Optimal Control Modification for Time-Scale Separated Systems
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2012-01-01
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.
Use of optimization in helicopter vibration control by structural modification
NASA Astrophysics Data System (ADS)
Done, G. T. S.; Rangacharyulu, M. A. V.
1981-02-01
The application of a mathematical optimization process to helicopter vibration control by structural modification is described. Attention is focused on the reduction of vibration in the crew area. With stiffness parameters as design variables, use is made of forced vibration response circles to identify the parameters most effective in controlling the response in the crew area, thereby reducing the number of available design variables to a tractable size. The problem of reducing vibration is then cast as a non-linear programming problem and a sequential unconstrained minimization technique incorporating an algorithm based on the methods of Davidon, Fletcher and Powell is used to determine the precise values of the parameters. The method is applied to a simple two-dimensional beam-element helicopter fuselage model and the results discussed. Although the model is too simple for useful deductions of practical significance to be made in the strictly engineering sense, the exercise does demonstrate what can and cannot be done in controlling vibration by using an optimization routine.
Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model
NASA Technical Reports Server (NTRS)
Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.
2010-01-01
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.
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.
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan
2009-01-01
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.
NASA Technical Reports Server (NTRS)
Nguyen, Nhan
2013-01-01
This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.
Optimal Control Modification Adaptive Law for Time-Scale Separated Systems
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.
Asymptotic Linearity of Optimal Control Modification Adaptive Law with Analytical Stability Margins
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
Optimal control modification has been developed to improve robustness to model-reference adaptive control. For systems with linear matched uncertainty, optimal control modification adaptive law can be shown by a singular perturbation argument to possess an outer solution that exhibits a linear asymptotic property. Analytical expressions of phase and time delay margins for the outer solution can be obtained. Using the gradient projection operator, a free design parameter of the adaptive law can be selected to satisfy stability margins.
Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)
2016-01-01
Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.
On Time Delay Margin Estimation for Adaptive Control and Optimal Control Modification
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2011-01-01
This paper presents methods for estimating time delay margin for adaptive control of input delay systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent an adaptive law by a locally bounded linear approximation within a small time window. The time delay margin of this input delay system represents a local stability measure and is computed analytically by three methods: Pade approximation, Lyapunov-Krasovskii method, and the matrix measure method. These methods are applied to the standard model-reference adaptive control, s-modification adaptive law, and optimal control modification adaptive law. The windowing analysis results in non-unique estimates of the time delay margin since it is dependent on the length of a time window and parameters which vary from one time window to the next. The optimal control modification adaptive law overcomes this limitation in that, as the adaptive gain tends to infinity and if the matched uncertainty is linear, then the closed-loop input delay system tends to a LTI system. A lower bound of the time delay margin of this system can then be estimated uniquely without the need for the windowing analysis. Simulation results demonstrates the feasibility of the bounded linear stability method for time delay margin estimation.
Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.
An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan
2008-01-01
This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.
Control and optimization system
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.
Optimal control computer programs
NASA Technical Reports Server (NTRS)
Kuo, F.
1992-01-01
The solution of the optimal control problem, even with low order dynamical systems, can usually strain the analytical ability of most engineers. The understanding of this subject matter, therefore, would be greatly enhanced if a software package existed that could simulate simple generic problems. Surprisingly, despite a great abundance of commercially available control software, few, if any, address the part of optimal control in its most generic form. The purpose of this paper is, therefore, to present a simple computer program that will perform simulations of optimal control problems that arise from the first necessary condition and the Pontryagin's maximum principle.
Integrated controls design optimization
Lou, Xinsheng; Neuschaefer, Carl H.
2015-09-01
A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.
Fuzzy logic controller optimization
Sepe, Jr., Raymond B; Miller, John Michael
2004-03-23
A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.
Johnson, E.A.; Leung, C.; Schira, J.J.
1983-03-01
A closed loop timing optimization control for an internal combustion engine closed about the instantaneous rotational velocity of the engine's crankshaft is disclosed herein. The optimization control computes from the instantaneous rotational velocity of the engine's crankshaft, a signal indicative of the angle at which the crankshaft has a maximum rotational velocity for the torque impulses imparted to the engine's crankshaft by the burning of an air/fuel mixture in each of the engine's combustion chambers and generates a timing correction signal for each of the engine's combustion chambers. The timing correction signals, applied to the engine timing control, modifies the time at which the ignition signal, injection signals or both are generated such that the rotational velocity of the engine's crankshaft has a maximum value at a predetermined angle for each torque impulse generated optimizing the conversion of the combustion energy to rotational torque.
Cluster optimization simplified by interaction modification
NASA Astrophysics Data System (ADS)
Stillinger, Frank H.; Stillinger, Dorothea K.
1990-10-01
Even when interactions are known exactly, it is generally very difficult to determine the lowest-energy configuration (a global potential energy minimum) for clusters with more than very few atoms or molecules. In mathematical parlance this is an NP-complete problem. A nonlinear optimization strategy, the ``ant-lion method,'' has been proposed to accelerate the search for global minima, and works by adroitly deforming the potential surface to produce overwhelming dominance by global minimum potential energy basins. This strategy is illustrated by application to clusters of 13 noble gas atoms. Monte Carlo results demonstrate that reduction of p in the pair potential 4(r-2p-r-p) below the ``physical'' value 6 produces a dramatic rise to essentially unity in probability of random encounter with the global minimum basins (icosahedral clusters).
Adaptive Control with Reference Model Modification
NASA Technical Reports Server (NTRS)
Stepanyan, Vahram; Krishnakumar, Kalmanje
2012-01-01
This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example
Modification of species-based differential evolution for multimodal optimization
NASA Astrophysics Data System (ADS)
Idrus, Said Iskandar Al; Syahputra, Hermawan; Firdaus, Muliawan
2015-12-01
At this time optimization has an important role in various fields as well as between other operational research, industry, finance and management. Optimization problem is the problem of maximizing or minimizing a function of one variable or many variables, which include unimodal and multimodal functions. Differential Evolution (DE), is a random search technique using vectors as an alternative solution in the search for the optimum. To localize all local maximum and minimum on multimodal function, this function can be divided into several domain of fitness using niching method. Species-based niching method is one of method that build sub-populations or species in the domain functions. This paper describes the modification of species-based previously to reduce the computational complexity and run more efficiently. The results of the test functions show species-based modifications able to locate all the local optima in once run the program.
NASA Technical Reports Server (NTRS)
Allan, Brian; Owens, Lewis
2010-01-01
In support of the Blended-Wing-Body aircraft concept, a new flow control hybrid vane/jet design has been developed for use in a boundary-layer-ingesting (BLI) offset inlet in transonic flows. This inlet flow control is designed to minimize the engine fan-face distortion levels and the first five Fourier harmonic half amplitudes while maximizing the inlet pressure recovery. This concept represents a potentially enabling technology for quieter and more environmentally friendly transport aircraft. An optimum vane design was found by minimizing the engine fan-face distortion, DC60, and the first five Fourier harmonic half amplitudes, while maximizing the total pressure recovery. The optimal vane design was then used in a BLI inlet wind tunnel experiment at NASA Langley's 0.3-meter transonic cryogenic tunnel. The experimental results demonstrated an 80-percent decrease in DPCPavg, the reduction in the circumferential distortion levels, at an inlet mass flow rate corresponding to the middle of the operational range at the cruise condition. Even though the vanes were designed at a single inlet mass flow rate, they performed very well over the entire inlet mass flow range tested in the wind tunnel experiment with the addition of a small amount of jet flow control. While the circumferential distortion was decreased, the radial distortion on the outer rings at the aerodynamic interface plane (AIP) increased. This was a result of the large boundary layer being distributed from the bottom of the AIP in the baseline case to the outer edges of the AIP when using the vortex generator (VG) vane flow control. Experimental results, as already mentioned, showed an 80-percent reduction of DPCPavg, the circumferential distortion level at the engine fan-face. The hybrid approach leverages strengths of vane and jet flow control devices, increasing inlet performance over a broader operational range with significant reduction in mass flow requirements. Minimal distortion level requirements
Post-translational Modification and Quality Control
Wang, Xuejun; Pattison, J. Scott; Su, Huabo
2013-01-01
Protein quality control (PQC) functions to minimize the level and toxicity of misfolded proteins in the cell. PQC is performed by intricate collaboration among chaperones and target protein degradation. The latter is carried out primarily by the ubiquitin-proteasome system and perhaps autophagy. Terminally misfolded proteins that are not timely removed tend to form aggregates. Their clearance requires macroautophagy. Macroautophagy serves in intracellular quality control also by selectively segregating defective organelles (e.g., mitochondria) and targeting them for degradation by the lysosome. Inadequate PQC is observed in a large subset of failing human hearts with a variety of etiologies and its pathogenic role has been experimentally demonstrated. Multiple post-translational modifications (PTMs) can occur to substrate proteins and/or PQC machineries, promoting or hindering the removal of the misfolded proteins. This article highlights recent advances in PTMs-mediated regulation of intracellular quality control mechanisms and its known involvement in cardiac pathology. PMID:23329792
COBRA-SFS modifications and cask model optimization
Rector, D.R.; Michener, T.E.
1989-01-01
Spent-fuel storage systems are complex systems and developing a computational model for one can be a difficult task. The COBRA-SFS computer code provides many capabilities for modeling the details of these systems, but these capabilities can also allow users to specify a more complex model than necessary. This report provides important guidance to users that dramatically reduces the size of the model while maintaining the accuracy of the calculation. A series of model optimization studies was performed, based on the TN-24P spent-fuel storage cask, to determine the optimal model geometry. Expanded modeling capabilities of the code are also described. These include adding fluid shear stress terms and a detailed plenum model. The mathematical models for each code modification are described, along with the associated verification results. 22 refs., 107 figs., 7 tabs.
Optimally Controlled Flexible Fuel Powertrain System
Hakan Yilmaz; Mark Christie; Anna Stefanopoulou
2010-12-31
The primary objective of this project was to develop a true Flex Fuel Vehicle capable of running on any blend of ethanol from 0 to 85% with reduced penalty in usable vehicle range. A research and development program, targeting 10% improvement in fuel economy using a direct injection (DI) turbocharged spark ignition engine was conducted. In this project a gasoline-optimized high-technology engine was considered and the hardware and configuration modifications were defined for the engine, fueling system, and air path. Combined with a novel engine control strategy, control software, and calibration this resulted in a highly efficient and clean FFV concept. It was also intended to develop robust detection schemes of the ethanol content in the fuel integrated with adaptive control algorithms for optimized turbocharged direct injection engine combustion. The approach relies heavily on software-based adaptation and optimization striving for minimal modifications to the gasoline-optimized engine hardware system. Our ultimate objective was to develop a compact control methodology that takes advantage of any ethanol-based fuel mixture and not compromise the engine performance under gasoline operation.
Robust Optimal Adaptive Control Method with Large Adaptive Gain
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2009-01-01
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.
Metacognitive Control and Optimal Learning
ERIC Educational Resources Information Center
Son, Lisa K.; Sethi, Rajiv
2006-01-01
The notion of optimality is often invoked informally in the literature on metacognitive control. We provide a precise formulation of the optimization problem and show that optimal time allocation strategies depend critically on certain characteristics of the learning environment, such as the extent of time pressure, and the nature of the uptake…
Supercomputer optimizations for stochastic optimal control applications
NASA Technical Reports Server (NTRS)
Chung, Siu-Leung; Hanson, Floyd B.; Xu, Huihuang
1991-01-01
Supercomputer optimizations for a computational method of solving stochastic, multibody, dynamic programming problems are presented. The computational method is valid for a general class of optimal control problems that are nonlinear, multibody dynamical systems, perturbed by general Markov noise in continuous time, i.e., nonsmooth Gaussian as well as jump Poisson random white noise. Optimization techniques for vector multiprocessors or vectorizing supercomputers include advanced data structures, loop restructuring, loop collapsing, blocking, and compiler directives. These advanced computing techniques and superconducting hardware help alleviate Bellman's curse of dimensionality in dynamic programming computations, by permitting the solution of large multibody problems. Possible applications include lumped flight dynamics models for uncertain environments, such as large scale and background random aerospace fluctuations.
