nasir, S. M.; Shayfull, Z.; Shazzuan, S.

2017-09-01

This paper discusses on an analysis run via injection moulding process in determination of the optimum processing parameters used for manufacturing side arms of catheters in minimizing the warpage issues. The optimization method used was RSM. Moreover, in this research tries to find the most significant factor affecting the warpage. From the previous literature review,4 most significant parameters on warpage defect was selected. Those parameters were melt temperature, packing time, packing pressure, mould temperature and cooling time. At the beginning, side arm was drawn using software of CATIA V5. Then, software Mouldflow and Design Expert were employed to analyses on the popular warpage issues. After that, GSO artificial intelligence was apply using the mathematical model from Design Expert for more optimization on RSM result. Recommended parameter settings from the simulation work were then compared with the optimization work of RSM and GSO. The result show that the warpage on the side arm was improved by 3.27 %

Multi-input multioutput orthogonal frequency division multiplexing radar waveform design for improving the detection performance of space-time adaptive processing

NASA Astrophysics Data System (ADS)

Wang, Hongyan

2017-04-01

This paper addresses the waveform optimization problem for improving the detection performance of multi-input multioutput (MIMO) orthogonal frequency division multiplexing (OFDM) radar-based space-time adaptive processing (STAP) in the complex environment. By maximizing the output signal-to-interference-and-noise-ratio (SINR) criterion, the waveform optimization problem for improving the detection performance of STAP, which is subjected to the constant modulus constraint, is derived. To tackle the resultant nonlinear and complicated optimization issue, a diagonal loading-based method is proposed to reformulate the issue as a semidefinite programming one; thereby, this problem can be solved very efficiently. In what follows, the optimized waveform can be obtained to maximize the output SINR of MIMO-OFDM such that the detection performance of STAP can be improved. The simulation results show that the proposed method can improve the output SINR detection performance considerably as compared with that of uncorrelated waveforms and the existing MIMO-based STAP method.

On the theory of singular optimal controls in dynamic systems with control delay

NASA Astrophysics Data System (ADS)

Mardanov, M. J.; Melikov, T. K.

2017-05-01

An optimal control problem with a control delay is considered, and a more broad class of singular (in classical sense) controls is investigated. Various sequences of necessary conditions for the optimality of singular controls in recurrent form are obtained. These optimality conditions include analogues of the Kelley, Kopp-Moyer, R. Gabasov, and equality-type conditions. In the proof of the main results, the variation of the control is defined using Legendre polynomials.

Performance and robustness of optimal fractional fuzzy PID controllers for pitch control of a wind turbine using chaotic optimization algorithms.

PubMed

Asgharnia, Amirhossein; Shahnazi, Reza; Jamali, Ali

2018-05-11

The most studied controller for pitch control of wind turbines is proportional-integral-derivative (PID) controller. However, due to uncertainties in wind turbine modeling and wind speed profiles, the need for more effective controllers is inevitable. On the other hand, the parameters of PID controller usually are unknown and should be selected by the designer which is neither a straightforward task nor optimal. To cope with these drawbacks, in this paper, two advanced controllers called fuzzy PID (FPID) and fractional-order fuzzy PID (FOFPID) are proposed to improve the pitch control performance. Meanwhile, to find the parameters of the controllers the chaotic evolutionary optimization methods are used. Using evolutionary optimization methods not only gives us the unknown parameters of the controllers but also guarantees the optimality based on the chosen objective function. To improve the performance of the evolutionary algorithms chaotic maps are used. All the optimization procedures are applied to the 2-mass model of 5-MW wind turbine model. The proposed optimal controllers are validated using simulator FAST developed by NREL. Simulation results demonstrate that the FOFPID controller can reach to better performance and robustness while guaranteeing fewer fatigue damages in different wind speeds in comparison to FPID, fractional-order PID (FOPID) and gain-scheduling PID (GSPID) controllers. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal second order sliding mode control for nonlinear uncertain systems.

PubMed

Das, Madhulika; Mahanta, Chitralekha

2014-07-01

In this paper, a chattering free optimal second order sliding mode control (OSOSMC) method is proposed to stabilize nonlinear systems affected by uncertainties. The nonlinear optimal control strategy is based on the control Lyapunov function (CLF). For ensuring robustness of the optimal controller in the presence of parametric uncertainty and external disturbances, a sliding mode control scheme is realized by combining an integral and a terminal sliding surface. The resulting second order sliding mode can effectively reduce chattering in the control input. Simulation results confirm the supremacy of the proposed optimal second order sliding mode control over some existing sliding mode controllers in controlling nonlinear systems affected by uncertainty. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

SCARLET: Design of the Fresnel concentrator array for New Millennium Deep Space 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murphy, D.M.; Eskenazi, M.I.

1997-12-31

The primary power for the JPL New Millennium Deep Space 1 spacecraft is a 2.6 kW concentrator solar array. This paper surveys the design and analysis employed to combine line-focus Fresnel lenses and multijunction (GaInP{sub 2}/GaAs/Ge) solar cells in the second-generation SCARLET (Solar Concentrator Array with Refractive Linear Element Technology) system. The array structure and mechanisms are reviewed. Discussion is focused on the lens and receiver, from the optimizations of optical efficiency and thermal management, to the design issues of environmental extremes, reliability, producibility, and control of pointing error.

Structural dynamics analysis

NASA Technical Reports Server (NTRS)

Housner, J. M.; Anderson, M.; Belvin, W.; Horner, G.

1985-01-01

Dynamic analysis of large space antenna systems must treat the deployment as well as vibration and control of the deployed antenna. Candidate computer programs for deployment dynamics, and issues and needs for future program developments are reviewed. Some results for mast and hoop deployment are also presented. Modeling of complex antenna geometry with conventional finite element methods and with repetitive exact elements is considered. Analytical comparisons with experimental results for a 15 meter hoop/column antenna revealed the importance of accurate structural properties including nonlinear joints. Slackening of cables in this antenna is also a consideration. The technology of designing actively damped structures through analytical optimization is discussed and results are presented.

Multi-Objective Trajectory Optimization of a Hypersonic Reconnaissance Vehicle with Temperature Constraints

NASA Astrophysics Data System (ADS)

Masternak, Tadeusz J.

This research determines temperature-constrained optimal trajectories for a scramjet-based hypersonic reconnaissance vehicle by developing an optimal control formulation and solving it using a variable order Gauss-Radau quadrature collocation method with a Non-Linear Programming (NLP) solver. The vehicle is assumed to be an air-breathing reconnaissance aircraft that has specified takeoff/landing locations, airborne refueling constraints, specified no-fly zones, and specified targets for sensor data collections. A three degree of freedom scramjet aircraft model is adapted from previous work and includes flight dynamics, aerodynamics, and thermal constraints. Vehicle control is accomplished by controlling angle of attack, roll angle, and propellant mass flow rate. This model is incorporated into an optimal control formulation that includes constraints on both the vehicle and mission parameters, such as avoidance of no-fly zones and coverage of high-value targets. To solve the optimal control formulation, a MATLAB-based package called General Pseudospectral Optimal Control Software (GPOPS-II) is used, which transcribes continuous time optimal control problems into an NLP problem. In addition, since a mission profile can have varying vehicle dynamics and en-route imposed constraints, the optimal control problem formulation can be broken up into several "phases" with differing dynamics and/or varying initial/final constraints. Optimal trajectories are developed using several different performance costs in the optimal control formulation: minimum time, minimum time with control penalties, and maximum range. The resulting analysis demonstrates that optimal trajectories that meet specified mission parameters and constraints can be quickly determined and used for larger-scale operational and campaign planning and execution.

Singular-Arc Time-Optimal Trajectory of Aircraft in Two-Dimensional Wind Field

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2006-01-01

This paper presents a study of a minimum time-to-climb trajectory analysis for aircraft flying in a two-dimensional altitude dependent wind field. The time optimal control problem possesses a singular control structure when the lift coefficient is taken as a control variable. A singular arc analysis is performed to obtain an optimal control solution on the singular arc. Using a time-scale separation with the flight path angle treated as a fast state, the dimensionality of the optimal control solution is reduced by eliminating the lift coefficient control. A further singular arc analysis is used to decompose the original optimal control solution into the flight path angle solution and a trajectory solution as a function of the airspeed and altitude. The optimal control solutions for the initial and final climb segments are computed using a shooting method with known starting values on the singular arc The numerical results of the shooting method show that the optimal flight path angle on the initial and final climb segments are constant. The analytical approach provides a rapid means for analyzing a time optimal trajectory for aircraft performance.

Thermal energy effects on articular cartilage: a multidisciplinary evaluation

NASA Astrophysics Data System (ADS)

Kaplan, Lee D.; Ernsthausen, John; Ionescu, Dan S.; Studer, Rebecca K.; Bradley, James P.; Chu, Constance R.; Fu, Freddie H.; Farkas, Daniel L.

2002-05-01

Partial thickness articular cartilage lesions are commonly encountered in orthopedic surgery. These lesions do not have the ability to heal by themselves, due to lack of vascular supply. Several types of treatment have addressed this problem, including mechanical debridement and thermal chondroplasty. The goal of these treatments is to provide a smooth cartilage surface and prevent propagation of the lesions. Early thermal chondroplasty was performed using lasers, and yielded very mixed results, including severe damage to the cartilage, due to poor control of the induced thermal effects. This led to the development (including commercial) of probes using radiofrequency to generate the thermal effects desired for chondroplasty. Similar concerns over the quantitative aspects and control ability of the induced thermal effects in these treatments led us to test the whole range of complex issues and parameters involved. Our investigations are designed to simultaneously evaluate clinical conditions, instrument variables for existing radiofrequency probes (pressure, speed, distance, dose) as well as the associated basic science issues such as damage temperature and controllability (down to the subcellular level), damage geometry, and effects of surrounding conditions (medium, temperature, flow, pressure). The overall goals of this work are (1) to establish whether thermal chondroplasty can be used in a safe and efficacious manner, and (2) provide a prescription for multi-variable optimization of the way treatments are delivered, based on quantitative analysis. The methods used form an interdisciplinary set, to include precise mechanical actuation, high accuracy temperature and temperature gradient control and measurement, advanced imaging approaches and mathematical modeling.

Fuzzy logic control and optimization system

DOEpatents

Lou, Xinsheng [West Hartford, CT

2012-04-17

A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.

Examining the interaction between cognitive control and reward sensitivity in substance use dependence.

PubMed

Charles-Walsh, Kathleen; Upton, Daniel J; Hester, Robert

2016-09-01

Drug dependence is characterized by altered reward processing and poor cognitive control, expressed as a preference for immediate rewards and impaired inhibitory control, respectively. To examine the interaction between reward processing (via the presence or absence of reward) and mechanisms of inhibitory control in drug dependence, the current study used the Monetary Incentive Control Task (MICT) to examine whether a group of opiate dependent persons demonstrated greater difficulty exerting control over immediate rewards compared to neutral stimuli. The MICT is a Go/Stop paradigm that examines inhibitory control over immediate rewards. Performance of 32 opiate dependent individuals was compared to 29 healthy controls. Opiate users demonstrated poorer inhibitory performance than controls, irrespective of cues signaling immediate reward. Whereas control participants' responses were modulated by probability cues, the opiate group did not show a capacity to up-regulate their cognitive control performance. The present results suggest a general decrease in cognitive control in opiate dependence, accompanied by a reduced ability to optimally modulate behavior in accordance with external cues. Opiate users and controls did not differ in the interaction between cognitive control and reward. The study highlights important issues for future research to consider when further examining this interaction in drug dependence. Crown Copyright © 2016. Published by Elsevier Ireland Ltd. All rights reserved.

Optimal spacecraft attitude control using collocation and nonlinear programming

NASA Astrophysics Data System (ADS)

Herman, A. L.; Conway, B. A.

1992-10-01

Direct collocation with nonlinear programming (DCNLP) is employed to find the optimal open-loop control histories for detumbling a disabled satellite. The controls are torques and forces applied to the docking arm and joint and torques applied about the body axes of the OMV. Solutions are obtained for cases in which various constraints are placed on the controls and in which the number of controls is reduced or increased from that considered in Conway and Widhalm (1986). DCLNP works well when applied to the optimal control problem of satellite attitude control. The formulation is straightforward and produces good results in a relatively small amount of time on a Cray X/MP with no a priori information about the optimal solution. The addition of joint acceleration to the controls significantly reduces the control magnitudes and optimal cost. In all cases, the torques and acclerations are modest and the optimal cost is very modest.

Neural dynamic programming and its application to control systems

NASA Astrophysics Data System (ADS)

Seong, Chang-Yun

There are few general practical feedback control methods for nonlinear MIMO (multi-input-multi-output) systems, although such methods exist for their linear counterparts. Neural Dynamic Programming (NDP) is proposed as a practical design method of optimal feedback controllers for nonlinear MIMO systems. NDP is an offspring of both neural networks and optimal control theory. In optimal control theory, the optimal solution to any nonlinear MIMO control problem may be obtained from the Hamilton-Jacobi-Bellman equation (HJB) or the Euler-Lagrange equations (EL). The two sets of equations provide the same solution in different forms: EL leads to a sequence of optimal control vectors, called Feedforward Optimal Control (FOC); HJB yields a nonlinear optimal feedback controller, called Dynamic Programming (DP). DP produces an optimal solution that can reject disturbances and uncertainties as a result of feedback. Unfortunately, computation and storage requirements associated with DP solutions can be problematic, especially for high-order nonlinear systems. This dissertation presents an approximate technique for solving the DP problem based on neural network techniques that provides many of the performance benefits (e.g., optimality and feedback) of DP and benefits from the numerical properties of neural networks. We formulate neural networks to approximate optimal feedback solutions whose existence DP justifies. We show the conditions under which NDP closely approximates the optimal solution. Finally, we introduce the learning operator characterizing the learning process of the neural network in searching the optimal solution. The analysis of the learning operator provides not only a fundamental understanding of the learning process in neural networks but also useful guidelines for selecting the number of weights of the neural network. As a result, NDP finds---with a reasonable amount of computation and storage---the optimal feedback solutions to nonlinear MIMO control problems that would be very difficult to solve with DP. NDP was demonstrated on several applications such as the lateral autopilot logic for a Boeing 747, the minimum fuel control of a double-integrator plant with bounded control, the backward steering of a two-trailer truck, and the set-point control of a two-link robot arm.

Optimal control of thermally coupled Navier Stokes equations

NASA Technical Reports Server (NTRS)

Ito, Kazufumi; Scroggs, Jeffrey S.; Tran, Hien T.

1994-01-01

The optimal boundary temperature control of the stationary thermally coupled incompressible Navier-Stokes equation is considered. Well-posedness and existence of the optimal control and a necessary optimality condition are obtained. Optimization algorithms based on the augmented Lagrangian method with second order update are discussed. A test example motivated by control of transport process in the high pressure vapor transport (HVPT) reactor is presented to demonstrate the applicability of our theoretical results and proposed algorithm.