Fuel consumption in optimal control
NASA Technical Reports Server (NTRS)
Redmond, Jim; Silverberg, Larry
1992-01-01
A method has been developed for comparing three optimal control strategies based on fuel consumption. A general cost function minimization procedure was developed by applying two theorems associated with convex sets. Three cost functions associated with control saturation, pseudofuel, and absolute fuel are introduced and minimized. The first two cost functions led to the bang-bang and continuous control strategies, and the minimization of absolute fuel led to an impulsive strategy. The three control strategies were implemented on two elementary systems and a comparison of fuel consumption was made. The impulse control strategy consumes significantly less fuel than the continuous and bang-bang control strategies. This comparison suggests a potential for fuel savings in higher-order systems using impulsive control strategies. However, since exact solutions to fuel-optimal control for large-order systems are difficult if not impossible to achieve, the alternative is to develop near-optimal control strategies.
Optimal control for electron shuttling
NASA Astrophysics Data System (ADS)
Zhang, Jun; Greenman, Loren; Deng, Xiaotian; Hayes, Ian M.; Whaley, K. Birgitta
2013-06-01
In this paper we apply an optimal control technique to derive control fields that transfer an electron between ends of a chain of donors or quantum dots. We formulate the transfer as an optimal steering problem, and then derive the dynamics of the optimal control. A numerical algorithm is developed to effectively generate control pulses. We apply this technique to transfer an electron between sites of a triple quantum dot and an ionized chain of phosphorus dopants in silicon. Using the optimal pulses for the spatial shuttling of phosphorus dopants, we then add hyperfine interactions to the Hamiltonian and show that a 500 G magnetic field will transfer the electron spatially as well as transferring the spin components of two of the four hyperfine states of the electron-nuclear spin pair.
Optimization of Airfoil Design for Flow Control with Plasma Actuators
NASA Astrophysics Data System (ADS)
Williams, Theodore; Corke, Thomas; Cooney, John
2011-11-01
Using computer simulations and design optimization methods, this research examines the implementation of active flow control devices on wind turbine blades. Through modifications to blade geometry in order to maximize the effectiveness of flow control devices, increases in aerodynamic performance and control of aerodynamic performance are expected. Due to this compliant flow, an increase in the power output of wind turbines is able to be realized with minimal modification and investment to existing turbine blades. This is achieved through dynamic lift control via virtual camber control. Methods using strategic flow separation near the trailing edge are analyzed to obtain desired aerodynamic performance. FLUENT is used to determine the aerodynamic performance of potential turbine blade design, and the post-processing uses optimization techniques to determine an optimal blade geometry and plasma actuator operating parameters. This work motivates the research and development of novel blade designs with flow control devices that will be tested at Notre Dame's Laboratory for Enhanced Wind Energy Design.
Optimal control of motorsport differentials
NASA Astrophysics Data System (ADS)
Tremlett, A. J.; Massaro, M.; Purdy, D. J.; Velenis, E.; Assadian, F.; Moore, A. P.; Halley, M.
2015-12-01
Modern motorsport limited slip differentials (LSD) have evolved to become highly adjustable, allowing the torque bias that they generate to be tuned in the corner entry, apex and corner exit phases of typical on-track manoeuvres. The task of finding the optimal torque bias profile under such varied vehicle conditions is complex. This paper presents a nonlinear optimal control method which is used to find the minimum time optimal torque bias profile through a lane change manoeuvre. The results are compared to traditional open and fully locked differential strategies, in addition to considering related vehicle stability and agility metrics. An investigation into how the optimal torque bias profile changes with reduced track-tyre friction is also included in the analysis. The optimal LSD profile was shown to give a performance gain over its locked differential counterpart in key areas of the manoeuvre where a quick direction change is required. The methodology proposed can be used to find both optimal passive LSD characteristics and as the basis of a semi-active LSD control algorithm.
Optimal control of native predators
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.
Optimization approaches to nonlinear model predictive control
Biegler, L.T. . Dept. of Chemical Engineering); Rawlings, J.B. . Dept. of Chemical Engineering)
1991-01-01
With the development of sophisticated methods for nonlinear programming and powerful computer hardware, it now becomes useful and efficient to formulate and solve nonlinear process control problems through on-line optimization methods. This paper explores and reviews control techniques based on repeated solution of nonlinear programming (NLP) problems. Here several advantages present themselves. These include minimization of readily quantifiable objectives, coordinated and accurate handling of process nonlinearities and interactions, and systematic ways of dealing with process constraints. We motivate this NLP-based approach with small nonlinear examples and present a basic algorithm for optimization-based process control. As can be seen this approach is a straightforward extension of popular model-predictive controllers (MPCs) that are used for linear systems. The statement of the basic algorithm raises a number of questions regarding stability and robustness of the method, efficiency of the control calculations, incorporation of feedback into the controller and reliable ways of handling process constraints. Each of these will be treated through analysis and/or modification of the basic algorithm. To highlight and support this discussion, several examples are presented and key results are examined and further developed. 74 refs., 11 figs.
Unifying process control and optimization
Makansi, J.
2005-09-01
About 40% of US generation is now subject to wholesale competition. To intelligently bid into these new markets, real-time prices must be aligned with real-time costs. It is time to integrate the many advanced applications, sensors, and analyzers used for control, automation, and optimization into a system that reflects process and financial objectives. The paper reports several demonstration projects in the USA revealing what is being done in the area of advanced process optimization (by Alliant Energy, American Electric Power, PacifiCorp, Detroit Edison and Tennessee Valley Authority). In addition to these projects US DOE's NETL has funded the plant environment and cost optimization system, PECOS which combines physical models, neural networks and fuzzy logic control to provide operators with least cost setpoints for controllable variables. At Dynegy Inc's Baldwin station in Illinois the DOE is subsidizing a project where real time, closed-loop IT systems will optimize combustion, soot-blowing and SCR performance as well as unit thermal performance and plant economic performance. Commercial products such as Babcock and Wilcox's Flame Doctor, continuous emissions monitoring systems and various real-time predictive monitoring systems are also available. 4 figs.
Optimal woofer tweeter control demonstration
NASA Astrophysics Data System (ADS)
Le Roux, B.; El Hadi, K.; NDiaye, M.; Gray, M.
2011-09-01
Large aperture telescope adaptive optics incorporates several deformable and active mirrors. Several options have been proposed for several DM adaptive optics systems. We study an optimal control approach for these woofer tweeter systems based on a Kalman filtering method. This approach allows to share out the spatial energy of correction between the mirrors and to deal with different temporal response time. The approach is presented and a validation of the control method is carried out in a numerical simulation. We finally present the experimental validation of such control solutions for woofer-tweeter systems. The validation bench and the optical components are presented and the first experimental results are shown.
Optimal control of hydroelectric facilities
NASA Astrophysics Data System (ADS)
Zhao, Guangzhi
This thesis considers a simple yet realistic model of pump-assisted hydroelectric facilities operating in a market with time-varying but deterministic power prices. Both deterministic and stochastic water inflows are considered. The fluid mechanical and engineering details of the facility are described by a model containing several parameters. We present a dynamic programming algorithm for optimizing either the total energy produced or the total cash generated by these plants. The algorithm allows us to give the optimal control strategy as a function of time and to see how this strategy, and the associated plant value, varies with water inflow and electricity price. We investigate various cases. For a single pumped storage facility experiencing deterministic power prices and water inflows, we investigate the varying behaviour for an oversimplified constant turbine- and pump-efficiency model with simple reservoir geometries. We then generalize this simple model to include more realistic turbine efficiencies, situations with more complicated reservoir geometry, and the introduction of dissipative switching costs between various control states. We find many results which reinforce our physical intuition about this complicated system as well as results which initially challenge, though later deepen, this intuition. One major lesson of this work is that the optimal control strategy does not differ much between two differing objectives of maximizing energy production and maximizing its cash value. We then turn our attention to the case of stochastic water inflows. We present a stochastic dynamic programming algorithm which can find an on-average optimal control in the face of this randomness. As the operator of a facility must be more cautious when inflows are random, the randomness destroys facility value. Following this insight we quantify exactly how much a perfect hydrological inflow forecast would be worth to a dam operator. In our final chapter we discuss the
Combined control-structure optimization
NASA Technical Reports Server (NTRS)
Salama, M.; Milman, M.; Bruno, R.; Scheid, R.; Gibson, S.
1989-01-01
An approach for combined control-structure optimization keyed to enhancing early design trade-offs is outlined and illustrated by numerical examples. The approach employs a homotopic strategy and appears to be effective for generating families of designs that can be used in these early trade studies. Analytical results were obtained for classes of structure/control objectives with linear quadratic Gaussian (LQG) and linear quadratic regulator (LQR) costs. For these, researchers demonstrated that global optima can be computed for small values of the homotopy parameter. Conditions for local optima along the homotopy path were also given. Details of two numerical examples employing the LQR control cost were given showing variations of the optimal design variables along the homotopy path. The results of the second example suggest that introducing a second homotopy parameter relating the two parts of the control index in the LQG/LQR formulation might serve to enlarge the family of Pareto optima, but its effect on modifying the optimal structural shapes may be analogous to the original parameter lambda.
Optimal control and Galois theory
Zelikin, M I; Kiselev, D D; Lokutsievskiy, L V
2013-11-30
An important role is played in the solution of a class of optimal control problems by a certain special polynomial of degree 2(n−1) with integer coefficients. The linear independence of a family of k roots of this polynomial over the field Q implies the existence of a solution of the original problem with optimal control in the form of an irrational winding of a k-dimensional Clifford torus, which is passed in finite time. In the paper, we prove that for n≤15 one can take an arbitrary positive integer not exceeding [n/2] for k. The apparatus developed in the paper is applied to the systems of Chebyshev-Hermite polynomials and generalized Chebyshev-Laguerre polynomials. It is proved that for such polynomials of degree 2m every subsystem of [(m+1)/2] roots with pairwise distinct squares is linearly independent over the field Q. Bibliography: 11 titles.
Optimal control in a macroeconomic problem
NASA Astrophysics Data System (ADS)
Bulgakov, V. K.; Shatov, G. L.
2007-08-01
The Pontryagin maximum principle is used to develop an original algorithm for finding an optimal control in a macroeconomic problem. Numerical results are presented for the optimal control and optimal trajectory of the development of a regional economic system. For an optimal control satisfying a certain constraint, an invariant of a macroeconomic system is derived.
An optimal modification of a Kalman filter for time scales
NASA Technical Reports Server (NTRS)
Greenhall, C. A.
2003-01-01
The Kalman filter in question, which was implemented in the time scale algorithm TA(NIST), produces time scales with poor short-term stability. A simple modification of the error covariance matrix allows the filter to produce time scales with good stability at all averaging times, as verified by simulations of clock ensembles.
A coordinated approach to control system modifications
Lance, G.J.; Babuka, R.D.; Ricker, S.
1995-10-01
This paper describes the structured approach to a major control system retrofit. The project included replacing out-dated controls hardware with a distributed control system as part of a low NO{sub x} conversion project. The success of the coordinated approach used for this project depended on many key factors. The most important factor was strength of the EKPC/B and W relationship that united B and W design and installation expertise with EKPC operations. This relationship provided a comprehensive forum for information exchange between all parties involved. The design documents (P and IDs, SRSs, I/O Lists, and SITs) provided a conduit for technical information exchange. The integrated schedule was used as a dynamic road map to drive, guide and coordinate the project. The schedule provided direction to all contributing organizations through the engineering, installation, and start-up phases. The labor partnering approach to electrical and instrumentation installation infused valuable installation expertise into the project. The lessons learned sessions provided important performance feedback. These sessions measured the effectiveness of overall communication and led to process improvement. The success of this project is directly attributable to the dedication and coordinated approach of the EKPC/B and W project team.
Optimal control of overdamped systems.
Zulkowski, Patrick R; DeWeese, Michael R
2015-09-01
Nonequilibrium physics encompasses a broad range of natural and synthetic small-scale systems. Optimizing transitions of such systems will be crucial for the development of nanoscale technologies and may reveal the physical principles underlying biological processes at the molecular level. Recent work has demonstrated that when a thermodynamic system is driven away from equilibrium then the space of controllable parameters has a Riemannian geometry induced by a generalized inverse diffusion tensor. We derive a simple, compact expression for the inverse diffusion tensor that depends solely on equilibrium information for a broad class of potentials. We use this formula to compute the minimal dissipation for two model systems relevant to small-scale information processing and biological molecular motors. In the first model, we optimally erase a single classical bit of information modeled by an overdamped particle in a smooth double-well potential. In the second model, we find the minimal dissipation of a simple molecular motor model coupled to an optical trap. In both models, we find that the minimal dissipation for the optimal protocol of duration τ is proportional to 1/τ, as expected, though the dissipation for the erasure model takes a different form than what we found previously for a similar system. PMID:26465436
HCCI Engine Optimization and Control
Rolf D. Reitz
2005-09-30
The goal of this project was to develop methods to optimize and control Homogeneous-Charge Compression Ignition (HCCI) engines, with emphasis on diesel-fueled engines. HCCI offers the potential of nearly eliminating IC engine NOx and particulate emissions at reduced cost over Compression Ignition Direct Injection engines (CIDI) by controlling pollutant emissions in-cylinder. The project was initiated in January, 2002, and the present report is the final report for work conducted on the project through December 31, 2004. Periodic progress has also been reported at bi-annual working group meetings held at USCAR, Detroit, MI, and at the Sandia National Laboratories. Copies of these presentation materials are available on CD-ROM, as distributed by the Sandia National Labs. In addition, progress has been documented in DOE Advanced Combustion Engine R&D Annual Progress Reports for FY 2002, 2003 and 2004. These reports are included as the Appendices in this Final report.
Servo Controlled Variable Pressure Modification to Space Shuttle Hydraulic Pump
NASA Technical Reports Server (NTRS)
Kouns, H. H.
1983-01-01
Engineering drawings show modifications made to the constant pressure control of the model AP27V-7 hydraulic pump to an electrically controlled variable pressure setting compensator. A hanger position indicator was included for continuously monitoring hanger angle. A simplex servo driver was furnished for controlling the pressure setting servovalve. Calibration of the rotary variable displacement transducer is described as well as pump performance and response characteristics.
Adaptive, predictive controller for optimal process control
Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.
1995-12-01
One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.
Optimal control of sun tracking solar concentrators
NASA Technical Reports Server (NTRS)
Hughes, R. O.
1979-01-01
Application of the modern control theory to derive an optimal sun tracking control for a point focusing solar concentrator is presented. A standard tracking problem converted to regulator problem using a sun rate input achieves an almost zero steady state tracking error with the optimal control formulation. However, these control techniques are costly because optimal type algorithms require large computing systems, thus they will be used mainly as comparison standards for other types of control algorithms and help in their development.
Fuzzy logic control and optimization system
Lou, Xinsheng
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.
CFD analysis to optimize a design modification of BSMT
NASA Technical Reports Server (NTRS)
Ratcliff, Mark; Avva, Ram; Williams, Robert
1992-01-01
The Bearings, Seals and Materials Tester (BSMT) is a test article being used at MSFC to evaluate the performance of conventional rolling contact bearings. Pressure differentials between the BSMT inlet and exit cavities are found to cause large parasitic axial loads on the bearing-carrier walls. These parasitic loads, besides being detrimental to the life of bearings, make the testing and evaluation of bearing performance very difficult, and need to be eliminated if at all possible. The objectives of this study are to estimate the hydrodynamic loads on the bearings and to recommend feasible design modifications for BSMT to eliminate the parasitic loads. Three-dimensional computational analyses of inlet and exit cavities in their baseline configuration were performed with REFLEQS which is an advanced finite-volume Navier-Stokes code. Computations were performed with and without a 1/4 inch diameter temperature probe included in each of the cavities. The results of the analyses indicate that the temperature probes substantially alter the flow field and reduce the pressure drop/rise in the cavities. The overall pressure drop across the tester compares quite well with the measurements.
Burner modifications for cost effective NO{sub x} control
Melick, T.A.; Payne, R.; Kersch, J.
1999-11-01
Low NO{sub x} Burners achieve their NO{sub x} reduction principally by control of the rate of fuel/air mixing. Based on many years of low NO{sub x} burner development experience for wall fired applications, Energy and Environmental Research Corporation (EER) has found that low NO{sub x} fuel/air mixing conditions can be incorporated into conventional burners by modifying the burners as an alternative to complete burner replacement. The NO{sub x} control achieved with such Low NO{sub x} Burner Modifications is, in many cases, comparable to that of new burners but the cost to the utility is much lower. This paper presents an update on EER`s experience in applying Low NO{sub x} Burner Modifications to circular burners focusing on Delmarva Power and Light`s (Connectiv) Indian River Station.
Effects of modifications to the space shuttle entry guidance and control systems
NASA Technical Reports Server (NTRS)
Powell, R. W.; Stone, H. W.; Rowell, L. F.
1976-01-01
A nonlinear six degree of freedom entry simulation study was conducted to identify space shuttle guidance and control system software modifications which reduce the control system sensitivity to the guidance system sampling frequency. Several modifications which eliminated the control system sensitivity and associated control limit cycling were examined. The result of the modifications was a reduction in required reaction control system fuel.
Optimal singular control with applications to trajectory optimization
NASA Technical Reports Server (NTRS)
Vinh, N. X.
1977-01-01
A comprehensive discussion of the problem of singular control is presented. Singular control enters an optimal trajectory when the so called switching function vanishes identically over a finite time interval. Using the concept of domain of maneuverability, the problem of optical switching is analyzed. Criteria for the optimal direction of switching are presented. The switching, or junction, between nonsingular and singular subarcs is examined in detail. Several theorems concerning the necessary, and also sufficient conditions for smooth junction are presented. The concepts of quasi-linear control and linearized control are introduced. They are designed for the purpose of obtaining approximate solution for the difficult Euler-Lagrange type of optimal control in the case where the control is nonlinear.
Adaptive optimization and control using neural networks
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
1993-10-22
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
Optimizing Dynamical Network Structure for Pinning Control
Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo
2016-01-01
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. PMID:27067020
Optimizing Dynamical Network Structure for Pinning Control.
Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo
2016-01-01
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. PMID:27067020
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.
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.
Optimal management strategies in variable environments: Stochastic optimal control methods
Williams, B.K.
1985-01-01
Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both
Semiclassical guided optimal control of molecular dynamics
Kondorskiy, A.; Mil'nikov, G.; Nakamura, H.
2005-10-15
An efficient semiclassical optimal control theory applicable to multidimensional systems is formulated for controlling wave packet dynamics on a single adiabatic potential energy surface. The approach combines advantages of different formulations of optimal control theory: quantum and classical on one hand and global and local on the other. Numerical applications to the control of HCN-CNH isomerization demonstrate that this theory can provide an efficient tool to manipulate molecular dynamics of many degrees of freedom by laser pulses.
NASA Astrophysics Data System (ADS)
Chang, Shinn-Liang; Liu, Jia-Hung
2009-10-01
Gears are the most important components in transmission systems. Modifications of gear teeth can accommodate errors and deformations encountered in the manufacture, assembly, and operation of gear pairs. For plunge shaving gears with tooth modifications, the design criteria of cutter clearance manufactured by protuberance hob cutter is investigated. With this novel design, the cutter has better strength and stiffness to keep the shaved gear profile stable. With the analytical descriptions of crowned gear and hence plunge shaving cutter have been constructed so that the grinding wheel can be optimized to minimized the topographic error. Efficiency is greatly improved by avoiding the traditional trial and error method.
NRMRL's Air Pollution Prevention and Control Division's Air Pollution Technology Branch has performed research and developed technologies for NOx reduction via combustion modification. Techniques such as low-excess air firing, staged combustion, flue gas recirculation, low NOx bu...
Linear optimal control of tokamak fusion devices
Kessel, C.E.; Firestone, M.A.; Conn, R.W.
1989-05-01
The control of plasma position, shape and current in a tokamak fusion reactor is examined using linear optimal control. These advanced tokamaks are characterized by non up-down symmetric coils and structure, thick structure surrounding the plasma, eddy currents, shaped plasmas, superconducting coils, vertically unstable plasmas, and hybrid function coils providing ohmic heating, vertical field, radial field, and shaping field. Models of the electromagnetic environment in a tokamak are derived and used to construct control gains that are tested in nonlinear simulations with initial perturbations. The issues of applying linear optimal control to advanced tokamaks are addressed, including complex equilibrium control, choice of cost functional weights, the coil voltage limit, discrete control, and order reduction. Results indicate that the linear optimal control is a feasible technique for controlling advanced tokamaks where the more common classical control will be severely strained or will not work. 28 refs., 13 figs.
Dynamic optimization and adaptive controller design
NASA Astrophysics Data System (ADS)
Inamdar, S. R.
2010-10-01
In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.
Role of controllability in optimizing quantum dynamics
Wu Rebing; Hsieh, Michael A.; Rabitz, Herschel
2011-06-15
This paper reveals an important role that controllability plays in the complexity of optimizing quantum control dynamics. We show that the loss of controllability generally leads to multiple locally suboptimal controls when gate fidelity in a quantum control system is maximized, which does not happen if the system is controllable. Such local suboptimal controls may attract an optimization algorithm into a local trap when a global optimal solution is sought, even if the target gate can be perfectly realized. This conclusion results from an analysis of the critical topology of the corresponding quantum control landscape, which refers to the gate fidelity objective as a functional of the control fields. For uncontrollable systems, due to SU(2) and SU(3) dynamical symmetries, the control landscape corresponding to an implementable target gate is proven to possess multiple locally optimal critical points, and its ruggedness can be further increased if the target gate is not realizable. These results imply that the optimization of quantum dynamics can be seriously impeded when operating with local search algorithms under these conditions, and thus full controllability is demanded.
Optimal Control of Evolution Mixed Variational Inclusions
Alduncin, Gonzalo
2013-12-15
Optimal control problems of primal and dual evolution mixed variational inclusions, in reflexive Banach spaces, are studied. The solvability analysis of the mixed state systems is established via duality principles. The optimality analysis is performed in terms of perturbation conjugate duality methods, and proximation penalty-duality algorithms to mixed optimality conditions are further presented. Applications to nonlinear diffusion constrained problems as well as quasistatic elastoviscoplastic bilateral contact problems exemplify the theory.
Direct Optimal Control of Duffing Dynamics
NASA Technical Reports Server (NTRS)
Oz, Hayrani; Ramsey, John K.
2002-01-01
The "direct control method" is a novel concept that is an attractive alternative and competitor to the differential-equation-based methods. The direct method is equally well applicable to nonlinear, linear, time-varying, and time-invariant systems. For all such systems, the method yields explicit closed-form control laws based on minimization of a quadratic control performance measure. We present an application of the direct method to the dynamics and optimal control of the Duffing system where the control performance measure is not restricted to a quadratic form and hence may include a quartic energy term. The results we present in this report also constitute further generalizations of our earlier work in "direct optimal control methodology." The approach is demonstrated for the optimal control of the Duffing equation with a softening nonlinear stiffness.
An intellignet controller for optimized sootblowing
Baldridge, D.; Bangham, M.; Gratcheva, K.
1996-05-01
Efficiency losses of over 200 Btu/KWH have been attributed to sub-optimal control of sootblowers in coal-fired boilers, frequently accounting for over 80% of the controllable losses. For a 500 MW power plant, this translates into yearly costs of over $1 M. The primary impediment to sootblowing optimization to date has been the difficulty associated with modeling the relationship between sootblowing, and boiler efficiency. New advances in neural network technology now provide an attractive approach to address this issue. This paper presents results to date of a project currently under way at DHR Technologies, Inc. (DHR), George Washington University (GWU), and Baltimore Gas and Electric Company (BGE), with funding provided by the Department of Energy (DOE), to develop an Intelligent Controller for Optimized Sootblowing (ICOS). The ICOS system combines a neural network-based process model with an optimization algorithm to provide automated, optimized control of steam or compressed air sootblowers for fossil utility boilers. In Phase I of the project, the proposed optimization approach was tested and validated using data from BGE`s Brandon Shores Station. Phase I quantified the expected savings of the controller and verified the effectiveness of the proposed technical approach. In Phase II, the control algorithm will be incorporated into DHR`s TOPAZ{trademark} optimization system and interfaced with Brandon Shore`s Diamond Power sootblowing controller, and will be demonstrated and tested for closed-loop, optimal sootblowing control. The savings achieved through use of the ICOS controller during testing will also be quantified.