Integrated cable vibration control system using wireless sensors

NASA Astrophysics Data System (ADS)

Jeong, Seunghoo; Cho, Soojin; Sim, Sung-Han

2017-04-01

As the number of long-span bridges is increasing worldwide, maintaining their structural integrity and safety become an important issue. Because the stay cable is a critical member in most long-span bridges and vulnerable to wind-induced vibrations, vibration mitigation has been of interest both in academia and practice. While active and semi-active control schemes are known to be quite effective in vibration reduction compared to the passive control, requirements for equipment including data acquisition, control devices, and power supply prevent a widespread adoption in real-world applications. This study develops an integrated system for vibration control of stay-cables using wireless sensors implementing a semi-active control. Arduino, a low-cost single board system, is employed with a MEMS digital accelerometer and a Zigbee wireless communication module to build the wireless sensor. The magneto-rheological (MR) damper is selected as a damping device, controlled by an optimal control algorithm implemented on the Arduino sensing system. The developed integrated system is tested in a laboratory environment using a cable to demonstrate the effectiveness of the proposed system on vibration reduction. The proposed system is shown to reduce the vibration of stay-cables with low operating power effectively.

Load Frequency Control of AC Microgrid Interconnected Thermal Power System

NASA Astrophysics Data System (ADS)

Lal, Deepak Kumar; Barisal, Ajit Kumar

2017-08-01

In this paper, a microgrid (MG) power generation system is interconnected with a single area reheat thermal power system for load frequency control study. A new meta-heuristic optimization algorithm i.e. Moth-Flame Optimization (MFO) algorithm is applied to evaluate optimal gains of the fuzzy based proportional, integral and derivative (PID) controllers. The system dynamic performance is studied by comparing the results with MFO optimized classical PI/PID controllers. Also the system performance is investigated with fuzzy PID controller optimized by recently developed grey wolf optimizer (GWO) algorithm, which has proven its superiority over other previously developed algorithm in many interconnected power systems.

Minimal time spiking in various ChR2-controlled neuron models.

PubMed

Renault, Vincent; Thieullen, Michèle; Trélat, Emmanuel

2018-02-01

We use conductance based neuron models, and the mathematical modeling of optogenetics to define controlled neuron models and we address the minimal time control of these affine systems for the first spike from equilibrium. We apply tools of geometric optimal control theory to study singular extremals, and we implement a direct method to compute optimal controls. When the system is too large to theoretically investigate the existence of singular optimal controls, we observe numerically the optimal bang-bang controls.

A homotopy algorithm for digital optimal projection control GASD-HADOC

NASA Technical Reports Server (NTRS)

Collins, Emmanuel G., Jr.; Richter, Stephen; Davis, Lawrence D.

1993-01-01

The linear-quadratic-gaussian (LQG) compensator was developed to facilitate the design of control laws for multi-input, multi-output (MIMO) systems. The compensator is computed by solving two algebraic equations for which standard closed-loop solutions exist. Unfortunately, the minimal dimension of an LQG compensator is almost always equal to the dimension of the plant and can thus often violate practical implementation constraints on controller order. This deficiency is especially highlighted when considering control-design for high-order systems such as flexible space structures. This deficiency motivated the development of techniques that enable the design of optimal controllers whose dimension is less than that of the design plant. A homotopy approach based on the optimal projection equations that characterize the necessary conditions for optimal reduced-order control. Homotopy algorithms have global convergence properties and hence do not require that the initializing reduced-order controller be close to the optimal reduced-order controller to guarantee convergence. However, the homotopy algorithm previously developed for solving the optimal projection equations has sublinear convergence properties and the convergence slows at higher authority levels and may fail. A new homotopy algorithm for synthesizing optimal reduced-order controllers for discrete-time systems is described. Unlike the previous homotopy approach, the new algorithm is a gradient-based, parameter optimization formulation and was implemented in MATLAB. The results reported may offer the foundation for a reliable approach to optimal, reduced-order controller design.

Design of an Efficient CAC for a Broadband DVB-S/DVB-RCS Satellite Access Network

NASA Astrophysics Data System (ADS)

Inzerilli, Tiziano; Montozzi, Simone

2003-07-01

This paper deals with efficient utilization of network resources in an advanced broadband satellite access system. It proposes a technique for admission control of IP streams with guaranteed QoS which does not interfere with the particular BoD (Bandwidth on Demand) algorithm that handles access to uplink bandwidth, an essential part of a DVB- RCS architecture. This feature of the admission control greatly simplify its integration in the satellite network. The purpose of this admission control algorithm in particular is to suitably and dynamically configure the overall traffic control parameters, in the access terminal of the user and service segment, with a simple approach which does not introduces limitations and/or constraints to the BoD algorithm. Performance of the proposed algorithm is evaluated thorugh Opnet simulations using an ad-hoc platform modeling DVB-based satellite access.The results presented in this paper were obtained within SATIP6 project, which is sponsored within the 5th EU Research Programme, IST. The aims of the project are to evaluate and demonstrate key issues of the integration of satellite-based access networks into the Internet in order to support multimedia services over wide areas. The satellite link layer is based on DVB-S on the forward link and DVB-RCS on the return link. Adaptation and optimization of the DVB-RCS access standard in order to support QoS provision are central issues of the project. They are handled through an integration of Connection Admission Control (CAC), Traffic Shaping and Policing techniques.

Insight into efficient image registration techniques and the demons algorithm.

PubMed

Vercauteren, Tom; Pennec, Xavier; Malis, Ezio; Perchant, Aymeric; Ayache, Nicholas

2007-01-01

As image registration becomes more and more central to many biomedical imaging applications, the efficiency of the algorithms becomes a key issue. Image registration is classically performed by optimizing a similarity criterion over a given spatial transformation space. Even if this problem is considered as almost solved for linear registration, we show in this paper that some tools that have recently been developed in the field of vision-based robot control can outperform classical solutions. The adequacy of these tools for linear image registration leads us to revisit non-linear registration and allows us to provide interesting theoretical roots to the different variants of Thirion's demons algorithm. This analysis predicts a theoretical advantage to the symmetric forces variant of the demons algorithm. We show that, on controlled experiments, this advantage is confirmed, and yields a faster convergence.

New evidence favoring multilevel decomposition and optimization

NASA Technical Reports Server (NTRS)

Padula, Sharon L.; Polignone, Debra A.

1990-01-01

The issue of the utility of multilevel decomposition and optimization remains controversial. To date, only the structural optimization community has actively developed and promoted multilevel optimization techniques. However, even this community acknowledges that multilevel optimization is ideally suited for a rather limited set of problems. It is warned that decomposition typically requires eliminating local variables by using global variables and that this in turn causes ill-conditioning of the multilevel optimization by adding equality constraints. The purpose is to suggest a new multilevel optimization technique. This technique uses behavior variables, in addition to design variables and constraints, to decompose the problem. The new technique removes the need for equality constraints, simplifies the decomposition of the design problem, simplifies the programming task, and improves the convergence speed of multilevel optimization compared to conventional optimization.

Distributed control systems with incomplete and uncertain information

NASA Astrophysics Data System (ADS)

Tang, Jingpeng

Scientific and engineering advances in wireless communication, sensors, propulsion, and other areas are rapidly making it possible to develop unmanned air vehicles (UAVs) with sophisticated capabilities. UAVs have come to the forefront as tools for airborne reconnaissance to search for, detect, and destroy enemy targets in relatively complex environments. They potentially reduce risk to human life, are cost effective, and are superior to manned aircraft for certain types of missions. It is desirable for UAVs to have a high level of intelligent autonomy to carry out mission tasks with little external supervision and control. This raises important issues involving tradeoffs between centralized control and the associated potential to optimize mission plans, and decentralized control with great robustness and the potential to adapt to changing conditions. UAV capabilities have been extended several ways through armament (e.g., Hellfire missiles on Predator UAVs), increased endurance and altitude (e.g., Global Hawk), and greater autonomy. Some known barriers to full-scale implementation of UAVs are increased communication and control requirements as well as increased platform and system complexity. One of the key problems is how UAV systems can handle incomplete and uncertain information in dynamic environments. Especially when the system is composed of heterogeneous and distributed UAVs, the overall system complexity is increased under such conditions. Presented through the use of published papers, this dissertation lays the groundwork for the study of methodologies for handling incomplete and uncertain information for distributed control systems. An agent-based simulation framework is built to investigate mathematical approaches (optimization) and emergent intelligence approaches. The first paper provides a mathematical approach for systems of UAVs to handle incomplete and uncertain information. The second paper describes an emergent intelligence approach for UAVs, again in handling incomplete and uncertain information. The third paper combines mathematical and emergent intelligence approaches.

A multi-mode operation control strategy for flexible microgrid based on sliding-mode direct voltage and hierarchical controls.

PubMed

Zhang, Qinjin; Liu, Yancheng; Zhao, Youtao; Wang, Ning

2016-03-01

Multi-mode operation and transient stability are two problems that significantly affect flexible microgrid (MG). This paper proposes a multi-mode operation control strategy for flexible MG based on a three-layer hierarchical structure. The proposed structure is composed of autonomous, cooperative, and scheduling controllers. Autonomous controller is utilized to control the performance of the single micro-source inverter. An adaptive sliding-mode direct voltage loop and an improved droop power loop based on virtual negative impedance are presented respectively to enhance the system disturbance-rejection performance and the power sharing accuracy. Cooperative controller, which is composed of secondary voltage/frequency control and phase synchronization control, is designed to eliminate the voltage/frequency deviations produced by the autonomous controller and prepare for grid connection. Scheduling controller manages the power flow between the MG and the grid. The MG with the improved hierarchical control scheme can achieve seamless transitions from islanded to grid-connected mode and have a good transient performance. In addition the presented work can also optimize the power quality issues and improve the load power sharing accuracy between parallel VSIs. Finally, the transient performance and effectiveness of the proposed control scheme are evaluated by theoretical analysis and simulation results. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

On Maximizing the Lifetime of Wireless Sensor Networks by Optimally Assigning Energy Supplies

PubMed Central

Asorey-Cacheda, Rafael; García-Sánchez, Antonio Javier; García-Sánchez, Felipe; García-Haro, Joan; Gonzalez-Castaño, Francisco Javier

2013-01-01

The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes) carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes) are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment) to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively. PMID:23939582

A Machine-Learning and Filtering Based Data Assimilation Framework for Geologic Carbon Sequestration Monitoring Optimization

NASA Astrophysics Data System (ADS)

Chen, B.; Harp, D. R.; Lin, Y.; Keating, E. H.; Pawar, R.

2017-12-01

Monitoring is a crucial aspect of geologic carbon sequestration (GCS) risk management. It has gained importance as a means to ensure CO2 is safely and permanently stored underground throughout the lifecycle of a GCS project. Three issues are often involved in a monitoring project: (i) where is the optimal location to place the monitoring well(s), (ii) what type of data (pressure, rate and/or CO2 concentration) should be measured, and (iii) What is the optimal frequency to collect the data. In order to address these important issues, a filtering-based data assimilation procedure is developed to perform the monitoring optimization. The optimal monitoring strategy is selected based on the uncertainty reduction of the objective of interest (e.g., cumulative CO2 leak) for all potential monitoring strategies. To reduce the computational cost of the filtering-based data assimilation process, two machine-learning algorithms: Support Vector Regression (SVR) and Multivariate Adaptive Regression Splines (MARS) are used to develop the computationally efficient reduced-order-models (ROMs) from full numerical simulations of CO2 and brine flow. The proposed framework for GCS monitoring optimization is demonstrated with two examples: a simple 3D synthetic case and a real field case named Rock Spring Uplift carbon storage site in Southwestern Wyoming.

Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

PubMed Central

Morris, Melody K.; Saez-Rodriguez, Julio; Lauffenburger, Douglas A.; Alexopoulos, Leonidas G.

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms. PMID:23226239

On maximizing the lifetime of Wireless Sensor Networks by optimally assigning energy supplies.

PubMed

Asorey-Cacheda, Rafael; García-Sánchez, Antonio Javier; García-Sánchez, Felipe; García-Haro, Joan; González-Castano, Francisco Javier

2013-08-09

The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes) carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes) are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment) to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively.

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

PubMed

Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Towards Development of Microcalorimeter Arrays of Mo/Au Transition-Edge Sensors with Bismuth Absorbers

NASA Technical Reports Server (NTRS)

Tralshawala, Nilesh; Brekosky, Regis; Figueroa-Feliciano, Enectali; Li, Mary; Stahle, Carl; Stahle, Caroline

2000-01-01

We report on our progress towards the development of arrays of X-ray microcalorimeters as candidates for the high resolution x-ray spectrometer on the Constellation-X mission. The microcalorimeter arrays (30 x 30) with appropriate pixel sizes (0.25 mm. x 0.25 mm) and high packing fractions (greater than 96%) are being developed. Each individual pixel has a 10 micron thick Bi X-ray absorber that is shaped like a mushroom to increase the packing fraction, and a Mo/Au proximity effect superconducting transition edge sensor (TES). These are deposited on a 0.25 or 0.5 micron thick silicon nitride membrane with slits to provide a controllable weak thermal link to the sink temperature. Studies are underway to model, test and optimize the TES pixel uniformity, critical current, heat capacity and the membrane thermal conductance in the array structure. Fabrication issues and procedures, and results of our efforts based on these optimizations will be provided.

Optimization of detectors positioning with respect to flying dynamics for future formation flight missions

NASA Astrophysics Data System (ADS)

Civitani, Marta; Djalal, Sophie; Chipaux, Remi

2009-08-01

In a X-ray telescope in formation flight configuration, the optics and the focal-plane detectors reside in two different spacecraft. The dynamics of the detector spacecraft (DSC) with respect to the mirror spacecraft (MSC, carrying the mirrors of the telescope) changes continuously the arrival positions of the photons on the detectors. In this paper we analyze this issue for the case of the SIMBOL-X hard X-ray mission, extensively studied by CNES and ASI until 2009 spring. Due to the existing gaps between pixels and between detector modules, the dynamics of the system may produce a relevant photometric effect. The aim of this work is to present the optimization study of the control-law algorithm with respect to the detector's geometry. As the photometric effect may vary depending upon position of the source image on the detector, the analysis-carried out using the simuLOS (INAF, CNES, CEA) simulation tool-is extended over the entire SIMBOL-X field of view.

Application-Oriented Chemical Optimization of a Metakaolin Based Geopolymer.

PubMed

Ferone, Claudio; Colangelo, Francesco; Roviello, Giuseppina; Asprone, Domenico; Menna, Costantino; Balsamo, Alberto; Prota, Andrea; Cioffi, Raffaele; Manfredi, Gaetano

2013-05-10

In this study the development of a metakaolin based geopolymeric mortar to be used as bonding matrix for external strengthening of reinforced concrete beams is reported. Four geopolymer formulations have been obtained by varying the composition of the activating solution in terms of SiO₂/Na₂O ratio. The obtained samples have been characterized from a structural, microstructural and mechanical point of view. The differences in structure and microstructure have been correlated to the mechanical properties. A major issue of drying shrinkage has been encountered in the high Si/Al ratio samples. In the light of the characterization results, the optimal geopolymer composition was then applied to fasten steel fibers to reinforced concrete beams. The mechanical behavior of the strengthened reinforced beams was evaluated by four-points bending tests, which were performed also on reinforced concrete beams as they are for comparison. The preliminary results of the bending tests point out an excellent behavior of the geopolymeric mixture tested, with the failure load of the reinforced beams roughly twice that of the control beam.