Optimal torque control for SCOLE slewing maneuvers
NASA Technical Reports Server (NTRS)
Bainum, P. M.; Li, Feiyue
1987-01-01
The Spacecraft Control Laboratory Experiment (SCOLE) was slewed from one attitude to the required attitude and an integral performance index which involves the control torques was minimized. Kinematic and dynamical equations, optimal control, two-point boundary-value problems, and estimation of unknown boundary conditions are presented.
Optimal controller design for structural damage detection
NASA Astrophysics Data System (ADS)
Lew, Jiann-Shiun
2005-03-01
The virtual passive control technique has recently been applied to structural damage detection, where the virtual passive controller only uses the existing control devices, and no additional physical elements are attached to the tested structure. One important task is to design passive controllers that can enhance the sensitivity of the identified parameters, such as natural frequencies, to structural damage. This paper presents a novel study of an optimal controller design for structural damage detection. We apply not only passive controllers but also low-order and fixed-structure controllers, such as PID controllers. In the optimal control design, the performance of structural damage detection is based on the application of a neural network technique, which uses the pattern of the correlation between the natural frequency changes of the tested system and the damaged system.
Modal insensitivity with optimality. [in feedback control
NASA Technical Reports Server (NTRS)
Calise, A. J.; Raman, K. V.
1984-01-01
This paper deals with the design of a constant gain, feedback controller which results in selected modal insensitivity, and at the same time optimizes a quadratic performance index representative of desired system performance for nominal plant parameter values. Both full state and output feedback control are considered. A constraint is established for the feedback gain matrix that results in modal insensitivity, and necessary conditions for optimality subject to this constraint are given. This forms the basis for a numerical algorithm to compute the optimal feedback gain. To illustrate the procedure, a design is carried out using the lateral dynamics of an L-1011 aircraft.
Optimal control techniques for active noise suppression
NASA Technical Reports Server (NTRS)
Banks, H. T.; Keeling, S. L.; Silcox, R. J.
1988-01-01
Active suppression of noise in a bounded enclosure is considered within the framework of optimal control theory. A sinusoidal pressure field due to exterior offending noise sources is assumed to be known in a neighborhood of interior sensors. The pressure field due to interior controlling sources is assumed to be governed by a nonhomogeneous wave equation within the enclosure and by a special boundary condition designed to accommodate frequency-dependent reflection properties of the enclosure boundary. The form of the controlling sources is determined by considering the steady-state behavior of the system, and it is established that the control strategy proposed is stable and asymptotically optimal.
Stochastic Optimal Control via Bellman's Principle
NASA Technical Reports Server (NTRS)
Crespo, Luis G.; Sun, Jian Q.
2003-01-01
This paper presents a method for finding optimal controls of nonlinear systems subject to random excitations. The method is capable to generate global control solutions when state and control constraints are present. The solution is global in the sense that controls for all initial conditions in a region of the state space are obtained. The approach is based on Bellman's Principle of optimality, the Gaussian closure and the Short-time Gaussian approximation. Examples include a system with a state-dependent diffusion term, a system in which the infinite hierarchy of moment equations cannot be analytically closed, and an impact system with a elastic boundary. The uncontrolled and controlled dynamics are studied by creating a Markov chain with a control dependent transition probability matrix via the Generalized Cell Mapping method. In this fashion, both the transient and stationary controlled responses are evaluated. The results show excellent control performances.
Optimal control of the spine system.
Xu, Yunfei; Choi, Jongeun; Reeves, N Peter; Cholewicki, Jacek
2010-05-01
The goal of this work is to present methodology to first evaluate the performance of an in vivo spine system and then to synthesize optimal neuromuscular control for rehabilitation interventions. This is achieved (1) by determining control system parameters such as static feedback gains and delays from experimental data, (2) by synthesizing the optimal feedback gains to attenuate the effect of disturbances to the system using modern control theory, and (3) by evaluating the robustness of the optimized closed-loop system. We also apply these methods to a postural control task, with two different control strategies, and evaluate the robustness of the spine system with respect to longer latencies found in the low back pain population. This framework could be used for rehabilitation design. To this end, we discuss several future research needs necessary to implement our framework in practice. PMID:20459205
Optimal cooperative control synthesis of active displays
NASA Technical Reports Server (NTRS)
Garg, S.; Schmidt, D. K.
1986-01-01
The utility of augmenting displays to aid the human operator in controlling high order complex systems is well known. Analytical evaluation of various display designs for a simple k/s sup 2 plant in a compensatory tracking task using an optimal Control Model (OCM) of human behavior is carried out. This analysis reveals that significant improvement in performance should be obtained by skillful integration of key information into the display dynamics. The cooperative control synthesis technique previously developed to design pilot-optimal control augmentation is extended to incorporate the simultaneous design of performance enhancing augmented displays. The application of the cooperative control synthesis technique to the design of augmented displays is discussed for the simple k/s sup 2 plant. This technique is intended to provide a systematic approach to design optimally augmented displays tailored for specific tasks.
Optimal cooperative control synthesis of active displays
NASA Technical Reports Server (NTRS)
Garg, S.; Schmidt, D. K.
1985-01-01
A technique is developed that is intended to provide a systematic approach to synthesizing display augmentation for optimal manual control in complex, closed-loop tasks. A cooperative control synthesis technique, previously developed to design pilot-optimal control augmentation for the plant, is extended to incorporate the simultaneous design of performance enhancing displays. The technique utilizes an optimal control model of the man in the loop. It is applied to the design of a quickening control law for a display and a simple K/s(2) plant, and then to an F-15 type aircraft in a multi-channel task. Utilizing the closed loop modeling and analysis procedures, the results from the display design algorithm are evaluated and an analytical validation is performed. Experimental validation is recommended for future efforts.
Optimal cooperative control synthesis of active displays
NASA Technical Reports Server (NTRS)
Gary, Sanjay; Schmidt, David K.
1987-01-01
A technique is developed that is intended to provide a systematic approach to synthesizing display augmentation for optimal manual control in complex, closed-loop tasks. A cooperative control synthesis technique, previously developed to design pilot-optimal control augmentation for the plant, is extended to incorporate the simultaneous design of performance enhancing displays. The technique utilizes an optimal control model of the man in the loop. It is applied to the design of a quickening control law for a display and a simple K/(s squared) plant, and then to an F-15 type aircraft in a multichannel task. Utilizing the closed-loop modeling and analysis procedures, the results from the display design algorithm are evaluated and an analytical validation is performed. Experimental validation is recommended for future efforts.
Optimal cooperative control synthesis of active displays
NASA Technical Reports Server (NTRS)
Garg, S.; Schmidt, D. K.
1985-01-01
The utility of augmenting displays to aid the human operator in controlling high order complex systems is well known. Analytical evaluations of various display designs for a simple k/s-squared plant in a compensatory tracking task using an Optimal Control Model (OCM) of human behavior is carried out. This analysis reveals that significant improvement in performance should be obtained by skillful integration of key information into the display dynamics. The cooperative control synthesis technique previously developed to design pilot-optimal control augmentation is extended to incorporate the simultaneous design of performance enhancing augmented displays. The application of the cooperative control synthesis technique to the design of augmented displays is discussed for the simple k/s-squared plant. This technique is intended to provide a systematic approach to design optimally augmented displays tailored for specific tasks.
Role of control constraints in quantum optimal control
NASA Astrophysics Data System (ADS)
Zhdanov, Dmitry V.; Seideman, Tamar
2015-11-01
The problems of optimizing the value of an arbitrary observable of a two-level system at both a fixed time and the shortest possible time is theoretically explored. Complete identification and classification along with comprehensive analysis of globally optimal control policies and traps (i.e., policies which are locally but not globally optimal) are presented. The central question addressed is whether the control landscape remains trap-free if control constraints of the inequality type are imposed. The answer is astonishingly controversial: Although the traps are proven always to exist in this case, in practice they become trivially escapable once the control time is fixed and chosen long enough.
A reliable algorithm for optimal control synthesis
NASA Technical Reports Server (NTRS)
Vansteenwyk, Brett; Ly, Uy-Loi
1992-01-01
In recent years, powerful design tools for linear time-invariant multivariable control systems have been developed based on direct parameter optimization. In this report, an algorithm for reliable optimal control synthesis using parameter optimization is presented. Specifically, a robust numerical algorithm is developed for the evaluation of the H(sup 2)-like cost functional and its gradients with respect to the controller design parameters. The method is specifically designed to handle defective degenerate systems and is based on the well-known Pade series approximation of the matrix exponential. Numerical test problems in control synthesis for simple mechanical systems and for a flexible structure with densely packed modes illustrate positively the reliability of this method when compared to a method based on diagonalization. Several types of cost functions have been considered: a cost function for robust control consisting of a linear combination of quadratic objectives for deterministic and random disturbances, and one representing an upper bound on the quadratic objective for worst case initial conditions. Finally, a framework for multivariable control synthesis has been developed combining the concept of closed-loop transfer recovery with numerical parameter optimization. The procedure enables designers to synthesize not only observer-based controllers but also controllers of arbitrary order and structure. Numerical design solutions rely heavily on the robust algorithm due to the high order of the synthesis model and the presence of near-overlapping modes. The design approach is successfully applied to the design of a high-bandwidth control system for a rotorcraft.
Post-Translational Modification Control of Innate Immunity.
Liu, Juan; Qian, Cheng; Cao, Xuetao
2016-07-19
A coordinated balance between the positive and negative regulation of pattern-recognition receptor (PRR)-initiated innate inflammatory responses is required to ensure the most favorable outcome for the host. Post-translational modifications (PTMs) of innate sensors and downstream signaling molecules influence their activity and function by inducing their covalent linkage to new functional groups. PTMs including phosphorylation and polyubiquitination have been shown to potently regulate innate inflammatory responses through the activation, cellular translocation, and interaction of innate receptors, adaptors, and downstream signaling molecules in response to infectious and dangerous signals. Other PTMs such as methylation, acetylation, SUMOylation, and succinylation are increasingly implicated in the regulation of innate immunity and inflammation. In this review, we focus on the roles of PTMs in controlling PRR-triggered innate immunity and inflammatory responses. The emerging roles of PTMs in the pathogenesis and potential treatment of infectious and inflammatory immune diseases are also discussed. PMID:27438764
OPTIMIZATION OF COMBINED SEWER OVERFLOW CONTROL SYSTEMS
The highly variable and intermittent pollutant concentrations and flowrates associated with wet-weather events in combined sewersheds necessitates the use of storage-treatment systems to control pollution.An optimized combined-sewer-overflow (CSO) control system requires a manage...
Centralized Stochastic Optimal Control of Complex Systems
Malikopoulos, Andreas
2015-01-01
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 using the long-run expected average cost per unit time criterion, and we show that the control policy yielding the Pareto optimal solution minimizes the average cost criterion online. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.
Algorithm For Optimal Control Of Large Structures
NASA Technical Reports Server (NTRS)
Salama, Moktar A.; Garba, John A..; Utku, Senol
1989-01-01
Cost of computation appears competitive with other methods. Problem to compute optimal control of forced response of structure with n degrees of freedom identified in terms of smaller number, r, of vibrational modes. Article begins with Hamilton-Jacobi formulation of mechanics and use of quadratic cost functional. Complexity reduced by alternative approach in which quadratic cost functional expressed in terms of control variables only. Leads to iterative solution of second-order time-integral matrix Volterra equation of second kind containing optimal control vector. Cost of algorithm, measured in terms of number of computations required, is of order of, or less than, cost of prior algoritms applied to similar problems.
The use of intake condition modifications to control diesel emissions
Bowen, C.E.; Reader, G.T.; Potter, I.J.; Gustafson, R.W.
1995-12-31
Diesel engines have the inherent capability of producing emissions, such as NOx, particulates, unburned hydrocarbons, and noise which at certain levels and concentrations are considered to be environmentally unfriendly. To control these emissions, techniques have been developed which are aimed at reducing the amount of pollutants formed in the combustion process or preventing them from reaching the atmosphere (after treatment). The initial condition of the in-cylinder reactants and diluents affects how the combustion process proceeds and hence influences the formation and rate of formation of the pollutants. Thus, one approach to emission control is to modify the intake oxidant conditions, i.e., the composition and thermodynamic state of the working fluid. This modification can be accomplished by the use of exhaust gas recirculation (EGR). EGR has been extensively developed for use with SI engine emission control systems and for specialized diesel engine operations where synthetic atmospheres are used (underwater) or where operations take place in contaminated environments (underground). More recently EGR has been considered as a technique for helping reduce NOx emissions from conventional diesel engine systems. Usually, experimental investigations involving EGR have dealt with the global effects on emissions and performance but in the research reported in this paper efforts have been made to identify the specific effects of altering intake conditions, e.g., oxygen concentration, on the operation of an Indirect-Injection (IDI) diesel engine.
Optimal integral controller with sensor failure accommodation
NASA Technical Reports Server (NTRS)
Alberts, T.; Houlihan, T.
1989-01-01
An Optimal Integral Controller that readily accommodates Sensor Failure - without resorting to (Kalman) filter or observer generation - has been designed. The system is based on Navy-sponsored research for the control of high performance aircraft. In conjunction with a NASA developed Numerical Optimization Code, the Integral Feedback Controller will provide optimal system response even in the case of incomplete state feedback. Hence, the need for costly replication of plant sensors is avoided since failure accommodation is effected by system software reconfiguration. The control design has been applied to a particularly ill-behaved, third-order system. Dominant-root design in the classical sense produced an almost 100 percent overshoot for the third-order system response. An application of the newly-developed Optimal Integral Controller - assuming all state information available - produces a response with no overshoot. A further application of the controller design - assuming a one-third sensor failure scenario - produced a slight overshoot response that still preserved the steady state time-point of the full-state feedback response. The control design should have wide application in space systems.
Advanced rotorcraft control using parameter optimization
NASA Technical Reports Server (NTRS)
Vansteenwyk, Brett; Ly, Uy-Loi
1991-01-01
A reliable algorithm for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters is presented. The algorithm is part of a design algorithm for an optimal linear dynamic output feedback controller that minimizes a finite time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed loop eigensystem. This approach through the use of a accurate Pade series approximation does not require the closed loop system matrix to be diagonalizable. The algorithm has been included in a control design package for optimal robust low order controllers. Usefulness of the proposed numerical algorithm has been demonstrated using numerous practical design cases where degeneracies occur frequently in the closed loop system under an arbitrary controller design initialization and during the numerical search.
Stochastic time-optimal control problems
NASA Technical Reports Server (NTRS)
Zhang, W.; Elliot, D.
1988-01-01
Two types of stochastic time-optimal controls in a one-dimensional setting are considered. Multidimensional problems, in the case of complete state information available and the system modeled by stochastic differential equations, are studied under the formulation of minimizing the expected transient-response time. The necessary condition of optimality is the satisfaction for the value function of a parabolic partial differential equation with boundary conditions. The sufficient condition of optimality is also provided, based on Dynkin's formula. Finally, three examples are given.
Road map to adaptive optimal control. [jet engine control
NASA Technical Reports Server (NTRS)
Boyer, R.
1980-01-01
A building block control structure leading toward adaptive, optimal control for jet engines is developed. This approach simplifies the addition of new features and allows for easier checkout of the control by providing a baseline system for comparison. Also, it is possible to eliminate certain features that do not have payoff by being selective in the addition of new building blocks to be added to the baseline system. The minimum risk approach specifically addresses the need for active identification of the plant to be controlled in real time and real time optimization of the control for the identified plant.
Multimodel methods for optimal control of aeroacoustics.
Chen, Guoquan; Collis, Samuel Scott
2005-01-01
A new multidomain/multiphysics computational framework for optimal control of aeroacoustic noise has been developed based on a near-field compressible Navier-Stokes solver coupled with a far-field linearized Euler solver both based on a discontinuous Galerkin formulation. In this approach, the coupling of near- and far-field domains is achieved by weakly enforcing continuity of normal fluxes across a coupling surface that encloses all nonlinearities and noise sources. For optimal control, gradient information is obtained by the solution of an appropriate adjoint problem that involves the propagation of adjoint information from the far-field to the near-field. This computational framework has been successfully applied to study optimal boundary-control of blade-vortex interaction, which is a significant noise source for helicopters on approach to landing. In the model-problem presented here, the noise propagated toward the ground is reduced by 12dB.
Optimal and multivariable control of a turbogenerator
NASA Astrophysics Data System (ADS)
Lahoud, M. A.; Harley, R. G.; Secker, A.
The use of modern control methods to design multivariable controllers which improve the performance of a turbogenerator was investigated. The turbogenerator nonlinear mathematical model from which a linearized model is deduced is presented. The inverse Nyquist Array method and the theory of optimal control are both applied to the linearized model to generate two alternative control schemes. The schemes are implemented on the nonlinear simulation model to assess their dynamic performance. Results from modern multivariable control schemes are compared with the classical automatic voltage regulator and speed governor system.
Quadratic optimal cooperative control synthesis with flight control application
NASA Technical Reports Server (NTRS)
Schmidt, D. K.; Innocenti, M.
1984-01-01
An optimal control-law synthesis approach is presented that involves simultaneous solution for two cooperating controllers operating in parallel. One controller's structure includes stochastic state estimation and linear feedback of the state estimates, while the other controller involves direct linear feedback of selected system output measurements. This structure is shown to be optimal under the constraint of linear feedback of system outputs in one controller. Furthermore, it is appropriate for flight control synthesis where the full-state optimal stochastic controller can be adjusted to be representative of an optimal control model of the human pilot in a stochastic regulation task. The method is experimentally verified in the case of the selection of pitch-damper gain for optimum pitch tracking, where optimum implies the best subjective pilot rating in the task. Finally, results from application of the method to synthesize a controller for a multivariable fighter aircraft are presented, and implications of the results of this method regarding the optimal plant dynamics for tracking are discussed.
Optimal Feedback Control of Thermal Networks
NASA Technical Reports Server (NTRS)
Papalexandris, Miltiadis
2003-01-01
An improved approach to the mathematical modeling of feedback control of thermal networks has been devised. Heretofore software for feedback control of thermal networks has been developed by time-consuming trial-and-error methods that depend on engineers expertise. In contrast, the present approach is a systematic means of developing algorithms for feedback control that is optimal in the sense that it combines performance with low cost of implementation. An additional advantage of the present approach is that a thermal engineer need not be expert in control theory. Thermal networks are lumped-parameter approximations used to represent complex thermal systems. Thermal networks are closely related to electrical networks commonly represented by lumped-parameter circuit diagrams. Like such electrical circuits, thermal networks are mathematically modeled by systems of differential-algebraic equations (DAEs) that is, ordinary differential equations subject to a set of algebraic constraints. In the present approach, emphasis is placed on applications in which thermal networks are subject to constant disturbances and, therefore, integral control action is necessary to obtain steady-state responses. The mathematical development of the present approach begins with the derivation of optimal integral-control laws via minimization of an appropriate cost functional that involves augmented state vectors. Subsequently, classical variational arguments provide optimality conditions in the form of the Hamiltonian equations for the standard linear-quadratic-regulator (LQR) problem. These equations are reduced to an algebraic Riccati equation (ARE) with respect to the augmented state vector. The solution of the ARE leads to the direct computation of the optimal proportional- and integral-feedback control gains. In cases of very complex networks, large numbers of state variables make it difficult to implement optimal controllers in the manner described in the preceding paragraph.
Optimal control with multiple human papillomavirus vaccines.
Malik, Tufail; Imran, Mudassar; Jayaraman, Raja
2016-03-21
A two-sex, deterministic ordinary differential equations model for human papillomavirus (HPV) is constructed and analyzed for optimal control strategies in a vaccination program administering three types of vaccines in the female population: a bivalent vaccine that targets two HPV types and provides longer duration of protection and cross-protection against some non-target types, a quadrivalent vaccine which targets an additional two HPV types, and a nonavalent vaccine which targets nine HPV types (including those covered by the quadrivalent vaccine), but with lesser type-specific efficacy. Considering constant vaccination controls, the disease-free equilibrium and the effective reproduction number Rv for the autonomous model are computed in terms of the model parameters. Local-asymptotic stability of the disease-free equilibrium is established in terms of Rv. Uncertainty and Sensitivity analyses are carried out to study the influence of various important model parameters on the HPV infection prevalence. Assuming the HPV infection prevalence in the population under the constant control, optimal control theory is used to devise optimal vaccination strategies for the associated non-autonomous model when the vaccination rates are functions of time. The impact of these strategies on the number of infected individuals and the accumulated cost is assessed and compared with the constant control case. Switch times from one vaccine combination to a different combination including the nonavalent vaccine are assessed during an optimally designed HPV immunization program. PMID:26796222
Sensitivity of optimal control systems with bang-bang control.
NASA Technical Reports Server (NTRS)
Rootenberg, J.; Courtin, P.
1973-01-01
The effects of small parameter variations on the performance index of optimal control systems with initial and final target manifolds, free end time, and bang-bang control are analyzed in this paper. A new approach to the sensitivity equation is presented. This approach takes into account the pulse-shaped variation produced by the parameter change on the bang-bang control. An expression, that relates the variations of the performance index, the trajectory, the final time, and the parameter, is derived. This expression extends to the class of optimal systems with bang-bang control, a result previously obtained by Courtin and Rootenberg (1971).
Optimal control of anthracnose using mixed strategies.
Fotsa Mbogne, David Jaures; Thron, Christopher
2015-11-01
In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously developed in [15]. We use the model to simulate two different types of control strategies against anthracnose disease. Strategies that employ chemical fungicides are modeled using a continuous control function; while strategies that rely on cultivational practices (such as pruning and removal of mummified fruits) are modeled with a control function which is discrete in time (though not in space). For comparative purposes, we perform our analyses for a spatially-averaged model as well as the space-dependent diffusion model. Under weak smoothness conditions on parameters we demonstrate the well-posedness of both models by verifying existence and uniqueness of the solution for the growth inhibition rate for given initial conditions. We also show that the set [0, 1] is positively invariant. We first study control by impulsive strategies, then analyze the simultaneous use of mixed continuous and pulse strategies. In each case we specify a cost functional to be minimized, and we demonstrate the existence of optimal control strategies. In the case of pulse-only strategies, we provide explicit algorithms for finding the optimal control strategies for both the spatially-averaged model and the space-dependent model. We verify the algorithms for both models via simulation, and discuss properties of the optimal solutions. PMID:26407644
2012-01-01
Background Secretory signal peptides (SPs) are well-known sequence motifs targeting proteins for translocation across the endoplasmic reticulum membrane. After passing through the secretory pathway, most proteins are secreted to the environment. Here, we describe the modification of an expression vector containing the SP from secreted acid phosphatase 1 (SAP1) of Leishmania mexicana for optimized protein expression-secretion in the eukaryotic parasite Leishmania tarentolae with regard to recombinant antibody fragments. For experimental design the online tool SignalP was used, which predicts the presence and location of SPs and their cleavage sites in polypeptides. To evaluate the signal peptide cleavage site as well as changes of expression, SPs were N-terminally linked to single-chain Fragment variables (scFv’s). The ability of L. tarentolae to express complex eukaryotic proteins with highly diverse post-translational modifications and its easy bacteria-like handling, makes the parasite a promising expression system for secretory proteins. Results We generated four vectors with different SP-sequence modifications based on in-silico analyses with SignalP in respect to cleavage probability and location, named pLTEX-2 to pLTEX-5. To evaluate their functionality, we cloned four individual scFv-fragments into the vectors and transfected all 16 constructs into L. tarentolae. Independently from the expressed scFv, pLTEX-5 derived constructs showed the highest expression rate, followed by pLTEX-4 and pLTEX-2, whereas only low amounts of protein could be obtained from pLTEX-3 clones, indicating dysfunction of the SP. Next, we analysed the SP cleavage sites by Edman degradation. For pLTEX-2, -4, and -5 derived scFv’s, the results corresponded to in-silico predictions, whereas pLTEX-3 derived scFv’s contained one additional amino-acid (AA). Conclusions The obtained results demonstrate the importance of SP-sequence optimization for efficient expression-secretion of sc
Linear stochastic optimal control and estimation problem
NASA Technical Reports Server (NTRS)
Geyser, L. C.; Lehtinen, F. K. B.