Parallel Distributed Processing at 25: further explorations in the microstructure of cognition.

PubMed

Rogers, Timothy T; McClelland, James L

2014-08-01

This paper introduces a special issue of Cognitive Science initiated on the 25th anniversary of the publication of Parallel Distributed Processing (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary developments in learning, optimality theory, perception, memory, language, conceptual knowledge, cognitive control, and consciousness. Here we consider the approach more generally, reviewing the original motivations, the resulting framework, and the central tenets of the underlying theory. We then evaluate the impact of PDP both on the field at large and within specific subdomains of cognitive science and consider the current role of PDP models within the broader landscape of contemporary theoretical frameworks in cognitive science. Looking to the future, we consider the implications for cognitive science of the recent success of machine learning systems called "deep networks"-systems that build on key ideas presented in the PDP volumes. Copyright © 2014 Cognitive Science Society, Inc.

A systemic study on key parameters affecting nanocomposite coatings on magnesium substrates.

PubMed

Johnson, Ian; Wang, Sebo Michelle; Silken, Christine; Liu, Huinan

2016-05-01

Nanocomposite coatings offer multiple functions simultaneously to improve the interfacial properties of magnesium (Mg) alloys for skeletal implant applications, e.g., controlling the degradation rate of Mg substrates, improving bone cell functions, and providing drug delivery capability. However, the effective service time of nanocomposite coatings may be limited due to their early delamination from the Mg-based substrates. Therefore, the objective of this study was to address the delamination issue of nanocomposite coatings, improve the coating properties for reducing the degradation of Mg-based substrates, and thus improve their cytocompatibility with bone marrow derived mesenchymal stem cells (BMSCs). The surface conditions of the substrates, polymer component type of the nanocomposite coatings, and post-deposition processing are the key parameters that contribute to the efficacy of the nanocomposite coatings in regulating substrate degradation and bone cell responses. Specifically, the effects of metallic surface versus alkaline heat-treated hydroxide surface of the substrates on coating quality were investigated. For the nanocomposite coatings, nanophase hydroxyapatite (nHA) was dispersed in three types of biodegradable polymers, i.e., poly(lactic-co-glycolic acid) (PLGA), poly(l-lactic acid) (PLLA), or poly(caprolactone) (PCL) to determine which polymer component could provide integrated properties for slowest Mg degradation. The nanocomposite coatings with or without post-deposition processing, i.e., melting, annealing, were compared to determine which processing route improved the properties of the nanocomposite coatings most significantly. The results showed that optimizing the coating processes addressed the delamination issue. The melted then annealed nHA/PCL coating on the metallic Mg substrates showed the slowest degradation and the best coating adhesion, among all the combinations of conditions studied; and, it improved the adhesion density of BMSCs. This study elucidated the key parameters for optimizing nanocomposite coatings on Mg-based substrates for skeletal implant applications, and provided rational design guidelines for the nanocomposite coatings on Mg alloys for potential clinical translation of biodegradable Mg-based implants. This manuscript describes the systemic optimization of nanocomposite coatings to control the degradation and bioactivity of magnesium for skeletal implant applications. The key parameters influencing the integrity and functions of the nanocomposite coatings on magnesium were identified, guidelines for the optimization of the coatings were established, and the benefits of coating optimization were demonstrated through reduced magnesium degradation and increased bone marrow derived mesenchymal stem cell (BMSC) adhesion in vitro. The guidelines developed in this manuscript are valuable for the biometal field to improve the design of bioresorbable implants and devices, which will advance the clinical translation of magnesium-based implants. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Optimal coordination and control of posture and movements.

PubMed

Johansson, Rolf; Fransson, Per-Anders; Magnusson, Måns

2009-01-01

This paper presents a theoretical model of stability and coordination of posture and locomotion, together with algorithms for continuous-time quadratic optimization of motion control. Explicit solutions to the Hamilton-Jacobi equation for optimal control of rigid-body motion are obtained by solving an algebraic matrix equation. The stability is investigated with Lyapunov function theory and it is shown that global asymptotic stability holds. It is also shown how optimal control and adaptive control may act in concert in the case of unknown or uncertain system parameters. The solution describes motion strategies of minimum effort and variance. The proposed optimal control is formulated to be suitable as a posture and movement model for experimental validation and verification. The combination of adaptive and optimal control makes this algorithm a candidate for coordination and control of functional neuromuscular stimulation as well as of prostheses. Validation examples with experimental data are provided.

Ask the experts: the challenges and benefits of flow chemistry to optimize drug development.

PubMed

Anderson, Neal; Gernaey, Krist V; Jamison, Timothy F; Kircher, Manfred; Wiles, Charlotte; Leadbeater, Nicholas E; Sandford, Graham; Richardson, Paul

2012-09-01

Against a backdrop of a struggling economic and regulatory climate, pharmaceutical companies have recently been forced to develop new ways to provide more efficient technology to meet the demands of a competitive drug industry. This issue, coupled with an increase in patent legislation and a rising generics market, makes these themes common issues in the growth of drug development. As a consequence, the importance of process chemistry and scale-up has never been more under the spotlight. Future Medicinal Chemistry wishes to share the thoughts and opinions of a variety of experts from this field, discussing issues concerning the use of flow chemistry to optimize drug development, the potential regulatory and environmental challenges faced with this, and whether the academic and industrial sectors could benefit from a more harmonized system relevant to process chemistry.

Optimization of Thermal Object Nonlinear Control Systems by Energy Efficiency Criterion.

NASA Astrophysics Data System (ADS)

Velichkin, Vladimir A.; Zavyalov, Vladimir A.

2018-03-01

This article presents the results of thermal object functioning control analysis (heat exchanger, dryer, heat treatment chamber, etc.). The results were used to determine a mathematical model of the generalized thermal control object. The appropriate optimality criterion was chosen to make the control more energy-efficient. The mathematical programming task was formulated based on the chosen optimality criterion, control object mathematical model and technological constraints. The “maximum energy efficiency” criterion helped avoid solving a system of nonlinear differential equations and solve the formulated problem of mathematical programming in an analytical way. It should be noted that in the case under review the search for optimal control and optimal trajectory reduces to solving an algebraic system of equations. In addition, it is shown that the optimal trajectory does not depend on the dynamic characteristics of the control object.

On-Board Real-Time Optimization Control for Turbo-Fan Engine Life Extending

NASA Astrophysics Data System (ADS)

Zheng, Qiangang; Zhang, Haibo; Miao, Lizhen; Sun, Fengyong

2017-11-01

A real-time optimization control method is proposed to extend turbo-fan engine service life. This real-time optimization control is based on an on-board engine mode, which is devised by a MRR-LSSVR (multi-input multi-output recursive reduced least squares support vector regression method). To solve the optimization problem, a FSQP (feasible sequential quadratic programming) algorithm is utilized. The thermal mechanical fatigue is taken into account during the optimization process. Furthermore, to describe the engine life decaying, a thermal mechanical fatigue model of engine acceleration process is established. The optimization objective function not only contains the sub-item which can get fast response of the engine, but also concludes the sub-item of the total mechanical strain range which has positive relationship to engine fatigue life. Finally, the simulations of the conventional optimization control which just consider engine acceleration performance or the proposed optimization method have been conducted. The simulations demonstrate that the time of the two control methods from idle to 99.5 % of the maximum power are equal. However, the engine life using the proposed optimization method could be surprisingly increased by 36.17 % compared with that using conventional optimization control.

Maintenance and sustained use of insecticide-treated bednets and curtains three years after a controlled trial in western Kenya.

PubMed

Kachur, S P; Phillips-Howard, P A; Odhacha, A M; Ruebush, T K; Oloo, A J; Nahlen, B L

1999-11-01

In large experimental trials throughout Africa, insecticide-treated bednets and curtains have reduced child mortality in malaria-endemic communities by 15%-30%. While few questions remain about the efficacy of this intervention, operational issues around how to implement and sustain insecticide-treated materials (ITM) projects need attention. We revisited the site of a small-scale ITM intervention trial, 3 years after the project ended, to assess how local attitudes and practices had changed. Qualitative and quantitative methods, including 16 focus group discussions and a household survey (n = 60), were employed to assess use, maintenance, retreatment and perceptions of ITM and the insecticide in former study communities. Families that had been issued bednets were more likely to have kept and maintained them and valued bednets more highly than those who had been issued curtains. While most households retained their original bednets, none had treated them with insecticide since the intervention trial was completed 3 years earlier. Most of those who had been issued bednets repaired them, but none acquired new or replacement nets. In contrast, households that had been issued insecticide-treated curtains often removed them. Three (15%) of the households issued curtains had purchased one or more bednets since the study ended. In households where bednets had been issued, children 10 years of age and younger were a third as likely to sleep under a net as were adults (relative risk (RR) = 0. 32; 95% confidence interval (95%CI) = 0.19, 0.53). Understanding how and why optimal ITM use declined following this small-scale intervention trial can suggest measures that may improve the sustainability of current and future ITM efforts.

Interactive Implementation of the Optimal Systems Control Design Program (OPTSYSX) on the IBM 3033.

DTIC Science & Technology

1984-03-01

DAS A44 159 INTERACTIVE IMPLEMENTATION OF THE OPTIMAL SYSTEMS I CONTROL DESIGN PROGRAM (OPTSYSX) ON THE 1DM 3033(U NAVAL POSTGRADUATE SCHOOL MONTEREY...noesear end idswtif’r b block number) Optimal Systems Control Systems Control Control Systems 10.; ABSTRACT (Continu an reveree side ff Roe684v ad Id yI...34 by block number) .- This thesis discusses the modification of an existing Optimal Systems Control FORTRAN program (OPTSYS) originally obtained from

Ship Trim Optimization: Assessment of Influence of Trim on Resistance of MOERI Container Ship

PubMed Central

Duan, Wenyang

2014-01-01

Environmental issues and rising fuel prices necessitate better energy efficiency in all sectors. Shipping industry is a stakeholder in environmental issues. Shipping industry is responsible for approximately 3% of global CO2 emissions, 14-15% of global NOX emissions, and 16% of global SOX emissions. Ship trim optimization has gained enormous momentum in recent years being an effective operational measure for better energy efficiency to reduce emissions. Ship trim optimization analysis has traditionally been done through tow-tank testing for a specific hullform. Computational techniques are increasingly popular in ship hydrodynamics applications. The purpose of this study is to present MOERI container ship (KCS) hull trim optimization by employing computational methods. KCS hull total resistances and trim and sinkage computed values, in even keel condition, are compared with experimental values and found in reasonable agreement. The agreement validates that mesh, boundary conditions, and solution techniques are correct. The same mesh, boundary conditions, and solution techniques are used to obtain resistance values in different trim conditions at Fn = 0.2274. Based on attained results, optimum trim is suggested. This research serves as foundation for employing computational techniques for ship trim optimization. PMID:24578649

Assessment of short reports using a human rights-based approach to tobacco control to the Commitee on Economics, Cultural and Social Rights.

PubMed

Dresler, Carolyn; Henry, Kirsten; Loftus, John; Lando, Harry

2017-07-28

The health impact of tobacco use remains a major global public health concern and a human rights issue. The Human Rights and Tobacco Control Network (HRTCN) was established to increase the visibility of tobacco as a human rights issue. HRTCN submitted short reports to the UN Committee on Economic Social and Cultural Rights evaluating individual nations' tobacco control policies and offering recommendations. HRTCN reviewed Concluding Observations documents for nations for which the HRTCN submitted reports. If tobacco was mentioned in the Concluding Observations through acknowledging the Framework Convention on Tobacco Control ratification, policy changes or discussing tobacco in the recommendations, this was scored as a positive finding. HRTCN also reviewed Concluding Observations for nations for which HRTCN did not submit reports as a comparison. Thirty-eight HRTCN reports were submitted and tobacco was mentioned in Concluding Observations for 11 nations for a rate of 28.9%. In a comparison set of Concluding Observations (n=59), 7% had comments or recommendations relative to tobacco. This was not a controlled study and the 28.9% 'success rate' for impacting the Concluding Observations, although encouraging, is less than optimal-and leaves room for improvement. The higher rate of tobacco mentions for the cases where the HRTCN short reports were submitted provides preliminary indications that the short reports may have potential to increase the state focus on tobacco control. Future work will seek to improve the design and scope of the reports, and the specificity of the background information and recommendations offered. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Optimal Control for Quantum Driving of Two-Level Systems

NASA Astrophysics Data System (ADS)

Qi, Xiao-Qiu

2018-01-01

In this paper, the optimal quantum control of two-level systems is studied by the decompositions of SU(2). Using the Pontryagin maximum principle, the minimum time of quantum control is analyzed in detail. The solution scheme of the optimal control function is given in the general case. Finally, two specific cases, which can be applied in many quantum systems, are used to illustrate the scheme, while the corresponding optimal control functions are obtained.

Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure.

PubMed

Luo, Biao; Liu, Derong; Wu, Huai-Ning

2018-06-01

Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.

Mystic: Implementation of the Static Dynamic Optimal Control Algorithm for High-Fidelity, Low-Thrust Trajectory Design

NASA Technical Reports Server (NTRS)

Whiffen, Gregory J.

2006-01-01

Mystic software is designed to compute, analyze, and visualize optimal high-fidelity, low-thrust trajectories, The software can be used to analyze inter-planetary, planetocentric, and combination trajectories, Mystic also provides utilities to assist in the operation and navigation of low-thrust spacecraft. Mystic will be used to design and navigate the NASA's Dawn Discovery mission to orbit the two largest asteroids, The underlying optimization algorithm used in the Mystic software is called Static/Dynamic Optimal Control (SDC). SDC is a nonlinear optimal control method designed to optimize both 'static variables' (parameters) and dynamic variables (functions of time) simultaneously. SDC is a general nonlinear optimal control algorithm based on Bellman's principal.

Advanced integrated enhanced vision systems

NASA Astrophysics Data System (ADS)

Kerr, J. R.; Luk, Chiu H.; Hammerstrom, Dan; Pavel, Misha

2003-09-01

In anticipation of its ultimate role in transport, business and rotary wing aircraft, we clarify the role of Enhanced Vision Systems (EVS): how the output data will be utilized, appropriate architecture for total avionics integration, pilot and control interfaces, and operational utilization. Ground-map (database) correlation is critical, and we suggest that "synthetic vision" is simply a subset of the monitor/guidance interface issue. The core of integrated EVS is its sensor processor. In order to approximate optimal, Bayesian multi-sensor fusion and ground correlation functionality in real time, we are developing a neural net approach utilizing human visual pathway and self-organizing, associative-engine processing. In addition to EVS/SVS imagery, outputs will include sensor-based navigation and attitude signals as well as hazard detection. A system architecture is described, encompassing an all-weather sensor suite; advanced processing technology; intertial, GPS and other avionics inputs; and pilot and machine interfaces. Issues of total-system accuracy and integrity are addressed, as well as flight operational aspects relating to both civil certification and military applications in IMC.