1980-01-01
Problem involves design of controls for linear time-invariant system disturbed by white noise. Solution is Kalman filter coupled through set of optimal regulator gains to produce desired control signal. Key to solution is solving matrix Riccati differential equation. LSOCE effectively solves problem for wide range of practical applications. Program is written in FORTRAN IV for batch execution and has been implemented on IBM 360.
Mean-field sparse optimal control
Fornasier, Massimo; Piccoli, Benedetto; Rossi, Francesco
2014-01-01
We introduce the rigorous limit process connecting finite dimensional sparse optimal control problems with ODE constraints, modelling parsimonious interventions on the dynamics of a moving population divided into leaders and followers, to an infinite dimensional optimal control problem with a constraint given by a system of ODE for the leaders coupled with a PDE of Vlasov-type, governing the dynamics of the probability distribution of the followers. In the classical mean-field theory, one studies the behaviour of a large number of small individuals freely interacting with each other, by simplifying the effect of all the other individuals on any given individual by a single averaged effect. In this paper, we address instead the situation where the leaders are actually influenced also by an external policy maker, and we propagate its effect for the number N of followers going to infinity. The technical derivation of the sparse mean-field optimal control is realized by the simultaneous development of the mean-field limit of the equations governing the followers dynamics together with the Γ-limit of the finite dimensional sparse optimal control problems. PMID:25288818
RESOURCES ALLOCATION TO OPTIMIZE MINING POLLUTION CONTROL
A comprehensive model for mine drainage simulation and optimization of resource allocation to control mine acid pollution in a watershed has been developed. The model is capable of: (a) Producing a time trace of acid load and flow from acid drainage sources as a function of clima...
Optimal decentralized control for multimachine power systems--
Quali, A. ); Fantin, J. )
1989-01-01
This paper provides a method for determining an optimal decentralized control for multimachine power systems with quadratic performance measure. An iterative algorithm is developed whereby a local minimum is attained. The constraint of decentralization is tackled with in minimization algorithm by using the method of feasible directions. An example of three synchronous machines is given to illustrate the proposed algorithm.
Optimal control solutions to sodic soil reclamation
NASA Astrophysics Data System (ADS)
Mau, Yair; Porporato, Amilcare
2016-05-01
We study the reclamation process of a sodic soil by irrigation with water amended with calcium cations. In order to explore the entire range of time-dependent strategies, this task is framed as an optimal control problem, where the amendment rate is the control and the total rehabilitation time is the quantity to be minimized. We use a minimalist model of vertically averaged soil salinity and sodicity, in which the main feedback controlling the dynamics is the nonlinear coupling of soil water and exchange complex, given by the Gapon equation. We show that the optimal solution is a bang-bang control strategy, where the amendment rate is discontinuously switched along the process from a maximum value to zero. The solution enables a reduction in remediation time of about 50%, compared with the continuous use of good-quality irrigation water. Because of its general structure, the bang-bang solution is also shown to work for the reclamation of other soil conditions, such as saline-sodic soils. The novelty in our modeling approach is the capability of searching the entire "strategy space" for optimal time-dependent protocols. The optimal solutions found for the minimalist model can be then fine-tuned by experiments and numerical simulations, applicable to realistic conditions that include spatial variability and heterogeneities.
Optimal and robust control of transition
NASA Technical Reports Server (NTRS)
Bewley, T. R.; Agarwal, R.
1996-01-01
Optimal and robust control theories are used to determine feedback control rules that effectively stabilize a linearly unstable flow in a plane channel. Wall transpiration (unsteady blowing/suction) with zero net mass flux is used as the control. Control algorithms are considered that depend both on full flowfield information and on estimates of that flowfield based on wall skin-friction measurements only. The development of these control algorithms accounts for modeling errors and measurement noise in a rigorous fashion; these disturbances are considered in both a structured (Gaussian) and unstructured ('worst case') sense. The performance of these algorithms is analyzed in terms of the eigenmodes of the resulting controlled systems, and the sensitivity of individual eigenmodes to both control and observation is quantified.
Optimal singular control for nonlinear semistabilisation
NASA Astrophysics Data System (ADS)
L'Afflitto, Andrea; Haddad, Wassim M.
2016-06-01
The singular optimal control problem for asymptotic stabilisation has been extensively studied in the literature. In this paper, the optimal singular control problem is extended to address a weaker version of closed-loop stability, namely, semistability, which is of paramount importance for consensus control of network dynamical systems. Three approaches are presented to address the nonlinear semistable singular control problem. Namely, a singular perturbation method is presented to construct a state-feedback singular controller that guarantees closed-loop semistability for nonlinear systems. In this approach, we show that for a non-negative cost-to-go function the minimum cost of a nonlinear semistabilising singular controller is lower than the minimum cost of a singular controller that guarantees asymptotic stability of the closed-loop system. In the second approach, we solve the nonlinear semistable singular control problem by using the cost-to-go function to cancel the singularities in the corresponding Hamilton-Jacobi-Bellman equation. For this case, we show that the minimum value of the singular performance measure is zero. Finally, we provide a framework based on the concepts of state-feedback linearisation and feedback equivalence to solve the singular control problem for semistabilisation of nonlinear dynamical systems. For this approach, we also show that the minimum value of the singular performance measure is zero. Three numerical examples are presented to demonstrate the efficacy of the proposed singular semistabilisation frameworks.
Preconception optimization of glycaemic control in diabetes.
Islam, Najmul
2016-09-01
The prevalence of Diabetes Mellitus is increasing worldwide. In developing countries 25% of adult females with diabetes are in the reproductive age. Thus in developing countries increased number of pregnancies are complicated by diabetes. Uncontrolled diabetes in pregnancy is associated with increased risk for both mother and foetus. These risks can be minimized by good control of diabetes before and during pregnancy. Management in the preconception period is discussed in this review article. Detailed management involves general advice of lifestyle modification followed by specific details of screening for complications of diabetes. Changes in the drugs for both glycaemic control and other co-morbid conditions are discussed. The recommended insulin regimen in the preconception period and monitoring of glycaemic control by self-monitoring of blood glucose (SMBG) and HbA1C has also been highlighted. PMID:27582143
Optimization for efficient structure-control systems
NASA Technical Reports Server (NTRS)
Oz, Hayrani; Khot, Narendra S.
1993-01-01
The efficiency of a structure-control system is a nondimensional parameter which indicates the fraction of the total control power expended usefully in controlling a finite-dimensional system. The balance of control power is wasted on the truncated dynamics serving no useful purpose towards the control objectives. Recently, it has been demonstrated that the concept of efficiency can be used to address a number of control issues encountered in the control of dynamic systems such as the spillover effects, selection of a good input configuration and obtaining reduced order control models. Reference (1) introduced the concept and presented analyses of several Linear Quadratic Regulator designs on the basis of their efficiencies. Encouraged by the results of Ref. (1), Ref. (2) introduces an efficiency modal analysis of a structure-control system which gives an internal characterization of the controller design and establishes the link between the control design and the initial disturbances to affect efficient structure-control system designs. The efficiency modal analysis leads to identification of principal controller directions (or controller modes) distinct from the structural natural modes. Thus ultimately, many issues of the structure-control system revolve around the idea of insuring compatibility of the structural modes and the controller modes with each other, the better the match the higher the efficiency. A key feature in controlling a reduced order model of a high dimensional (or infinity-dimensional distributed parameter system) structural dynamic system must be to achieve high efficiency of the control system while satisfying the control objectives and/or constraints. Formally, this can be achieved by designing the control system and structural parameters simultaneously within an optimization framework. The subject of this paper is to present such a design procedure.
Active control of combustion for optimal performance
Jackson, M.D.; Agrawal, A.K.
1999-07-01
Combustion-zone stoichiometry and fuel-air premixing were actively controlled to optimize the combustor performance over a range of operating conditions. The objective was to maximize the combustion temperature, while maintaining NO{sub x} within a specified limit. The combustion system consisted of a premixer located coaxially near the inlet of a water-cooled shroud. The equivalence ratio was controlled by a variable-speed suction fan located downstream. The split between the premixing air and diffusion air was governed by the distance between the premixer and shroud. The combustor performance was characterized by a cost function evaluated from time-averaged measurements of NO{sub x} and oxygen concentrations in products. The cost function was minimized by downhill simplex algorithm employing closed-loop feedback. Experiments were conducted at different fuel flow rates to demonstrate that the controller optimized the performance without prior knowledge of the combustor behavior.
A control model for dependable hydropower capacity optimization
NASA Astrophysics Data System (ADS)
Georgakakos, Aris P.; Yao, Huaming; Yu, Yongqing
In this article a control model that can be used to determine the dependable power capacity of a hydropower system is presented and tested. The model structure consists of a turbine load allocation module and a reservoir control module and allows for a detailed representation of hydroelectric facilities and various aspects of water management. Although this scheme is developed for planning purposes, it can also be used operationally with minor modifications. The model is applied to the Lanier-Allatoona-Carters reservoir system on the Chattahoochee and Coosa River Basins, in the southeastern United States. The case studies demonstrate that the more traditional simulation-based approaches often underestimate dependable power capacity. Firm energy optimization with or without dependable capacity constraints is taken up in a companion article [Georgakakos et al., this issue].
Optimality principles in sensorimotor control (review)
Todorov, Emanuel
2006-01-01
The sensorimotor system is a product of evolution, development, learning, adaptation – processes that work on different time scales to improve behavioral performance. Consequenly, many theories of motor function are based on the notion of optimal performance: they quantify the task goals, and apply the sophisticated tools of optimal control theory to obtain detailed behavioral predictions. The resulting models, although not without limitations, has explained a wider range of empirical phenomena than any other class of models. Traditional emphasis has been on optimizing average trajectories while ignoring sensory feedback. Recent work has redefined optimality on the level of feedback control laws, and focused on the mechanisms that generate behavior online. This has made it possible to fit a number of previously unrelated concepts and observations into what may become a unified theoretical framework for interpreting motor function. At the heart of the framework is the relationship between high-level goals, and the realtime sensorimotor control strategies most suitable for accomplishing those goals. PMID:15332089
Algorithms for optimizing CT fluence control
NASA Astrophysics Data System (ADS)
Hsieh, Scott S.; Pelc, Norbert J.
2014-03-01
The ability to customize the incident x-ray fluence in CT via beam-shaping filters or mA modulation is known to improve image quality and/or reduce radiation dose. Previous work has shown that complete control of x-ray fluence (ray-by-ray fluence modulation) would further improve dose efficiency. While complete control of fluence is not currently possible, emerging concepts such as dynamic attenuators and inverse-geometry CT allow nearly complete control to be realized. Optimally using ray-by-ray fluence modulation requires solving a very high-dimensional optimization problem. Most optimization techniques fail or only provide approximate solutions. We present efficient algorithms for minimizing mean or peak variance given a fixed dose limit. The reductions in variance can easily be translated to reduction in dose, if the original variance met image quality requirements. For mean variance, a closed form solution is derived. The peak variance problem is recast as iterated, weighted mean variance minimization, and at each iteration it is possible to bound the distance to the optimal solution. We apply our algorithms in simulations of scans of the thorax and abdomen. Peak variance reductions of 45% and 65% are demonstrated in the abdomen and thorax, respectively, compared to a bowtie filter alone. Mean variance shows smaller gains (about 15%).
Helicopter trajectory planning using optimal control theory
NASA Technical Reports Server (NTRS)
Menon, P. K. A.; Cheng, V. H. L.; Kim, E.
1988-01-01
A methodology for optimal trajectory planning, useful in the nap-of-the-earth guidance of helicopters, is presented. This approach uses an adjoint-control transformation along with a one-dimensional search scheme for generating the optimal trajectories. In addition to being useful for helicopter nap-of-the-earth guidance, the trajectory planning solution is of interest in several other contexts, such as robotic vehicle guidance and terrain-following guidance for cruise missiles and aircraft. A distinguishing feature of the present research is that the terrain constraint and the threat envelopes are incorporated in the equations of motion. Second-order necessary conditions are examined.