Artificial Intelligence Based Control Power Optimization on Tailless Aircraft. [ARMD Seedling Fund Phase I

NASA Technical Reports Server (NTRS)

Gern, Frank; Vicroy, Dan D.; Mulani, Sameer B.; Chhabra, Rupanshi; Kapania, Rakesh K.; Schetz, Joseph A.; Brown, Derrell; Princen, Norman H.

2014-01-01

Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process.

Strategies for Voltage Control and Transient Stability Assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hiskens, Ian A.

As wind generation grows, its influence on power system performance will becoming increasingly noticeable. Wind generation di ffers from traditional forms of generation in numerous ways though, motivating the need to reconsider the usual approaches to power system assessment and performance enhancement. The project has investigated the impact of wind generation on transient stability and voltage control, identifying and addressing issues at three distinct levels of the power system: 1) at the device level, the physical characteristics of wind turbine generators (WTGs) are quite unlike those of synchronous machines, 2) at the wind-farm level, the provision of reactive support ismore » achieved through coordination of numerous dissimilar devices, rather than straightforward generator control, and 3) from a systems perspective, the location of wind-farms on the sub-transmission network, coupled with the variability inherent in their power output, can cause complex voltage control issues. The project has sought to develop a thorough understanding of the dynamic behaviour of type-3 WTGs, and in particular the WECC generic model. The behaviour of such models is governed by interactions between the continuous dynamics of state variables and discrete events associated with limits. It was shown that these interactions can be quite complex, and may lead to switching deadlock that prevents continuation of the trajectory. Switching hysteresis was proposed for eliminating deadlock situations. Various type-3 WTG models include control blocks that duplicate integrators. It was shown that this leads to non-uniqueness in the conditions governing steady-state, and may result in pre- and post-disturbance equilibria not coinciding. It also gives rise to a zero eigenvalue in the linearized WTG model. In order to eliminate the anomalous behaviour revealed through this investigation, WECC has now released a new generic model for type-3 WTGs. Wind-farms typically incorporate a variety of voltage control equipment including tapchanging transformers, switched capacitors, SVCs, STATCOMs and the WTGs themselves. The project has considered the coordinated control of this equipment, and has addressed a range of issues that arise in wind-farm operation. The first concerns the ability of WTGs to meet reactive power requirements when voltage saturation in the collector network restricts the reactive power availability of individual generators. Secondly, dynamic interactions between voltage regulating devices have been investigated. It was found that under certain realistic conditions, tap-changing transformers may exhibit instability. In order to meet cost, maintenance, fault tolerance and other requirements, it is desirable for voltage control equipment to be treated as an integrated system rather than as independent devices. The resulting high-level scheduling of wind-farm reactive support has been investigated. In addressing this control problem, several forms of future information were considered, including exact future knowledge and stochastic predictions. Deterministic and Stochastic Dynamic Programming techniques were used in the development of control algorithms. The results demonstrated that while exact future knowledge is very useful, simple prediction methods yield little bene fit. The integration of inherently variable wind generation into weak grids, particularly subtransmission networks that are characterized by low X=R ratios, aff ects bus voltages, regulating devices and line flows. The meshed structure of these networks adds to the complexity, especially when wind generation is distributed across multiple nodes. A range of techniques have been considered for analyzing the impact of wind variability on weak grids. Sensitivity analysis, based on the power-flow Jacobian, was used to highlight sections of a system that are most severely a ffected by wind-power variations. A continuation power flow was used to determine parameter changes that reduce the impact of wind-power variability. It was also used to explore interactions between multiple wind-farms. Furthermore, these tools have been used to examine the impact of wind injection on transformer tap operation in subtransmission networks. The results of a tap operation simulation study show that voltage regulation at wind injection nodes increases tap change operations. The tradeo ff between local voltage regulation and tap change frequency is fundamentally important in optimizing the size of reactive compensation used for voltage regulation at wind injection nodes. Line congestion arising as a consequence of variable patterns of wind-power production has also been investigated. Two optimization problems have been formulated, based respectively on the DC and AC power flow models, for identifying vulnerable line segments. The DC optimization is computationally more e fficient, whereas the AC sensitivity-based optimization provides greater accuracy.« less

A Particle Swarm Optimization Algorithm for Optimal Operating Parameters of VMI Systems in a Two-Echelon Supply Chain

NASA Astrophysics Data System (ADS)

Sue-Ann, Goh; Ponnambalam, S. G.

This paper focuses on the operational issues of a Two-echelon Single-Vendor-Multiple-Buyers Supply chain (TSVMBSC) under vendor managed inventory (VMI) mode of operation. To determine the optimal sales quantity for each buyer in TSVMBC, a mathematical model is formulated. Based on the optimal sales quantity can be obtained and the optimal sales price that will determine the optimal channel profit and contract price between the vendor and buyer. All this parameters depends upon the understanding of the revenue sharing between the vendor and buyers. A Particle Swarm Optimization (PSO) is proposed for this problem. Solutions obtained from PSO is compared with the best known results reported in literature.

A novel model of motor learning capable of developing an optimal movement control law online from scratch.

PubMed

Shimansky, Yury P; Kang, Tao; He, Jiping

2004-02-01

A computational model of a learning system (LS) is described that acquires knowledge and skill necessary for optimal control of a multisegmental limb dynamics (controlled object or CO), starting from "knowing" only the dimensionality of the object's state space. It is based on an optimal control problem setup different from that of reinforcement learning. The LS solves the optimal control problem online while practicing the manipulation of CO. The system's functional architecture comprises several adaptive components, each of which incorporates a number of mapping functions approximated based on artificial neural nets. Besides the internal model of the CO's dynamics and adaptive controller that computes the control law, the LS includes a new type of internal model, the minimal cost (IM(mc)) of moving the controlled object between a pair of states. That internal model appears critical for the LS's capacity to develop an optimal movement trajectory. The IM(mc) interacts with the adaptive controller in a cooperative manner. The controller provides an initial approximation of an optimal control action, which is further optimized in real time based on the IM(mc). The IM(mc) in turn provides information for updating the controller. The LS's performance was tested on the task of center-out reaching to eight randomly selected targets with a 2DOF limb model. The LS reached an optimal level of performance in a few tens of trials. It also quickly adapted to movement perturbations produced by two different types of external force field. The results suggest that the proposed design of a self-optimized control system can serve as a basis for the modeling of motor learning that includes the formation and adaptive modification of the plan of a goal-directed movement.

Analogue of the Kelley condition for optimal systems with retarded control

NASA Astrophysics Data System (ADS)

Mardanov, Misir J.; Melikov, Telman K.

2017-07-01

In this paper, we consider an optimal control problem with retarded control and study a larger class of singular (in the classical sense) controls. The Kelley and equality type optimality conditions are obtained. To prove our main results, we use the Legendre polynomials as variations of control.

Integrative energy-systems design: System structure from thermodynamic optimization

NASA Astrophysics Data System (ADS)

Ordonez, Juan Carlos

This thesis deals with the application of thermodynamic optimization to find optimal structure and operation conditions of energy systems. Chapter 1 outlines the thermodynamic optimization of a combined power and refrigeration system subject to constraints. It is shown that the thermodynamic optimum is reached by distributing optimally the heat exchanger inventory. Chapter 2 considers the maximization of power extraction from a hot stream in the presence of phase change. It shows that when the receiving (cold) stream boils in a counterflow heat exchanger, the thermodynamic optimization consists of locating the optimal capacity rate of the cold stream. Chapter 3 shows that the main architectural features of a counterflow heat exchanger can be determined based on thermodynamic optimization subject to volume constraint. Chapter 4 addresses two basic issues in the thermodynamic optimization of environmental control systems (ECS) for aircraft: realistic limits for the minimal power requirement, and design features that facilitate operation at minimal power consumption. Several models of the ECS-Cabin interaction are considered and it is shown that in all the models the temperature of the air stream that the ECS delivers to the cabin can be optimized for operation at minimal power. In chapter 5 it is shown that the sizes (weights) of heat and fluid flow systems that function on board vehicles such as aircraft can be derived from the maximization of overall (system level) performance. Chapter 6 develops analytically the optimal sizes (hydraulic diameters) of parallel channels that penetrate and cool a volume with uniformly distributed internal heat generation and Chapter 7 shows analytically and numerically how an originally uniform flow structure transforms itself into a nonuniform one when the objective is to minimize global flow losses. It is shown that flow maldistribution and the abandonment of symmetry are necessary for the development of flow structures with minimal resistance. In the second part of the chapter, the flow medium is continuous and permeated by Darcy flow. As flow systems become smaller and more compact, the flow systems themselves become "designed porous media".

Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2012-01-01

This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

Some optimal considerations in attitude control systems. [evaluation of value of relative weighting between time and fuel for relay control law

NASA Technical Reports Server (NTRS)

Boland, J. S., III

1973-01-01

The conventional six-engine reaction control jet relay attitude control law with deadband is shown to be a good linear approximation to a weighted time-fuel optimal control law. Techniques for evaluating the value of the relative weighting between time and fuel for a particular relay control law is studied along with techniques to interrelate other parameters for the two control laws. Vehicle attitude control laws employing control moment gyros are then investigated. Steering laws obtained from the expression for the reaction torque of the gyro configuration are compared to a total optimal attitude control law that is derived from optimal linear regulator theory. This total optimal attitude control law has computational disadvantages in the solving of the matrix Riccati equation. Several computational algorithms for solving the matrix Riccati equation are investigated with respect to accuracy, computational storage requirements, and computational speed.

A new optimal sliding mode controller design using scalar sign function.

PubMed

Singla, Mithun; Shieh, Leang-San; Song, Gangbing; Xie, Linbo; Zhang, Yongpeng

2014-03-01

This paper presents a new optimal sliding mode controller using the scalar sign function method. A smooth, continuous-time scalar sign function is used to replace the discontinuous switching function in the design of a sliding mode controller. The proposed sliding mode controller is designed using an optimal Linear Quadratic Regulator (LQR) approach. The sliding surface of the system is designed using stable eigenvectors and the scalar sign function. Controller simulations are compared with another existing optimal sliding mode controller. To test the effectiveness of the proposed controller, the controller is implemented on an aluminum beam with piezoceramic sensor and actuator for vibration control. This paper includes the control design and stability analysis of the new optimal sliding mode controller, followed by simulation and experimental results. The simulation and experimental results show that the proposed approach is very effective. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

EDITORIAL: Focus on Quantum Control

NASA Astrophysics Data System (ADS)

Rabitz, Herschel

2009-10-01

Control of quantum phenomena has grown from a dream to a burgeoning field encompassing wide-ranging experimental and theoretical activities. Theoretical research in this area primarily concerns identification of the principles for controlling quantum phenomena, the exploration of new experimental applications and the development of associated operational algorithms to guide such experiments. Recent experiments with adaptive feedback control span many applications including selective excitation, wave packet engineering and control in the presence of complex environments. Practical procedures are also being developed to execute real-time feedback control considering the resultant back action on the quantum system. This focus issue includes papers covering many of the latest advances in the field. Focus on Quantum Control Contents Control of quantum phenomena: past, present and future Constantin Brif, Raj Chakrabarti and Herschel Rabitz Biologically inspired molecular machines driven by light. Optimal control of a unidirectional rotor Guillermo Pérez-Hernández, Adam Pelzer, Leticia González and Tamar Seideman Simulating quantum search algorithm using vibronic states of I2 manipulated by optimally designed gate pulses Yukiyoshi Ohtsuki Efficient coherent control by sequences of pulses of finite duration Götz S Uhrig and Stefano Pasini Control by decoherence: weak field control of an excited state objective Gil Katz, Mark A Ratner and Ronnie Kosloff Multi-qubit compensation sequences Y Tomita, J T Merrill and K R Brown Environment-invariant measure of distance between evolutions of an open quantum system Matthew D Grace, Jason Dominy, Robert L Kosut, Constantin Brif and Herschel Rabitz Simplified quantum process tomography M P A Branderhorst, J Nunn, I A Walmsley and R L Kosut Achieving 'perfect' molecular discrimination via coherent control and stimulated emission Stephen D Clow, Uvo C Holscher and Thomas C Weinacht A convenient method to simulate and visually represent two-photon power spectra of arbitrarily and adaptively shaped broadband laser pulses M A Montgomery and N H Damrauer Accurate and efficient implementation of the von Neumann representation for laser pulses with discrete and finite spectra Frank Dimler, Susanne Fechner, Alexander Rodenberg, Tobias Brixner and David J Tannor Coherent strong-field control of multiple states by a single chirped femtosecond laser pulse M Krug, T Bayer, M Wollenhaupt, C Sarpe-Tudoran, T Baumert, S S Ivanov and N V Vitanov Quantum-state measurement of ionic Rydberg wavepackets X Zhang and R R Jones On the paradigm of coherent control: the phase-dependent light-matter interaction in the shaping window Tiago Buckup, Jurgen Hauer and Marcus Motzkus Use of the spatial phase of a focused laser beam to yield mechanistic information about photo-induced chemical reactions V J Barge, Z Hu and R J Gordon Coherent control of multiple vibrational excitations for optimal detection S D McGrane, R J Scharff, M Greenfield and D S Moore Mode selectivity with polarization shaping in the mid-IR David B Strasfeld, Chris T Middleton and Martin T Zanni Laser-guided relativistic quantum dynamics Chengpu Liu, Markus C Kohler, Karen Z Hatsagortsyan, Carsten Muller and Christoph H Keitel Continuous quantum error correction as classical hybrid control Hideo Mabuchi Quantum filter reduction for measurement-feedback control via unsupervised manifold learning Anne E B Nielsen, Asa S Hopkins and Hideo Mabuchi Control of the temporal profile of the local electromagnetic field near metallic nanostructures Ilya Grigorenko and Anatoly Efimov Laser-assisted molecular orientation in gaseous media: new possibilities and applications Dmitry V Zhdanov and Victor N Zadkov Optimization of laser field-free orientation of a state-selected NO molecular sample Arnaud Rouzee, Arjan Gijsbertsen, Omair Ghafur, Ofer M Shir, Thomas Back, Steven Stolte and Marc J J Vrakking Controlling the sense of molecular rotation Sharly Fleischer, Yuri Khodorkovsky, Yehiam Prior and Ilya Sh Averbukh Optimal control of interacting particles: a multi-configuration time-dependent Hartree-Fock approach Michael Mundt and David J Tannor Exact quantum dissipative dynamics under external time-dependent driving fields Jian Xu, Rui-Xue Xu and Yi Jing Yan Pulse trains in molecular dynamics and coherent spectroscopy: a theoretical study J Voll and R de Vivie-Riedle Quantum control of electron localization in molecules driven by trains of half-cycle pulses Emil Persson, Joachim Burgdorfer and Stefanie Grafe Quantum control design by Lyapunov trajectory tracking for dipole and polarizability coupling Jean-Michel Coron, Andreea Grigoriu, Catalin Lefter and Gabriel Turinici Sliding mode control of quantum systems Daoyi Dong and Ian R Petersen Implementation of fault-tolerant quantum logic gates via optimal control R Nigmatullin and S G Schirmer Generalized filtering of laser fields in optimal control theory: application to symmetry filtering of quantum gate operations Markus Schroder and Alex Brown

The optimal dynamic immunization under a controlled heterogeneous node-based SIRS model

NASA Astrophysics Data System (ADS)

Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan

2016-05-01

Dynamic immunizations, under which the state of the propagation network of electronic viruses can be changed by adjusting the control measures, are regarded as an alternative to static immunizations. This paper addresses the optimal dynamical immunization under the widely accepted SIRS assumption. First, based on a controlled heterogeneous node-based SIRS model, an optimal control problem capturing the optimal dynamical immunization is formulated. Second, the existence of an optimal dynamical immunization scheme is shown, and the corresponding optimality system is derived. Next, some numerical examples are given to show that an optimal immunization strategy can be worked out by numerically solving the optimality system, from which it is found that the network topology has a complex impact on the optimal immunization strategy. Finally, the difference between a payoff and the minimum payoff is estimated in terms of the deviation of the corresponding immunization strategy from the optimal immunization strategy. The proposed optimal immunization scheme is justified, because it can achieve a low level of infections at a low cost.