Simultaneous structure and control optimization of tensegrities
NASA Astrophysics Data System (ADS)
Masic, Milenko; Skelton, Robert E.
2005-05-01
This paper concerns optimization of prestress of a tensegrity structure to achieve the optimal mixed dynamic and control performance. A linearized dynamic model of the structure is derived. The force density variables that parameterize prestress of the structure appear linearly in the model. The feasible region of these parameters is defined in terms of the extreme directions of the prestress cone. Several properties of the problem are established inside the feasible region of the parameters. The problem is solved using a gradient method that provides a monotonic decrease of the objective function inside the feasible region. A numerical example of a cantilevered planar tensegrity beam is shown.
NASA Astrophysics Data System (ADS)
Shu, Chuan-Cun; Ho, Tak-San; Rabitz, Herschel
2016-05-01
We present a monotonic convergent quantum optimal control method that can be utilized to optimize the control field while exactly enforcing multiple equality constraints for steering quantum systems from an initial state towards desired quantum states. For illustration, special consideration is given to finding optimal control fields with (i) exact zero area and (ii) exact zero area along with constant pulse fluence. The method combined with these two types of constraints is successfully employed to maximize the state-to-state transition probability in a model vibrating diatomic molecule.
Perturbation analysis of optimal integral controls
NASA Technical Reports Server (NTRS)
Slater, G. L.
1984-01-01
The application of linear optimal control to the design of systems with integral control action on specified outputs is considered. Using integral terms in a quadratic performance index, an asymptotic analysis is used to determine the effect of variable quadratic weights on the eigenvalues and eigenvectors of the closed loop system. It is shown that for small integral terms the placement of integrator poles and gain calculation can be effectively decoupled from placement of the primary system eigenvalues. This technique is applied to the design of integral controls for a STOL aircraft outer loop guidance system.
PDEMOD: Software for control/structures optimization
NASA Technical Reports Server (NTRS)
Taylor, Lawrence W., Jr.; Zimmerman, David
1991-01-01
Because of the possibility of adverse interaction between the control system and the structural dynamics of large, flexible spacecraft, great care must be taken to ensure stability and system performance. Because of the high cost of insertion of mass into low earth orbit, it is prudent to optimize the roles of structure and control systems simultaneously. Because of the difficulty and the computational burden in modeling and analyzing the control structure system dynamics, the total problem is often split and treated iteratively. It would aid design if the control structure system dynamics could be represented in a single system of equations. With the use of the software PDEMOD (Partial Differential Equation Model), it is now possible to optimize structure and control systems simultaneously. The distributed parameter modeling approach enables embedding the control system dynamics into the same equations for the structural dynamics model. By doing this, the current difficulties involved in model order reduction are avoided. The NASA Mini-MAST truss is used an an example for studying integrated control structure design.
Modal methods in optimal control synthesis
NASA Technical Reports Server (NTRS)
Bryson, A. E., Jr.; Hall, W. E., Jr.
1980-01-01
Efficient algorithms for solving linear smoother-follower problems with quadratic criteria are presented. For time-invariant systems, the algorithm consists of one backward integration of a linear vector equation and one forward integration of another linear vector equation. Furthermore, the backward and forward Riccati matrices can be expressed in terms of the eigenvalues and eigenvectors of the Euler-Lagrange equations. Hence, the gains of the forward and backward Kalman-Bucy filters and of the optimal state-feedback regulator can be determined without integration of matrix Riccati equations. A computer program has been developed, based on this method of determining the gains, to synthesize the optimal time-invariant compensator in the presence of random disturbance inputs and random measurement errors. The program also computes the rms state and control variables of the optimal closed-loop system.
Optimal control of multiplicative control systems arising from cancer therapy
NASA Technical Reports Server (NTRS)
Bahrami, K.; Kim, M.
1975-01-01
This study deals with ways of curtailing the rapid growth of cancer cell populations. The performance functional that measures the size of the population at the terminal time as well as the control effort is devised. With use of the discrete maximum principle, the Hamiltonian for this problem is determined and the condition for optimal solutions are developed. The optimal strategy is shown to be a bang-bang control. It is shown that the optimal control for this problem must be on the vertices of an N-dimensional cube contained in the N-dimensional Euclidean space. An algorithm for obtaining a local minimum of the performance function in an orderly fashion is developed. Application of the algorithm to the design of antitumor drug and X-irradiation schedule is discussed.
Aerodynamic shape optimization using control theory
NASA Technical Reports Server (NTRS)
Reuther, James
1996-01-01
Aerodynamic shape design has long persisted as a difficult scientific challenge due its highly nonlinear flow physics and daunting geometric complexity. However, with the emergence of Computational Fluid Dynamics (CFD) it has become possible to make accurate predictions of flows which are not dominated by viscous effects. It is thus worthwhile to explore the extension of CFD methods for flow analysis to the treatment of aerodynamic shape design. Two new aerodynamic shape design methods are developed which combine existing CFD technology, optimal control theory, and numerical optimization techniques. Flow analysis methods for the potential flow equation and the Euler equations form the basis of the two respective design methods. In each case, optimal control theory is used to derive the adjoint differential equations, the solution of which provides the necessary gradient information to a numerical optimization method much more efficiently then by conventional finite differencing. Each technique uses a quasi-Newton numerical optimization algorithm to drive an aerodynamic objective function toward a minimum. An analytic grid perturbation method is developed to modify body fitted meshes to accommodate shape changes during the design process. Both Hicks-Henne perturbation functions and B-spline control points are explored as suitable design variables. The new methods prove to be computationally efficient and robust, and can be used for practical airfoil design including geometric and aerodynamic constraints. Objective functions are chosen to allow both inverse design to a target pressure distribution and wave drag minimization. Several design cases are presented for each method illustrating its practicality and efficiency. These include non-lifting and lifting airfoils operating at both subsonic and transonic conditions.
Optimal Control via Self-Generated Stochasticity
NASA Technical Reports Server (NTRS)
Zak, Michail
2011-01-01
The problem of global maxima of functionals has been examined. Mathematical roots of local maxima are the same as those for a much simpler problem of finding global maximum of a multi-dimensional function. The second problem is instability even if an optimal trajectory is found, there is no guarantee that it is stable. As a result, a fundamentally new approach is introduced to optimal control based upon two new ideas. The first idea is to represent the functional to be maximized as a limit of a probability density governed by the appropriately selected Liouville equation. Then, the corresponding ordinary differential equations (ODEs) become stochastic, and that sample of the solution that has the largest value will have the highest probability to appear in ODE simulation. The main advantages of the stochastic approach are that it is not sensitive to local maxima, the function to be maximized must be only integrable but not necessarily differentiable, and global equality and inequality constraints do not cause any significant obstacles. The second idea is to remove possible instability of the optimal solution by equipping the control system with a self-stabilizing device. The applications of the proposed methodology will optimize the performance of NASA spacecraft, as well as robot performance.
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.
Ultrasound therapy applicators for controlled thermal modification of tissue
NASA Astrophysics Data System (ADS)
Burdette, E. Clif; Lichtenstiger, Carol; Rund, Laurie; Keralapura, Mallika; Gossett, Chad; Stahlhut, Randy; Neubauer, Paul; Komadina, Bruce; Williams, Emery; Alix, Chris; Jensen, Tor; Schook, Lawrence; Diederich, Chris J.
2011-03-01
Heat therapy has long been used for treatments in dermatology and sports medicine. The use of laser, RF, microwave, and more recently, ultrasound treatment, for psoriasis, collagen reformation, and skin tightening has gained considerable interest over the past several years. Numerous studies and commercial devices have demonstrated the efficacy of these methods for treatment of skin disorders. Despite these promising results, current systems remain highly dependent on operator skill, and cannot effectively treat effectively because there is little or no control of the size, shape, and depth of the target zone. These limitations make it extremely difficult to obtain consistent treatment results. The purpose of this study was to determine the feasibility for using acoustic energy for controlled dose delivery sufficient to produce collagen modification for the treatment of skin tissue in the dermal and sub-dermal layers. We designed and evaluated a curvilinear focused ultrasound device for treating skin disorders such as psoriasis, stimulation of wound healing, tightening of skin through shrinkage of existing collagen and stimulation of new collagen formation, and skin cancer. Design parameters were examined using acoustic pattern simulations and thermal modeling. Acute studies were performed in 201 freshly-excised samples of young porcine underbelly skin tissue and 56 in-vivo treatment areas in 60- 80 kg pigs. These were treated with ultrasound (9-11MHz) focused in the deep dermis. Dose distribution was analyzed and gross pathology assessed. Tissue shrinkage was measured based on fiducial markers and video image registration and analyzed using NIH Image-J software. Comparisons were made between RF and focused ultrasound for five energy ranges. In each experimental series, therapeutic dose levels (60degC) were attained at 2-5mm depth. Localized collagen changes ranged from 1-3% for RF versus 8-15% for focused ultrasound. Therapeutic ultrasound applied at high
Intermittent locomotion as an optimal control strategy
Paoletti, P.; Mahadevan, L.
2014-01-01
Birds, fish and other animals routinely use unsteady effects to save energy by alternating between phases of active propulsion and passive coasting. Here, we construct a minimal model for such behaviour that can be couched as an optimal control problem via an analogy to travelling with a rechargeable battery. An analytical solution of the optimal control problem proves that intermittent locomotion has lower energy requirements relative to steady-state strategies. Additional realistic hypotheses, such as the assumption that metabolic cost at a given power should be minimal (the fixed gear hypothesis), a nonlinear dependence of the energy storage rate on propulsion and/or a preferred average speed, allow us to generalize the model and demonstrate the flexibility of intermittent locomotion with implications for biological and artificial systems. PMID:24711718
Cancer Behavior: An Optimal Control Approach
Gutiérrez, Pedro J.; Russo, Irma H.; Russo, J.
2009-01-01
With special attention to cancer, this essay explains how Optimal Control Theory, mainly used in Economics, can be applied to the analysis of biological behaviors, and illustrates the ability of this mathematical branch to describe biological phenomena and biological interrelationships. Two examples are provided to show the capability and versatility of this powerful mathematical approach in the study of biological questions. The first describes a process of organogenesis, and the second the development of tumors. PMID:22247736
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.
COMBUSTION MODIFICATION CONTROLS FOR STATIONARY GAS TURBINE. VOLUME I: ENVIRONMENTAL ASSESSMENT
The report gives an environmental assessment of combustion modification techniques for stationary gas turbines, with respect to NOx control effectiveness, operational impact, thermal efficiency impact, control costs, and effect on emissions of pollutants other than NOx.
Reduced state feedback gain computation. [optimization and control theory for aircraft control
NASA Technical Reports Server (NTRS)
Kaufman, H.
1976-01-01
Because application of conventional optimal linear regulator theory to flight controller design requires the capability of measuring and/or estimating the entire state vector, it is of interest to consider procedures for computing controls which are restricted to be linear feedback functions of a lower dimensional output vector and which take into account the presence of measurement noise and process uncertainty. Therefore, a stochastic linear model that was developed is presented which accounts for aircraft parameter and initial uncertainty, measurement noise, turbulence, pilot command and a restricted number of measurable outputs. Optimization with respect to the corresponding output feedback gains was performed for both finite and infinite time performance indices without gradient computation by using Zangwill's modification of a procedure originally proposed by Powell. Results using a seventh order process show the proposed procedures to be very effective.
Model Identification for Optimal Diesel Emissions Control
Stevens, Andrew J.; Sun, Yannan; Song, Xiaobo; Parker, Gordon
2013-06-20
In this paper we develop a model based con- troller for diesel emission reduction using system identification methods. Specifically, our method minimizes the downstream readings from a production NOx sensor while injecting a minimal amount of urea upstream. Based on the linear quadratic estimator we derive the closed form solution to a cost function that accounts for the case some of the system inputs are not controllable. Our cost function can also be tuned to trade-off between input usage and output optimization. Our approach performs better than a production controller in simulation. Our NOx conversion efficiency was 92.7% while the production controller achieved 92.4%. For NH3 conversion, our efficiency was 98.7% compared to 88.5% for the production controller.
Averaging and Linear Programming in Some Singularly Perturbed Problems of Optimal Control
Gaitsgory, Vladimir; Rossomakhine, Sergey
2015-04-15
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 of 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.