How to mathematically optimize drug regimens using optimal control.

PubMed

Moore, Helen

2018-02-01

This article gives an overview of a technique called optimal control, which is used to optimize real-world quantities represented by mathematical models. I include background information about the historical development of the technique and applications in a variety of fields. The main focus here is the application to diseases and therapies, particularly the optimization of combination therapies, and I highlight several such examples. I also describe the basic theory of optimal control, and illustrate each of the steps with an example that optimizes the doses in a combination regimen for leukemia. References are provided for more complex cases. The article is aimed at modelers working in drug development, who have not used optimal control previously. My goal is to make this technique more accessible in the biopharma community.

Optimization of helicopter airframe structures for vibration reduction considerations, formulations and applications

NASA Technical Reports Server (NTRS)

Murthy, T. Sreekanta

1988-01-01

Several key issues involved in the application of formal optimization technique to helicopter airframe structures for vibration reduction are addressed. Considerations which are important in the optimization of real airframe structures are discussed. Considerations necessary to establish relevant set of design variables, constraints and objectives which are appropriate to conceptual, preliminary, detailed design, ground and flight test phases of airframe design are discussed. A methodology is suggested for optimization of airframes in various phases of design. Optimization formulations that are unique to helicopter airframes are described and expressions for vibration related functions are derived. Using a recently developed computer code, the optimization of a Bell AH-1G helicopter airframe is demonstrated.

Optimal Guaranteed Cost Sliding Mode Control for Constrained-Input Nonlinear Systems With Matched and Unmatched Disturbances.

PubMed

Zhang, Huaguang; Qu, Qiuxia; Xiao, Geyang; Cui, Yang

2018-06-01

Based on integral sliding mode and approximate dynamic programming (ADP) theory, a novel optimal guaranteed cost sliding mode control is designed for constrained-input nonlinear systems with matched and unmatched disturbances. When the system moves on the sliding surface, the optimal guaranteed cost control problem of sliding mode dynamics is transformed into the optimal control problem of a reformulated auxiliary system with a modified cost function. The ADP algorithm based on single critic neural network (NN) is applied to obtain the approximate optimal control law for the auxiliary system. Lyapunov techniques are used to demonstrate the convergence of the NN weight errors. In addition, the derived approximate optimal control is verified to guarantee the sliding mode dynamics system to be stable in the sense of uniform ultimate boundedness. Some simulation results are presented to verify the feasibility of the proposed control scheme.

Time-optimal control with finite bandwidth

NASA Astrophysics Data System (ADS)

Hirose, M.; Cappellaro, P.

2018-04-01

Time-optimal control theory provides recipes to achieve quantum operations with high fidelity and speed, as required in quantum technologies such as quantum sensing and computation. While technical advances have achieved the ultrastrong driving regime in many physical systems, these capabilities have yet to be fully exploited for the precise control of quantum systems, as other limitations, such as the generation of higher harmonics or the finite response time of the control apparatus, prevent the implementation of theoretical time-optimal control. Here we present a method to achieve time-optimal control of qubit systems that can take advantage of fast driving beyond the rotating wave approximation. We exploit results from time-optimal control theory to design driving protocols that can be implemented with realistic, finite-bandwidth control fields, and we find a relationship between bandwidth limitations and achievable control fidelity.

Optimization of the convection volume in online post-dilution haemodiafiltration: practical and technical issues

PubMed Central

Chapdelaine, Isabelle; de Roij van Zuijdewijn, Camiel L.M.; Mostovaya, Ira M.; Lévesque, Renée; Davenport, Andrew; Blankestijn, Peter J.; Wanner, Christoph; Nubé, Menso J.; Grooteman, Muriel P.C.

2015-01-01

In post-dilution online haemodiafiltration (ol-HDF), a relationship has been demonstrated between the magnitude of the convection volume and survival. However, to achieve high convection volumes (>22 L per session) detailed notion of its determining factors is highly desirable. This manuscript summarizes practical problems and pitfalls that were encountered during the quest for high convection volumes. Specifically, it addresses issues such as type of vascular access, needles, blood flow rate, recirculation, filtration fraction, anticoagulation and dialysers. Finally, five of the main HDF systems in Europe are briefly described as far as HDF prescription and optimization of the convection volume is concerned. PMID:25815176

Numerical optimization methods for controlled systems with parameters

NASA Astrophysics Data System (ADS)

Tyatyushkin, A. I.

2017-10-01

First- and second-order numerical methods for optimizing controlled dynamical systems with parameters are discussed. In unconstrained-parameter problems, the control parameters are optimized by applying the conjugate gradient method. A more accurate numerical solution in these problems is produced by Newton's method based on a second-order functional increment formula. Next, a general optimal control problem with state constraints and parameters involved on the righthand sides of the controlled system and in the initial conditions is considered. This complicated problem is reduced to a mathematical programming one, followed by the search for optimal parameter values and control functions by applying a multimethod algorithm. The performance of the proposed technique is demonstrated by solving application problems.

A Routing Protocol for Multisink Wireless Sensor Networks in Underground Coalmine Tunnels

PubMed Central

Xia, Xu; Chen, Zhigang; Liu, Hui; Wang, Huihui; Zeng, Feng

2016-01-01

Traditional underground coalmine monitoring systems are mainly based on the use of wired transmission. However, when cables are damaged during an accident, it is difficult to obtain relevant data on environmental parameters and the emergency situation underground. To address this problem, the use of wireless sensor networks (WSNs) has been proposed. However, the shape of coalmine tunnels is not conducive to the deployment of WSNs as they are long and narrow. Therefore, issues with the network arise, such as extremely large energy consumption, very weak connectivity, long time delays, and a short lifetime. To solve these problems, in this study, a new routing protocol algorithm for multisink WSNs based on transmission power control is proposed. First, a transmission power control algorithm is used to negotiate the optimal communication radius and transmission power of each sink. Second, the non-uniform clustering idea is adopted to optimize the cluster head selection. Simulation results are subsequently compared to the Centroid of the Nodes in a Partition (CNP) strategy and show that the new algorithm delivers a good performance: power efficiency is increased by approximately 70%, connectivity is increased by approximately 15%, the cluster interference is diminished by approximately 50%, the network lifetime is increased by approximately 6%, and the delay is reduced with an increase in the number of sinks. PMID:27916917

Statistical Optimization of Pharmacogenomics Association Studies: Key Considerations from Study Design to Analysis

PubMed Central

Grady, Benjamin J.; Ritchie, Marylyn D.

2011-01-01

Research in human genetics and genetic epidemiology has grown significantly over the previous decade, particularly in the field of pharmacogenomics. Pharmacogenomics presents an opportunity for rapid translation of associated genetic polymorphisms into diagnostic measures or tests to guide therapy as part of a move towards personalized medicine. Expansion in genotyping technology has cleared the way for widespread use of whole-genome genotyping in the effort to identify novel biology and new genetic markers associated with pharmacokinetic and pharmacodynamic endpoints. With new technology and methodology regularly becoming available for use in genetic studies, a discussion on the application of such tools becomes necessary. In particular, quality control criteria have evolved with the use of GWAS as we have come to understand potential systematic errors which can be introduced into the data during genotyping. There have been several replicated pharmacogenomic associations, some of which have moved to the clinic to enact change in treatment decisions. These examples of translation illustrate the strength of evidence necessary to successfully and effectively translate a genetic discovery. In this review, the design of pharmacogenomic association studies is examined with the goal of optimizing the impact and utility of this research. Issues of ascertainment, genotyping, quality control, analysis and interpretation are considered. PMID:21887206

A Routing Protocol for Multisink Wireless Sensor Networks in Underground Coalmine Tunnels.

PubMed

Xia, Xu; Chen, Zhigang; Liu, Hui; Wang, Huihui; Zeng, Feng

2016-11-30

Traditional underground coalmine monitoring systems are mainly based on the use of wired transmission. However, when cables are damaged during an accident, it is difficult to obtain relevant data on environmental parameters and the emergency situation underground. To address this problem, the use of wireless sensor networks (WSNs) has been proposed. However, the shape of coalmine tunnels is not conducive to the deployment of WSNs as they are long and narrow. Therefore, issues with the network arise, such as extremely large energy consumption, very weak connectivity, long time delays, and a short lifetime. To solve these problems, in this study, a new routing protocol algorithm for multisink WSNs based on transmission power control is proposed. First, a transmission power control algorithm is used to negotiate the optimal communication radius and transmission power of each sink. Second, the non-uniform clustering idea is adopted to optimize the cluster head selection. Simulation results are subsequently compared to the Centroid of the Nodes in a Partition (CNP) strategy and show that the new algorithm delivers a good performance: power efficiency is increased by approximately 70%, connectivity is increased by approximately 15%, the cluster interference is diminished by approximately 50%, the network lifetime is increased by approximately 6%, and the delay is reduced with an increase in the number of sinks.

Effect of biased feedback on motor imagery learning in BCI-teleoperation system.

PubMed

Alimardani, Maryam; Nishio, Shuichi; Ishiguro, Hiroshi

2014-01-01

Feedback design is an important issue in motor imagery BCI systems. Regardless, to date it has not been reported how feedback presentation can optimize co-adaptation between a human brain and such systems. This paper assesses the effect of realistic visual feedback on users' BCI performance and motor imagery skills. We previously developed a tele-operation system for a pair of humanlike robotic hands and showed that BCI control of such hands along with first-person perspective visual feedback of movements can arouse a sense of embodiment in the operators. In the first stage of this study, we found that the intensity of this ownership illusion was associated with feedback presentation and subjects' performance during BCI motion control. In the second stage, we probed the effect of positive and negative feedback bias on subjects' BCI performance and motor imagery skills. Although the subject specific classifier, which was set up at the beginning of experiment, detected no significant change in the subjects' online performance, evaluation of brain activity patterns revealed that subjects' self-regulation of motor imagery features improved due to a positive bias of feedback and a possible occurrence of ownership illusion. Our findings suggest that in general training protocols for BCIs, manipulation of feedback can play an important role in the optimization of subjects' motor imagery skills.

Mixed-Strategy Chance Constrained Optimal Control

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J.

2013-01-01

This paper presents a novel chance constrained optimal control (CCOC) algorithm that chooses a control action probabilistically. A CCOC problem is to find a control input that minimizes the expected cost while guaranteeing that the probability of violating a set of constraints is below a user-specified threshold. We show that a probabilistic control approach, which we refer to as a mixed control strategy, enables us to obtain a cost that is better than what deterministic control strategies can achieve when the CCOC problem is nonconvex. The resulting mixed-strategy CCOC problem turns out to be a convexification of the original nonconvex CCOC problem. Furthermore, we also show that a mixed control strategy only needs to "mix" up to two deterministic control actions in order to achieve optimality. Building upon an iterative dual optimization, the proposed algorithm quickly converges to the optimal mixed control strategy with a user-specified tolerance.

Coordinated single-phase control scheme for voltage unbalance reduction in low voltage network.

PubMed

Pullaguram, Deepak; Mishra, Sukumar; Senroy, Nilanjan

2017-08-13

Low voltage (LV) distribution systems are typically unbalanced in nature due to unbalanced loading and unsymmetrical line configuration. This situation is further aggravated by single-phase power injections. A coordinated control scheme is proposed for single-phase sources, to reduce voltage unbalance. A consensus-based coordination is achieved using a multi-agent system, where each agent estimates the averaged global voltage and current magnitudes of individual phases in the LV network. These estimated values are used to modify the reference power of individual single-phase sources, to ensure system-wide balanced voltages and proper power sharing among sources connected to the same phase. Further, the high X / R ratio of the filter, used in the inverter of the single-phase source, enables control of reactive power, to minimize voltage unbalance locally. The proposed scheme is validated by simulating a LV distribution network with multiple single-phase sources subjected to various perturbations.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Modeling of the control of the driven current profile in ICRF MCCD on EAST plasma

NASA Astrophysics Data System (ADS)

Yin, L.; Yang, C.; Gong, X. Y.; Lu, X. Q.; Cao, J. J.; Wu, Z. Y.; Chen, Y.; Du, D.

2018-05-01

Control of the current profile is a crucial issue for improved confinement and the inhibition of instability in advanced tokamak operation. Using typical discharge data for the Experimental Advanced Superconducting Tokamak, numerical simulations of driven-current profile control in mode conversion current drive (MCCD) in the ion cyclotron range of frequencies were performed employing a full-wave method and Ehst-Karney efficiency formula. Results indicate that the driven current profile in MCCD can be effectively modified by shifting the mode conversion layer. The peak of the driven current can be located at an aimed position in the normalized minor radius range (-0.60 ≤r/a≤0) by changing the radiofrequency and the minority-ion concentration. The efficiency of the off-axis MCCD can reach 233 kA/MW through optimization, and the mode converted ion cyclotron wave plays an important role in such scenarios. The effects of electron temperature and plasma density on the driven current profile are also investigated.

Cerebellar supervised learning revisited: biophysical modeling and degrees-of-freedom control.

PubMed

Kawato, Mitsuo; Kuroda, Shinya; Schweighofer, Nicolas

2011-10-01

The biophysical models of spike-timing-dependent plasticity have explored dynamics with molecular basis for such computational concepts as coincidence detection, synaptic eligibility trace, and Hebbian learning. They overall support different learning algorithms in different brain areas, especially supervised learning in the cerebellum. Because a single spine is physically very small, chemical reactions at it are essentially stochastic, and thus sensitivity-longevity dilemma exists in the synaptic memory. Here, the cascade of excitable and bistable dynamics is proposed to overcome this difficulty. All kinds of learning algorithms in different brain regions confront with difficult generalization problems. For resolution of this issue, the control of the degrees-of-freedom can be realized by changing synchronicity of neural firing. Especially, for cerebellar supervised learning, the triangle closed-loop circuit consisting of Purkinje cells, the inferior olive nucleus, and the cerebellar nucleus is proposed as a circuit to optimally control synchronous firing and degrees-of-freedom in learning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Guest Editorial Introduction to the Special Issue on 'Advanced Signal Processing Techniques and Telecommunications Network Infrastructures for Smart Grid Analysis, Monitoring, and Management'

DOE PAGES

Bracale, Antonio; Barros, Julio; Cacciapuoti, Angela Sara; ...

2015-06-10

Electrical power systems are undergoing a radical change in structure, components, and operational paradigms, and are progressively approaching the new concept of smart grids (SGs). Future power distribution systems will be characterized by the simultaneous presence of various distributed resources, such as renewable energy systems (i.e., photovoltaic power plant and wind farms), storage systems, and controllable/non-controllable loads. Control and optimization architectures will enable network-wide coordination of these grid components in order to improve system efficiency and reliability and to limit greenhouse gas emissions. In this context, the energy flows will be bidirectional from large power plants to end users andmore » vice versa; producers and consumers will continuously interact at different voltage levels to determine in advance the requests of loads and to adapt the production and demand for electricity flexibly and efficiently also taking into account the presence of storage systems.« less

Numerical solution of a conspicuous consumption model with constant control delay☆

PubMed Central

Huschto, Tony; Feichtinger, Gustav; Hartl, Richard F.; Kort, Peter M.; Sager, Sebastian; Seidl, Andrea

2011-01-01

We derive optimal pricing strategies for conspicuous consumption products in periods of recession. To that end, we formulate and investigate a two-stage economic optimal control problem that takes uncertainty of the recession period length and delay effects of the pricing strategy into account. This non-standard optimal control problem is difficult to solve analytically, and solutions depend on the variable model parameters. Therefore, we use a numerical result-driven approach. We propose a structure-exploiting direct method for optimal control to solve this challenging optimization problem. In particular, we discretize the uncertainties in the model formulation by using scenario trees and target the control delays by introduction of slack control functions. Numerical results illustrate the validity of our approach and show the impact of uncertainties and delay effects on optimal economic strategies. During the recession, delayed optimal prices are higher than the non-delayed ones. In the normal economic period, however, this effect is reversed and optimal prices with a delayed impact are smaller compared to the non-delayed case. PMID:22267871

Optimal treatment interruptions control of TB transmission model

NASA Astrophysics Data System (ADS)

Nainggolan, Jonner; Suparwati, Titik; Kawuwung, Westy B.

2018-03-01

A tuberculosis model which incorporates treatment interruptions of infectives is established. Optimal control of individuals infected with active TB is given in the model. It is obtained that the control reproduction numbers is smaller than the reproduction number, this means treatment controls could optimize the decrease in the spread of active TB. For this model, controls on treatment of infection individuals to reduce the actively infected individual populations, by application the Pontryagins Maximum Principle for optimal control. The result further emphasized the importance of controlling disease relapse in reducing the number of actively infected and treatment interruptions individuals with tuberculosis.

Different extraction pretreatments significantly change the flavonoid contents of Scutellaria baicalensis

PubMed Central

Yu, Chunhao; Qu, Fengyun; Mao, Yanyong; Li, Dong; Zhen, Zhong; Nass, Rachael; Calway, Tyler; Wang, Yunwei; Yuan, Chun-Su; Wang, Chong-Zhi

2014-01-01

Context Scutellaria baicalensis is one of the most commonly used medicinal herbs, especially in traditional Chinese medicine. However, compared to many pharmacological studies of this botanical, much less attention has been paid to the quality control of the herb’s pretreatment prior to extract preparation, an issue that may affect therapeutic outcomes. Objective The current study was designed to evaluate whether different pretreatment conditions change the contents of its four major flavonoids in the herb, i.e., two glycosides (baicalin and wogonoside) and two aglycons (baicalein and wogonin). Materials and methods An HPLC assay was used to quantify the contents of these four flavonoids. The composition changes of four flavonoids by different pretreatment conditions including solvent, treatment time, temperature, pH value, and herb/solvent ratio were evaluated. Results After selection of the first order time-curve kinetics, our data showed that at 50°C, 1:5 herb/water (in w/v) ratio and pH 6.67 yielded an optimal conversion rate from flavonoid glycosides to their aglycons. In this optimized condition, the contents of baicalin and wogonoside were decreased to 1/70 and 1/13, while baicalein and wogonin were increased 3.5 and 3.1 folds, respectively, compared to untreated herb. Discussion and conclusion The markedly variable conversion rates by different pretreatment conditions complicated the quality control of this herb, mainly due to the high amount of endogenous enzymes of S. baicalensis. Optimal pretreatment conditions obtained from this study could be used obtain the highest level of desired constituents to achieve better pharmacological effects. PMID:23738852

Different extraction pretreatments significantly change the flavonoid contents of Scutellaria baicalensis.

PubMed

Yu, Chunhao; Qu, Fengyun; Mao, Yanyong; Li, Dong; Zhen, Zhong; Nass, Rachael; Calway, Tyler; Wang, Yunwei; Yuan, Chun-Su; Wang, Chong-Zhi

2013-10-01

Scutellaria baicalensis Georgi (Labiatae) is one of the most commonly used medicinal herbs, especially in traditional Chinese medicine. However, compared to many pharmacological studies of this botanical, much less attention has been paid to the quality control of the herb's pretreatment prior to extract preparation, an issue that may affect therapeutic outcomes. The current study was designed to evaluate whether different pretreatment conditions change the contents of the four major flavonoids in the herb, i.e., two glycosides (baicalin and wogonoside) and two aglycones (baicalein and wogonin). A high-performance liquid chromatography assay was used to quantify the contents of these four flavonoids. The composition changes of four flavonoids by different pretreatment conditions, including solvent, treatment time, temperature, pH value and herb/solvent ratio were evaluated. After selection of the first order time-curve kinetics, our data showed that at 50 °C, 1:5 herb/water (in w/v) ratio and pH 6.67 yielded an optimal conversion rate from flavonoid glycosides to their aglycones. In this optimized condition, the contents of baicalin and wogonoside were decreased to 1/70 and 1/13, while baicalein and wogonin were increased 3.5- and 3.1-fold, respectively, compared to untreated herb. The markedly variable conversion rates by different pretreatment conditions complicated the quality control of this herb, mainly due to the high amount of endogenous enzymes of S. baicalensis. Optimal pretreatment conditions observed in this study could be used obtain the highest level of desired constituents to achieve better pharmacological effects.

Applying Biomimetic Algorithms for Extra-Terrestrial Habitat Generation

NASA Technical Reports Server (NTRS)

Birge, Brian

2012-01-01

The objective is to simulate and optimize distributed cooperation among a network of robots tasked with cooperative excavation on an extra-terrestrial surface. Additionally to examine the concept of directed Emergence among a group of limited artificially intelligent agents. Emergence is the concept of achieving complex results from very simple rules or interactions. For example, in a termite mound each individual termite does not carry a blueprint of how to make their home in a global sense, but their interactions based strictly on local desires create a complex superstructure. Leveraging this Emergence concept applied to a simulation of cooperative agents (robots) will allow an examination of the success of non-directed group strategy achieving specific results. Specifically the simulation will be a testbed to evaluate population based robotic exploration and cooperative strategies while leveraging the evolutionary teamwork approach in the face of uncertainty about the environment and partial loss of sensors. Checking against a cost function and 'social' constraints will optimize cooperation when excavating a simulated tunnel. Agents will act locally with non-local results. The rules by which the simulated robots interact will be optimized to the simplest possible for the desired result, leveraging Emergence. Sensor malfunction and line of sight issues will be incorporated into the simulation. This approach falls under Swarm Robotics, a subset of robot control concerned with finding ways to control large groups of robots. Swarm Robotics often contains biologically inspired approaches, research comes from social insect observation but also data from among groups of herding, schooling, and flocking animals. Biomimetic algorithms applied to manned space exploration is the method under consideration for further study.

GaAs/AlOx high-contrast grating mirrors for mid-infrared VCSELs

NASA Astrophysics Data System (ADS)

Almuneau, G.; Laaroussi, Y.; Chevallier, C.; Genty, F.; Fressengeas, N. s.; Cerutti, L.; Gauthier-Lafaye, Olivier

2015-02-01

Mid-infrared Vertical cavity surface emitting lasers (MIR-VCSEL) are very attractive compact sources for spectroscopic measurements above 2μm, relevant for molecules sensing in various application domains. A long-standing issue for long wavelength VCSEL is the large structure thickness affecting the laser properties, added for the MIR to the tricky technological implementation of the antimonide alloys system. In this paper, we propose a new geometry for MIR-VCSEL including both a lateral confinement by an oxide aperture, and a high-contrast sub-wavelength grating mirror (HCG mirror) formed by the high contrast combination AIOx/GaAs in place of GaSb/A|AsSb top Bragg reflector. In addition to drastically simplifying the vertical stack, HCG mirror allows to control through its design the beam properties. The robust design of the HCG has been ensured by an original method of optimization based on particle swarm optimization algorithm combined with an anti-optimization one, thus allowing large error tolerance for the nano-fabrication. Oxide-based electro-optical confinement has been adapted to mid-infrared lasers, byusing a metamorphic approach with (Al) GaAs layer directly epitaxially grown on the GaSb-based VCSEL bottom structure. This approach combines the advantages of the will-controlled oxidation of AlAs layer and the efficient gain media of Sb-based for mid-infrared emission. We finally present the results obtained on electrically pumped mid-IR-VCSELs structures, for which we included oxide aperturing for lateral confinement and HCG as high reflectivity output mirrors, both based on AlxOy/GaAs heterostructures.

Optimal speech motor control and token-to-token variability: a Bayesian modeling approach.

PubMed

Patri, Jean-François; Diard, Julien; Perrier, Pascal

2015-12-01

The remarkable capacity of the speech motor system to adapt to various speech conditions is due to an excess of degrees of freedom, which enables producing similar acoustical properties with different sets of control strategies. To explain how the central nervous system selects one of the possible strategies, a common approach, in line with optimal motor control theories, is to model speech motor planning as the solution of an optimality problem based on cost functions. Despite the success of this approach, one of its drawbacks is the intrinsic contradiction between the concept of optimality and the observed experimental intra-speaker token-to-token variability. The present paper proposes an alternative approach by formulating feedforward optimal control in a probabilistic Bayesian modeling framework. This is illustrated by controlling a biomechanical model of the vocal tract for speech production and by comparing it with an existing optimal control model (GEPPETO). The essential elements of this optimal control model are presented first. From them the Bayesian model is constructed in a progressive way. Performance of the Bayesian model is evaluated based on computer simulations and compared to the optimal control model. This approach is shown to be appropriate for solving the speech planning problem while accounting for variability in a principled way.

CO and NO emissions from pellet stoves: an experimental study

NASA Astrophysics Data System (ADS)

Petrocelli, D.; Lezzi, A. M.

2014-04-01

This work presents a report on an experimental investigation on pellet stoves aimed to fully understand which parameters influence CO and NO emissions and how it is possible to find and choose the optimal point of working. Tests are performed on three pellet stoves varying heating power, combustion chamber size and burner pot geometry. After a brief review on the factors which influence the production of these pollutants, we present and discuss the results of experimental tests aimed to ascertain how the geometry of the combustion chamber and the distribution of primary and secondary air, can modify the quantity of CO and NO in the flue gas. Experimental tests show that production of CO is strongly affected by the excess air and by its distribution: in particular, it is critical an effective control of air distribution. In these devices a low-level of CO emissions does require a proper setup to operate in the optimal range of excess air that minimizes CO production. In order to simplify the optimization process, we propose the use of instantaneous data of CO and O2 concentration, instead of average values, because they allow a quick identification of the optimal point. It is shown that the optimal range of operation can be enlarged as a consequence of proper burner pot design. Finally, it is shown that NO emissions are not a critical issue, since they are well below threshold enforced by law, are not influenced by the distribution of air in the combustion chamber, and their behavior as a function of air excess is the same for all the geometries investigated here.

Competitive Swarm Optimizer Based Gateway Deployment Algorithm in Cyber-Physical Systems.

PubMed

Huang, Shuqiang; Tao, Ming

2017-01-22

Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K -center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms.

Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mani, Seethambal S.; van Bloemen Waanders, Bart Gustaaf; Cooper, Scott Patrick

2006-11-01

The project objective was to detail better ways to assess and exploit intelligent oil and gas field information through improved modeling, sensor technology, and process control to increase ultimate recovery of domestic hydrocarbons. To meet this objective we investigated the use of permanent downhole sensors systems (Smart Wells) whose data is fed real-time into computational reservoir models that are integrated with optimized production control systems. The project utilized a three-pronged approach (1) a value of information analysis to address the economic advantages, (2) reservoir simulation modeling and control optimization to prove the capability, and (3) evaluation of new generation sensormore » packaging to survive the borehole environment for long periods of time. The Value of Information (VOI) decision tree method was developed and used to assess the economic advantage of using the proposed technology; the VOI demonstrated the increased subsurface resolution through additional sensor data. Our findings show that the VOI studies are a practical means of ascertaining the value associated with a technology, in this case application of sensors to production. The procedure acknowledges the uncertainty in predictions but nevertheless assigns monetary value to the predictions. The best aspect of the procedure is that it builds consensus within interdisciplinary teams The reservoir simulation and modeling aspect of the project was developed to show the capability of exploiting sensor information both for reservoir characterization and to optimize control of the production system. Our findings indicate history matching is improved as more information is added to the objective function, clearly indicating that sensor information can help in reducing the uncertainty associated with reservoir characterization. Additional findings and approaches used are described in detail within the report. The next generation sensors aspect of the project evaluated sensors and packaging survivability issues. Our findings indicate that packaging represents the most significant technical challenge associated with application of sensors in the downhole environment for long periods (5+ years) of time. These issues are described in detail within the report. The impact of successful reservoir monitoring programs and coincident improved reservoir management is measured by the production of additional oil and gas volumes from existing reservoirs, revitalization of nearly depleted reservoirs, possible re-establishment of already abandoned reservoirs, and improved economics for all cases. Smart Well monitoring provides the means to understand how a reservoir process is developing and to provide active reservoir management. At the same time it also provides data for developing high-fidelity simulation models. This work has been a joint effort with Sandia National Laboratories and UT-Austin's Bureau of Economic Geology, Department of Petroleum and Geosystems Engineering, and the Institute of Computational and Engineering Mathematics.« less

Optimization of life support systems and their systems reliability

NASA Technical Reports Server (NTRS)

Fan, L. T.; Hwang, C. L.; Erickson, L. E.

1971-01-01

The identification, analysis, and optimization of life support systems and subsystems have been investigated. For each system or subsystem that has been considered, the procedure involves the establishment of a set of system equations (or mathematical model) based on theory and experimental evidences; the analysis and simulation of the model; the optimization of the operation, control, and reliability; analysis of sensitivity of the system based on the model; and, if possible, experimental verification of the theoretical and computational results. Research activities include: (1) modeling of air flow in a confined space; (2) review of several different gas-liquid contactors utilizing centrifugal force: (3) review of carbon dioxide reduction contactors in space vehicles and other enclosed structures: (4) application of modern optimal control theory to environmental control of confined spaces; (5) optimal control of class of nonlinear diffusional distributed parameter systems: (6) optimization of system reliability of life support systems and sub-systems: (7) modeling, simulation and optimal control of the human thermal system: and (8) analysis and optimization of the water-vapor eletrolysis cell.

Near-Optimal Tracking Control of Mobile Robots Via Receding-Horizon Dual Heuristic Programming.

PubMed

Lian, Chuanqiang; Xu, Xin; Chen, Hong; He, Haibo

2016-11-01

Trajectory tracking control of wheeled mobile robots (WMRs) has been an important research topic in control theory and robotics. Although various tracking control methods with stability have been developed for WMRs, it is still difficult to design optimal or near-optimal tracking controller under uncertainties and disturbances. In this paper, a near-optimal tracking control method is presented for WMRs based on receding-horizon dual heuristic programming (RHDHP). In the proposed method, a backstepping kinematic controller is designed to generate desired velocity profiles and the receding horizon strategy is used to decompose the infinite-horizon optimal control problem into a series of finite-horizon optimal control problems. In each horizon, a closed-loop tracking control policy is successively updated using a class of approximate dynamic programming algorithms called finite-horizon dual heuristic programming (DHP). The convergence property of the proposed method is analyzed and it is shown that the tracking control system based on RHDHP is asymptotically stable by using the Lyapunov approach. Simulation results on three tracking control problems demonstrate that the proposed method has improved control performance when compared with conventional model predictive control (MPC) and DHP. It is also illustrated that the proposed method has lower computational burden than conventional MPC, which is very beneficial for real-time tracking control.

Linking Temporal-Optimization and Spatial-Simulation Models for Forest Planning

Treesearch

Larry A. Leefers; Eric J. Gustafson; Phillip Freeman

2003-01-01

Increasingly, resource management agencies and researchers have turned their analysis and modeling efforts towards spatial and temporal information. This is driven by the need to address wildlife concerns, landscape issues, and social/economic questions. Historically, the USDA Forest Service has used optimization models (i.e., FORPLAN and Spectrum) for timber harvest...

Tracheal bioengineering: the next steps. Proceeds of an International Society of Cell Therapy Pulmonary Cellular Therapy Signature Series Workshop, Paris, France, April 22, 2014.

PubMed

Weiss, Daniel J; Elliott, Martin; Jang, Queenie; Poole, Brian; Birchall, Martin

2014-12-01

There has been significant and exciting recent progress in the development of bioengineering approaches for generating tracheal tissue that can be used for congenital and acquired tracheal diseases. This includes a growing clinical experience in both pediatric and adult patients with life-threatening tracheal diseases. However, not all of these attempts have been successful, and there is ongoing discussion and debate about the optimal approaches to be used. These include considerations of optimal materials, particularly use of synthetic versus biologic scaffolds, appropriate cellularization of the scaffolds, optimal surgical approaches and optimal measure of both clinical and biologic outcomes. To address these issues, the International Society of Cell Therapy convened a first-ever meeting of the leading clinicians and tracheal biologists, along with experts in regulatory and ethical affairs, to discuss and debate the issues. A series of recommendations are presented for how to best move the field ahead. Copyright © 2014 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Congestion control and routing over satellite networks

NASA Astrophysics Data System (ADS)

Cao, Jinhua

Satellite networks and transmissions find their application in fields of computer communications, telephone communications, television broadcasting, transportation, space situational awareness systems and so on. This thesis mainly focuses on two networking issues affecting satellite networking: network congestion control and network routing optimization. Congestion, which leads to long queueing delays, packet losses or both, is a networking problem that has drawn the attention of many researchers. The goal of congestion control mechanisms is to ensure high bandwidth utilization while avoiding network congestion by regulating the rate at which traffic sources inject packets into a network. In this thesis, we propose a stable congestion controller using data-driven, safe switching control theory to improve the dynamic performance of satellite Transmission Control Protocol/Active Queue Management (TCP/AQM) networks. First, the stable region of the Proportional-Integral (PI) parameters for a nominal model is explored. Then, a PI controller, whose parameters are adaptively tuned by switching among members of a given candidate set, using observed plant data, is presented and compared with some classical AQM policy examples, such as Random Early Detection (RED) and fixed PI control. A new cost detectable switching law with an interval cost function switching algorithm, which improves the performance and also saves the computational cost, is developed and compared with a law commonly used in the switching control literature. Finite-gain stability of the system is proved. A fuzzy logic PI controller is incorporated as a special candidate to achieve good performance at all nominal points with the available set of candidate controllers. Simulations are presented to validate the theory. An effocient routing algorithm plays a key role in optimizing network resources. In this thesis, we briefly analyze Low Earth Orbit (LEO) satellite networks, review the Cross Entropy (CE) method and then develop a novel on-demand routing system named Cross Entropy Accelerated Ant Routing System (CEAARS) for regular constellation LEO satellite networks. By implementing simulations on an Iridium-like satellite network, we compare the proposed CEAARS algorithm with the two approaches to adaptive routing protocols on the Internet: distance-vector (DV) and link-state (LS), as well as with the original Cross Entropy Ant Routing System (CEARS). DV algorithms are based on distributed Bellman Ford algorithm, and LS algorithms are implementation of Dijkstras single source shortest path. The results show that CEAARS not only remarkably improves the convergence speed of achieving optimal or suboptimal paths, but also reduces the number of overhead ants (management packets).

Optimal preview control for a linear continuous-time stochastic control system in finite-time horizon

NASA Astrophysics Data System (ADS)

Wu, Jiang; Liao, Fucheng; Tomizuka, Masayoshi

2017-01-01

This paper discusses the design of the optimal preview controller for a linear continuous-time stochastic control system in finite-time horizon, using the method of augmented error system. First, an assistant system is introduced for state shifting. Then, in order to overcome the difficulty of the state equation of the stochastic control system being unable to be differentiated because of Brownian motion, the integrator is introduced. Thus, the augmented error system which contains the integrator vector, control input, reference signal, error vector and state of the system is reconstructed. This leads to the tracking problem of the optimal preview control of the linear stochastic control system being transformed into the optimal output tracking problem of the augmented error system. With the method of dynamic programming in the theory of stochastic control, the optimal controller with previewable signals of the augmented error system being equal to the controller of the original system is obtained. Finally, numerical simulations show the effectiveness of the controller.

Alien Genetic Algorithm for Exploration of Search Space

NASA Astrophysics Data System (ADS)

Patel, Narendra; Padhiyar, Nitin

2010-10-01

Genetic Algorithm (GA) is a widely accepted population based stochastic optimization technique used for single and multi objective optimization problems. Various versions of modifications in GA have been proposed in last three decades mainly addressing two issues, namely increasing convergence rate and increasing probability of global minima. While both these. While addressing the first issue, GA tends to converge to a local optima and addressing the second issue corresponds the large computational efforts. Thus, to reduce the contradictory effects of these two aspects, we propose a modification in GA by adding an alien member in the population at every generation. Addition of an Alien member in the current population at every generation increases the probability of obtaining global minima at the same time maintaining higher convergence rate. With two test cases, we have demonstrated the efficacy of the proposed GA by comparing with the conventional GA.

Multidisciplinary design optimization of aircraft wing structures with aeroelastic and aeroservoelastic constraints

NASA Astrophysics Data System (ADS)

Jung, Sang-Young

Design procedures for aircraft wing structures with control surfaces are presented using multidisciplinary design optimization. Several disciplines such as stress analysis, structural vibration, aerodynamics, and controls are considered simultaneously and combined for design optimization. Vibration data and aerodynamic data including those in the transonic regime are calculated by existing codes. Flutter analyses are performed using those data. A flutter suppression method is studied using control laws in the closed-loop flutter equation. For the design optimization, optimization techniques such as approximation, design variable linking, temporary constraint deletion, and optimality criteria are used. Sensitivity derivatives of stresses and displacements for static loads, natural frequency, flutter characteristics, and control characteristics with respect to design variables are calculated for an approximate optimization. The objective function is the structural weight. The design variables are the section properties of the structural elements and the control gain factors. Existing multidisciplinary optimization codes (ASTROS* and MSC/NASTRAN) are used to perform single and multiple constraint optimizations of fully built up finite element wing structures. Three benchmark wing models are developed and/or modified for this purpose. The models are tested extensively.

God-Mediated Control and Change in Self-Rated Health

PubMed Central

Krause, Neal

2010-01-01

The purpose of this study was to see if feelings of God-mediated control are associated with change in self-rated health over time. In the process, an effort was made to see if a sense of meaning in life and optimism mediated the relationship between God-mediated control and change in health. The following hypothesized relationships were contained in the conceptual model that was developed to evaluate these issues: (1) people who go to church more often tend to have stronger God-mediated control beliefs than individuals who do not attend worship services as often; (2) people with a strong sense of God-mediated control are more likely to find a sense of meaning in life and be more optimistic than individuals who do not have a strong sense of God-mediated control; (3) people who are optimistic and who have a strong sense of meaning in life will rate their health more favorably over time than individuals who are not optimistic, as well as individuals who have not found a sense of meaning in life. Data from a longitudinal nationwide survey of older adults provided support for each of these hypotheses. PMID:21057586

Transfer of control system interface solutions from other domains to the thermal power industry.

PubMed

Bligård, L-O; Andersson, J; Osvalder, A-L

2012-01-01

In a thermal power plant the operators' roles are to control and monitor the process to achieve efficient and safe production. To achieve this, the human-machine interfaces have a central part. The interfaces need to be updated and upgraded together with the technical functionality to maintain optimal operation. One way of achieving relevant updates is to study other domains and see how they have solved similar issues in their design solutions. The purpose of this paper is to present how interface design solution ideas can be transferred from domains with operator control to thermal power plants. In the study 15 domains were compared using a model for categorisation of human-machine systems. The result from the domain comparison showed that nuclear power, refinery and ship engine control were most similar to thermal power control. From the findings a basic interface structure and three specific display solutions were proposed for thermal power control: process parameter overview, plant overview, and feed water view. The systematic comparison of the properties of a human-machine system allowed interface designers to find suitable objects, structures and navigation logics in a range of domains that could be transferred to the thermal power domain.

God-Mediated Control and Change in Self-Rated Health.

PubMed

Krause, Neal

2010-10-01

The purpose of this study was to see if feelings of God-mediated control are associated with change in self-rated health over time. In the process, an effort was made to see if a sense of meaning in life and optimism mediated the relationship between God-mediated control and change in health. The following hypothesized relationships were contained in the conceptual model that was developed to evaluate these issues: (1) people who go to church more often tend to have stronger God-mediated control beliefs than individuals who do not attend worship services as often; (2) people with a strong sense of God-mediated control are more likely to find a sense of meaning in life and be more optimistic than individuals who do not have a strong sense of God-mediated control; (3) people who are optimistic and who have a strong sense of meaning in life will rate their health more favorably over time than individuals who are not optimistic, as well as individuals who have not found a sense of meaning in life. Data from a longitudinal nationwide survey of older adults provided support for each of these hypotheses.

A Multiobjective Optimization Framework for Online Stochastic Optimal Control in Hybrid Electric Vehicles

DOE PAGES

Malikopoulos, Andreas

2015-01-01

The increasing urgency to extract additional efficiency from hybrid propulsion systems has led to the development of advanced power management control algorithms. In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain and we show that the control policy yielding the Pareto optimal solution minimizes online the long-run expected average cost per unit time criterion. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.more » Both solutions achieved the same cumulative fuel consumption demonstrating that the online Pareto control policy is an optimal control policy.« less

Computational alternatives to obtain time optimal jet engine control. M.S. Thesis

NASA Technical Reports Server (NTRS)

Basso, R. J.; Leake, R. J.

1976-01-01

Two computational methods to determine an open loop time optimal control sequence for a simple single spool turbojet engine are described by a set of nonlinear differential equations. Both methods are modifications of widely accepted algorithms which can solve fixed time unconstrained optimal control problems with a free right end. Constrained problems to be considered have fixed right ends and free time. Dynamic programming is defined on a standard problem and it yields a successive approximation solution to the time optimal problem of interest. A feedback control law is obtained and it is then used to determine the corresponding open loop control sequence. The Fletcher-Reeves conjugate gradient method has been selected for adaptation to solve a nonlinear optimal control problem with state variable and control constraints.

Implementation and on-sky results of an optimal wavefront controller for the MMT NGS adaptive optics system

NASA Astrophysics Data System (ADS)

Powell, Keith B.; Vaitheeswaran, Vidhya

2010-07-01

The MMT observatory has recently implemented and tested an optimal wavefront controller for the NGS adaptive optics system. Open loop atmospheric data collected at the telescope is used as the input to a MATLAB based analytical model. The model uses nonlinear constrained minimization to determine controller gains and optimize the system performance. The real-time controller performing the adaptive optics close loop operation is implemented on a dedicated high performance PC based quad core server. The controller algorithm is written in C and uses the GNU scientific library for linear algebra. Tests at the MMT confirmed the optimal controller significantly reduced the residual RMS wavefront compared with the previous controller. Significant reductions in image FWHM and increased peak intensities were obtained in J, H and K-bands. The optimal PID controller is now operating as the baseline wavefront controller for the MMT NGS-AO system.

Advanced Distribution Network Modelling with Distributed Energy Resources

NASA Astrophysics Data System (ADS)

O'Connell, Alison

The addition of new distributed energy resources, such as electric vehicles, photovoltaics, and storage, to low voltage distribution networks means that these networks will undergo major changes in the future. Traditionally, distribution systems would have been a passive part of the wider power system, delivering electricity to the customer and not needing much control or management. However, the introduction of these new technologies may cause unforeseen issues for distribution networks, due to the fact that they were not considered when the networks were originally designed. This thesis examines different types of technologies that may begin to emerge on distribution systems, as well as the resulting challenges that they may impose. Three-phase models of distribution networks are developed and subsequently utilised as test cases. Various management strategies are devised for the purposes of controlling distributed resources from a distribution network perspective. The aim of the management strategies is to mitigate those issues that distributed resources may cause, while also keeping customers' preferences in mind. A rolling optimisation formulation is proposed as an operational tool which can manage distributed resources, while also accounting for the uncertainties that these resources may present. Network sensitivities for a particular feeder are extracted from a three-phase load flow methodology and incorporated into an optimisation. Electric vehicles are the focus of the work, although the method could be applied to other types of resources. The aim is to minimise the cost of electric vehicle charging over a 24-hour time horizon by controlling the charge rates and timings of the vehicles. The results demonstrate the advantage that controlled EV charging can have over an uncontrolled case, as well as the benefits provided by the rolling formulation and updated inputs in terms of cost and energy delivered to customers. Building upon the rolling optimisation, a three-phase optimal power flow method is developed. The formulation has the capability to provide optimal solutions for distribution system control variables, for a chosen objective function, subject to required constraints. It can, therefore, be utilised for numerous technologies and applications. The three-phase optimal power flow is employed to manage various distributed resources, such as photovoltaics and storage, as well as distribution equipment, including tap changers and switches. The flexibility of the methodology allows it to be applied in both an operational and a planning capacity. The three-phase optimal power flow is employed in an operational planning capacity to determine volt-var curves for distributed photovoltaic inverters. The formulation finds optimal reactive power settings for a number of load and solar scenarios and uses these reactive power points to create volt-var curves. Volt-var curves are determined for 10 PV systems on a test feeder. A universal curve is also determined which is applicable to all inverters. The curves are validated by testing them in a power flow setting over a 24-hour test period. The curves are shown to provide advantages to the feeder in terms of reduction of voltage deviations and unbalance, with the individual curves proving to be more effective. It is also shown that adding a new PV system to the feeder only requires analysis for that system. In order to represent the uncertainties that inherently occur on distribution systems, an information gap decision theory method is also proposed and integrated into the three-phase optimal power flow formulation. This allows for robust network decisions to be made using only an initial prediction for what the uncertain parameter will be. The work determines tap and switch settings for a test network with demand being treated as uncertain. The aim is to keep losses below a predefined acceptable value. The results provide the decision maker with the maximum possible variation in demand for a given acceptable variation in the losses. A validation is performed with the resulting tap and switch settings being implemented, and shows that the control decisions provided by the formulation keep losses below the acceptable value while adhering to the limits imposed by the network.

Uncertainty-based simulation-optimization using Gaussian process emulation: Application to coastal groundwater management

NASA Astrophysics Data System (ADS)

Rajabi, Mohammad Mahdi; Ketabchi, Hamed

2017-12-01

Combined simulation-optimization (S/O) schemes have long been recognized as a valuable tool in coastal groundwater management (CGM). However, previous applications have mostly relied on deterministic seawater intrusion (SWI) simulations. This is a questionable simplification, knowing that SWI models are inevitably prone to epistemic and aleatory uncertainty, and hence a management strategy obtained through S/O without consideration of uncertainty may result in significantly different real-world outcomes than expected. However, two key issues have hindered the use of uncertainty-based S/O schemes in CGM, which are addressed in this paper. The first issue is how to solve the computational challenges resulting from the need to perform massive numbers of simulations. The second issue is how the management problem is formulated in presence of uncertainty. We propose the use of Gaussian process (GP) emulation as a valuable tool in solving the computational challenges of uncertainty-based S/O in CGM. We apply GP emulation to the case study of Kish Island (located in the Persian Gulf) using an uncertainty-based S/O algorithm which relies on continuous ant colony optimization and Monte Carlo simulation. In doing so, we show that GP emulation can provide an acceptable level of accuracy, with no bias and low statistical dispersion, while tremendously reducing the computational time. Moreover, five new formulations for uncertainty-based S/O are presented based on concepts such as energy distances, prediction intervals and probabilities of SWI occurrence. We analyze the proposed formulations with respect to their resulting optimized solutions, the sensitivity of the solutions to the intended reliability levels, and the variations resulting from repeated optimization runs.

Treatment of Thrombotic Antiphospholipid Syndrome: The Rationale of Current Management—An Insight into Future Approaches

PubMed Central

Ubiali, Tania; Meroni, Pier Luigi

2015-01-01

Vascular thrombosis and pregnancy morbidity represent the clinical manifestations of antiphospholipid syndrome (APS), which is serologically characterized by the persistent positivity of antiphospholipid antibodies (aPL). Antiplatelet and anticoagulant agents currently provide the mainstay of APS treatment. However, the debate is still open: controversies involve the intensity and the duration of anticoagulation and the treatment of stroke and refractory cases. Unfortunately, the literature cannot provide definite answers to these controversial issues as it is flawed by many limitations, mainly due to the recruitment of patients not fulfilling laboratory and clinical criteria for APS. The recommended therapeutic management of different aPL-related clinical manifestations is hereby presented, with a critical appraisal of the evidence supporting such approaches. Cutting edge therapeutic strategies are also discussed, presenting the pioneer reports about the efficacy of novel pharmacological agents in APS. Thanks to a better understanding of aPL pathogenic mechanisms, new therapeutic targets will soon be explored. Much work is still to be done to unravel the most controversial issues about APS management: future studies are warranted to define the optimal management according to aPL risk profile and to assess the impact of a strict control of cardiovascular risk factors on disease control. PMID:26075289

An optimized low-power voltage controlled oscillator

NASA Astrophysics Data System (ADS)

Shah, Kriyang; Le, Hai Phuong; Singh, Jugdutt

2007-01-01

This paper presents an optimised low-power low-phase-noise Voltage Controlled Oscillator (VCO) for Bluetooth wireless applications. The system level design issues and tradeoffs related to Direct Conversion Receiver (DCR) and Low Intermediate Frequency (IF) architecture for Bluetooth are discussed. Subsequently, for a low IF architecture, the critical VCO performance parameters are derived from system specifications. The VCO presented in the paper is optimised by implementing a novel biasing circuit that employs two current mirrors, one at the top and the other one at the bottom of the cross-coupled complementary VCO, to give the exact replica of the current in both the arms of current mirror circuit. This approach, therefore, significantly reduces the system power consumption as well as improves the system performance. Results show that, the VCO consumes only 281μW of power at 2V supply. Its phase noise performance are -115dBc/Hz, -130dBc/Hz and -141dBc/Hz at the offset frequency of 1MHz, 3MHz and 5MHz respectively. Results indicate that 31% reduction in power consumption is achieved as compared to the traditional VCO design. These characteristics make the designed VCO a better candidate for Bluetooth wireless application where power consumption is the major issue.

Mars transit vehicle thermal protection system: Issues, options, and trades

NASA Technical Reports Server (NTRS)

Brown, Norman

1986-01-01

A Mars mission is characterized by different mission phases. The thermal control of cryogenic propellant in a propulsive vehicle must withstand the different mission environments. Long term cryogenic storage may be achieved by passive or active systems. Passive cryo boiloff management features will include multilayer insulation, vapor cooled shield, and low conductance structural supports and penetrations. Active boiloff management incorporates the use of a refrigeration system. Key system trade areas include active verses passive system boiloff management (with respect to safety, reliability, and cost) and propellant tank insulation optimizations. Technology requirements include refrigeration technology advancements, insulation performance during long exposure, and cryogenic fluid transfer system for mission vehicle propellant tanking during vehicle buildip in LEO.

Effect of fossil fuels on the parameters of CO2 capture.

PubMed

Nagy, Tibor; Mizsey, Peter

2013-08-06

The carbon dioxide capture is a more and more important issue in the design and operation of boilers and/or power stations because of increasing environmental considerations. Such processes, absorber desorber should be able to cope with flue gases from the use of different fossil primary energy sources, in order to guarantee a flexible, stable, and secure energy supply operation. The changing flue gases have significant influence on the optimal operation of the capture process, that is, where the required heating of the desorber is the minimal. Therefore special considerations are devoted to the proper design and control of such boiler and/or power stations equipped with CO2 capture process.

Physical and Physiological Characteristics of Judo Athletes: An Update

PubMed Central

Torres-Luque, Gema; Hernández-García, Raquel; Escobar-Molina, Raquel; Garatachea, Nuria; Nikolaidis, Pantelis T.

2016-01-01

Judo competition is characterized structurally by weight category, which raises the importance of physiological control training in judo. The aim of the present review was to examine scientific papers on the physiological profile of the judokas, maintenance or loss of weight, framing issues, such as anthropometric parameters (body fat percentage), heart rate responses to training and combat, maximal oxygen uptake, hematological, biological and hormones indicators. The values shown in this review should be used as a reference for the evaluation of physical fitness and the effectiveness of training programs. Hence, this information is expected to contribute to the development of optimal training interventions aiming to achieve maximum athletic performance and to maintain the health of judokas.

Power Hardware-in-the-Loop (PHIL) Testing Facility for Distributed Energy Storage (Poster)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neubauer.J.; Lundstrom, B.; Simpson, M.

2014-06-01

The growing deployment of distributed, variable generation and evolving end-user load profiles presents a unique set of challenges to grid operators responsible for providing reliable and high quality electrical service. Mass deployment of distributed energy storage systems (DESS) has the potential to solve many of the associated integration issues while offering reliability and energy security benefits other solutions cannot. However, tools to develop, optimize, and validate DESS control strategies and hardware are in short supply. To fill this gap, NREL has constructed a power hardware-in-the-loop (PHIL) test facility that connects DESS, grid simulator, and load bank hardware to a distributionmore » feeder simulation.« less

The design of multirate digital control systems

NASA Technical Reports Server (NTRS)

Berg, M. C.

1986-01-01

The successive loop closures synthesis method is the only method for multirate (MR) synthesis in common use. A new method for MR synthesis is introduced which requires a gradient-search solution to a constrained optimization problem. Some advantages of this method are that the control laws for all control loops are synthesized simultaneously, taking full advantage of all cross-coupling effects, and that simple, low-order compensator structures are easily accomodated. The algorithm and associated computer program for solving the constrained optimization problem are described. The successive loop closures , optimal control, and constrained optimization synthesis methods are applied to two example design problems. A series of compensator pairs are synthesized for each example problem. The succesive loop closure, optimal control, and constrained optimization synthesis methods are compared, in the context of the two design problems.

Optimized Kernel Entropy Components.

PubMed

Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau

2017-06-01

This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.

Performance Analysis of a Semiactive Suspension System with Particle Swarm Optimization and Fuzzy Logic Control

PubMed Central

Qazi, Abroon Jamal; de Silva, Clarence W.

2014-01-01

This paper uses a quarter model of an automobile having passive and semiactive suspension systems to develop a scheme for an optimal suspension controller. Semi-active suspension is preferred over passive and active suspensions with regard to optimum performance within the constraints of weight and operational cost. A fuzzy logic controller is incorporated into the semi-active suspension system. It is able to handle nonlinearities through the use of heuristic rules. Particle swarm optimization (PSO) is applied to determine the optimal gain parameters for the fuzzy logic controller, while maintaining within the normalized ranges of the controller inputs and output. The performance of resulting optimized system is compared with different systems that use various control algorithms, including a conventional passive system, choice options of feedback signals, and damping coefficient limits. Also, the optimized semi-active suspension system is evaluated for its performance in relation to variation in payload. Furthermore, the systems are compared with respect to the attributes of road handling and ride comfort. In all the simulation studies it is found that the optimized fuzzy logic controller surpasses the other types of control. PMID:24574868

An optimal control strategies using vaccination and fogging in dengue fever transmission model

NASA Astrophysics Data System (ADS)

Fitria, Irma; Winarni, Pancahayani, Sigit; Subchan

2017-08-01

This paper discussed regarding a model and an optimal control problem of dengue fever transmission. We classified the model as human and vector (mosquito) population classes. For the human population, there are three subclasses, such as susceptible, infected, and resistant classes. Then, for the vector population, we divided it into wiggler, susceptible, and infected vector classes. Thus, the model consists of six dynamic equations. To minimize the number of dengue fever cases, we designed two optimal control variables in the model, the giving of fogging and vaccination. The objective function of this optimal control problem is to minimize the number of infected human population, the number of vector, and the cost of the controlling efforts. By giving the fogging optimally, the number of vector can be minimized. In this case, we considered the giving of vaccination as a control variable because it is one of the efforts that are being developed to reduce the spreading of dengue fever. We used Pontryagin Minimum Principle to solve the optimal control problem. Furthermore, the numerical simulation results are given to show the effect of the optimal control strategies in order to minimize the epidemic of dengue fever.

Optimal control on bladder cancer growth model with BCG immunotherapy and chemotherapy

NASA Astrophysics Data System (ADS)

Dewi, C.; Trisilowati

2015-03-01

In this paper, an optimal control model of the growth of bladder cancer with BCG (Basil Calmate Guerin) immunotherapy and chemotherapy is discussed. The purpose of this optimal control is to determine the number of BCG vaccine and drug should be given during treatment such that the growth of bladder cancer cells can be suppressed. Optimal control is obtained by applying Pontryagin principle. Furthermore, the optimal control problem is solved numerically using Forward-Backward Sweep method. Numerical simulations show the effectiveness of the vaccine and drug in controlling the growth of cancer cells. Hence, it can reduce the number of cancer cells that is not infected with BCG as well as minimize the cost of the treatment.

Dynamics and control of DNA sequence amplification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marimuthu, Karthikeyan; Chakrabarti, Raj, E-mail: raj@pmc-group.com, E-mail: rajc@andrew.cmu.edu; Division of Fundamental Research, PMC Advanced Technology, Mount Laurel, New Jersey 08054

2014-10-28

DNA amplification is the process of replication of a specified DNA sequence in vitro through time-dependent manipulation of its external environment. A theoretical framework for determination of the optimal dynamic operating conditions of DNA amplification reactions, for any specified amplification objective, is presented based on first-principles biophysical modeling and control theory. Amplification of DNA is formulated as a problem in control theory with optimal solutions that can differ considerably from strategies typically used in practice. Using the Polymerase Chain Reaction as an example, sequence-dependent biophysical models for DNA amplification are cast as control systems, wherein the dynamics of the reactionmore » are controlled by a manipulated input variable. Using these control systems, we demonstrate that there exists an optimal temperature cycling strategy for geometric amplification of any DNA sequence and formulate optimal control problems that can be used to derive the optimal temperature profile. Strategies for the optimal synthesis of the DNA amplification control trajectory are proposed. Analogous methods can be used to formulate control problems for more advanced amplification objectives corresponding to the design of new types of DNA amplification reactions.« less

Wetlands and Malaria in the Amazon: Guidelines for the Use of Synthetic Aperture Radar Remote-Sensing

PubMed Central

Catry, Thibault; Li, Zhichao; Roux, Emmanuel; Herbreteau, Vincent; Dessay, Nadine

2018-01-01

The prevention and control of mosquito-borne diseases, such as malaria, are important health issues in tropical areas. Malaria transmission is a multi-scale process strongly controlled by environmental factors, and the use of remote-sensing data is suitable for the characterization of its spatial and temporal dynamics. Synthetic aperture radar (SAR) is well-adapted to tropical areas, since it is capable of imaging independent of light and weather conditions. In this study, we highlight the contribution of SAR sensors in the assessment of the relationship between vectors, malaria and the environment in the Amazon region. More specifically, we focus on the SAR-based characterization of potential breeding sites of mosquito larvae, such as man-made water collections and natural wetlands, providing guidelines for the use of SAR capabilities and techniques in order to optimize vector control and malaria surveillance. In light of these guidelines, we propose a framework for the production of spatialized indicators and malaria risk maps based on the combination of SAR, entomological and epidemiological data to support malaria risk prevention and control actions in the field. PMID:29518988