Modification of the control modulator (for a klystron)
NASA Astrophysics Data System (ADS)
Heine, Eric
The modulators of the klystron units for pulse injection into an accelerator were modified in order to increase the peak power of the klystrons. The modulators were modified from 4 MW RF power out and 50 micro pulses to 10 MW RF power out and 5 microsec. The required modifications of the operator interface programming are explained.
Design, optimization, and control of tensegrity structures
NASA Astrophysics Data System (ADS)
Masic, Milenko
The contributions of this dissertation may be divided into four categories. The first category involves developing a systematic form-finding method for general and symmetric tensegrity structures. As an extension of the available results, different shape constraints are incorporated in the problem. Methods for treatment of these constraints are considered and proposed. A systematic formulation of the form-finding problem for symmetric tensegrity structures is introduced, and it uses the symmetry to reduce both the number of equations and the number of variables in the problem. The equilibrium analysis of modular tensegrities exploits their peculiar symmetry. The tensegrity similarity transformation completes the contributions in the area of enabling tools for tensegrity form-finding. The second group of contributions develops the methods for optimal mass-to-stiffness-ratio design of tensegrity structures. This technique represents the state-of-the-art for the static design of tensegrity structures. It is an extension of the results available for the topology optimization of truss structures. Besides guaranteeing that the final design satisfies the tensegrity paradigm, the problem constrains the structure from different modes of failure, which makes it very general. The open-loop control of the shape of modular tensegrities is the third contribution of the dissertation. This analytical result offers a closed form solution for the control of the reconfiguration of modular structures. Applications range from the deployment and stowing of large-scale space structures to the locomotion-inducing control for biologically inspired structures. The control algorithm is applicable regardless of the size of the structures, and it represents a very general result for a large class of tensegrities. Controlled deployments of large-scale tensegrity plates and tensegrity towers are shown as examples that demonstrate the full potential of this reconfiguration strategy. The last
Adaptive hybrid optimal quantum control for imprecisely characterized systems.
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. PMID:24996074
2007-01-01
Several modifications that have been made to the NDDO core-core interaction term and to the method of parameter optimization are described. These changes have resulted in a more complete parameter optimization, called PM6, which has, in turn, allowed 70 elements to be parameterized. The average unsigned error (AUE) between calculated and reference heats of formation for 4,492 species was 8.0 kcal mol−1. For the subset of 1,373 compounds involving only the elements H, C, N, O, F, P, S, Cl, and Br, the PM6 AUE was 4.4 kcal mol−1. The equivalent AUE for other methods were: RM1: 5.0, B3LYP 6–31G*: 5.2, PM5: 5.7, PM3: 6.3, HF 6–31G*: 7.4, and AM1: 10.0 kcal mol−1. Several long-standing faults in AM1 and PM3 have been corrected and significant improvements have been made in the prediction of geometries. Figure Calculated structure of the complex ion [Ta6Cl12]2+ (footnote): Reference value in parenthesis Electronic supplementary material The online version of this article (doi:10.1007/s00894-007-0233-4) contains supplementary material, which is available to authorized users. PMID:17828561
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.
Optimal Control of Flows in Moving Domains
NASA Astrophysics Data System (ADS)
Protas, Bartosz; Liao, Wenyuan; Glander, Donn
2006-11-01
This investigation concerns adjoint--based optimization of viscous incompressible flows (the Navier-Stokes problem) coupled with heat conduction involving change of phase (the Stefan problem) and occurring in domains with moving boundaries such as the free and solidification surfaces. This problem is motivated by optimization of advanced welding techniques used in automotive manufacturing. We characterize the sensitivity of a suitable cost functional defined for the system with respect to control (the heat input) using adjoint equations. Given that the shape of the domain is also a dependent variable, characterizing sensitivities necessitates the introduction of ``non-cylindrical'' calculus required to differentiate a cost functional defined on a variable domain. As a result, unlike the forward problem, the adjoint system is defined on a domain with a predetermined evolution in time and also involves ordinary differential equations defined on the domain boundary (``the adjoint transverse system''). We will discuss certain computational issues related to numerical solution of such adjoint problems.
Coherent optimal control of photosynthetic molecules
NASA Astrophysics Data System (ADS)
Caruso, F.; Montangero, S.; Calarco, T.; Huelga, S. F.; Plenio, M. B.
2012-04-01
We demonstrate theoretically that open-loop quantum optimal control techniques can provide efficient tools for the verification of various quantum coherent transport mechanisms in natural and artificial light-harvesting complexes under realistic experimental conditions. To assess the feasibility of possible biocontrol experiments, we introduce the main settings and derive optimally shaped and robust laser pulses that allow for the faithful preparation of specified initial states (such as localized excitation or coherent superposition, i.e., propagating and nonpropagating states) of the photosystem and probe efficiently the subsequent dynamics. With these tools, different transport pathways can be discriminated, which should facilitate the elucidation of genuine quantum dynamical features of photosystems and therefore enhance our understanding of the role that coherent processes may play in actual biological complexes.
Optimal control strategies for coupled quantum dots
NASA Astrophysics Data System (ADS)
Räsänen, Esa; Putaja, Antti; Mardoukhi, Yousof
2013-09-01
Semiconductor quantum dots are ideal candidates for quantum information applications in solid-state technology. However, advanced theoretical and experimental tools are required to coherently control, for example, the electronic charge in these systems. Here we demonstrate how quantum optimal control theory provides a powerful way to manipulate the electronic structure of coupled quantum dots with an extremely high fidelity. As alternative control fields we apply both laser pulses as well as electric gates, respectively. We focus on double and triple quantum dots containing a single electron or two electrons interacting via Coulomb repulsion. In the two-electron situation we also briefly demonstrate the challenges of timedependent density-functional theory within the adiabatic local-density approximation to produce comparable results with the numerically exact approach.
Optimization and Control of Plasma Doping Processes
Raj, Deven M.; Godet, Ludovic; Chamberlain, Nicholas; Hadidi, Kamal; Singh, Vikram; Papasouliotis, George D.
2011-01-07
Plasma doping (PLAD) is a well characterized alternative to beam-line technology, which has already been adopted in high volume manufacturing in the ultra high dose, low energy regime for advanced DRAM technology nodes. As semiconductor technology evolves, the demand for ever lower energy, higher dose implants will continue to grow, and the requirements for process control will become increasingly stringent. During plasma immersion ion implantation, ionized species present in the plasma are extracted and implanted into the wafer, while other processes, such as deposition, etching and sputtering, are competing in parallel. The dopant profile into the substrate results from contributions of all these mechanisms. Using the hardware and plasma composition control features present in the PLAD system to balance the contributions of the above processes, the dopant profile can be modified and dopant retention can be optimized. In this paper, we detail the process control approach used to optimize process performance for low energy, high dose implants, and validate it with plasma and wafer state data.
Optimally designed fields for controlling molecular dynamics
NASA Astrophysics Data System (ADS)
Rabitz, Herschel
1991-10-01
This research concerns the development of molecular control theory techniques for designing optical fields capable of manipulating molecular dynamic phenomena. Although is has been long recognized that lasers should be capable of manipulating dynamic events, many frustrating years of intuitively driven laboratory studies only serve to illustrate the point that the task is complex and defies intuition. The principal new component in the present research is the recognition that this problem falls into the category of control theory and its inherent complexities require the use of modern control theory tools largely developed in the engineering disciplines. Thus, the research has initiated a transfer of the control theory concepts to the molecular scale. Although much contained effort will be needed to fully develop these concepts, the research in this grant set forth the basic components of the theory and carried out illustrative studies involving the design of optical fields capable of controlling rotational, vibrational and electronic degrees of freedom. Optimal control within the quantum mechanical molecular realm represents a frontier area with many possible ultimate applications. At this stage, the theoretical tools need to be joined with merging laboratory optical pulse shaping capabilities to illustrate the power of the concepts.
STATE-OF-THE-ART COMBUSTION MODIFICATION NOX CONTROL FOR STATIONARY COMBUSTION EQUIPMENT
The paper is a brief discussion and summary of state-of-the-art combustion modification NOx control technology for boilers and industrial process combustion equipment. These combustion modification techniques, when properly applied, offer the potential for cost-effective NOx cont...
Optimal digital control of multirate systems
NASA Technical Reports Server (NTRS)
Amit, N.; Powell, J. D.
1981-01-01
Many digitally controlled aerospace systems have widely separated time constants and thus can benefit from the use of two or more sample rates. In this paper, the analysis and synthesis of multirate systems is accomplished by creating an equivalent single rate system and applying existing techniques. The optimal steady state solution of the single rate system is obtained by eigenvector decomposition and then used to compute the periodic solution to the Riccati equation of the original multirate system. An example shows when multirate analysis is necessary and the penalty of various levels of approximations to the exact multirate solution.
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.
Hypersonic Vehicle Trajectory Optimization and Control
NASA Technical Reports Server (NTRS)
Balakrishnan, S. N.; Shen, J.; Grohs, J. R.
1997-01-01
Two classes of neural networks have been developed for the study of hypersonic vehicle trajectory optimization and control. The first one is called an 'adaptive critic'. The uniqueness and main features of this approach are that: (1) they need no external training; (2) they allow variability of initial conditions; and (3) they can serve as feedback control. This is used to solve a 'free final time' two-point boundary value problem that maximizes the mass at the rocket burn-out while satisfying the pre-specified burn-out conditions in velocity, flightpath angle, and altitude. The second neural network is a recurrent network. An interesting feature of this network formulation is that when its inputs are the coefficients of the dynamics and control matrices, the network outputs are the Kalman sequences (with a quadratic cost function); the same network is also used for identifying the coefficients of the dynamics and control matrices. Consequently, we can use it to control a system whose parameters are uncertain. Numerical results are presented which illustrate the potential of these methods.
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.
Controlling modulus and morphology of hydrogel tubes through surface modification.
Enescu, Cristina; Shoichet, Molly S
2004-01-01
Crosslinked, porous poly(2-hydroxyethyl methacrylate-co-methyl methacrylate) (PHEMA-MMA) tubes were prepared in cylindrical glass molds using a new centrifugal casting process developed in our group. The resulting hydrogel tubes have a bi-phasic wall structure, with a spongy inner layer and a gel-like outer layer, the latter of which provides mechanical strength to the tube. While many factors influence wall morphology and, thus, mechanical properties, we focused on the effect of the surface properties of the glass mold in which tubes are synthesized. Specifically, we investigated the impact of a diverse set of silane modifications of the glass mold on tube morphology, elastic modulus and mold release. We treated activated glass surfaces with one of three alkoxysilanes having either ethoxy, amine or fluorocarbon end-groups. Silane-modified glass surfaces were found to be more hydrophobic than the unmodified glass mold, with the most hydrophobic surface being that of the fluorocarbon-terminated silane. The presence of the silane layer on the mold was confirmed by X-ray photoelectron spectroscopy and the stability of this modification was confirmed by examining the surface chemistry of the hydrogel tubes. The biphasic hydrogel tube wall structure was observed for all tubes, yet those tubes synthesized in unmodified molds had a cracked outer morphology, whereas those synthesized in silane-modified molds had a smooth outer morphology. This influenced the mechanical properties of the tubes where tubes synthesized in silane-modified molds had a significantly greater elastic modulus than those tubes synthesized in unmodified molds. Release from the molds was easiest with ethoxy- and amine-functionalized silane mold modifications. PMID:15109099
Alleman, T. L.; Tennant, C. J.; Hayes, R. R.; Miyasato, M.; Oshinuga, A.; Barton, G.; Rumminger, M.; Duggal, V.; Nelson, C.; Ray, M.; Cherrillo, R. A.
2005-11-01
A 2002 Cummins ISM engine was modified to be optimized for operation on gas-to-liquid (GTL) fuel and advanced emission control devices. The engine modifications included increased exhaust gas recirculation (EGR), decreased compression ratio, and reshaped piston and bowl configuration.
POLLUTANT CONTROL TECHNIQUES FOR PACKAGE BOILERS: HARDWARE MODIFICATIONS AND ALTERNATE FUELS
The report gives results of investigations of four ways to control nitrogen oxide (NOx) emissions from package boilers (both field operating boilers and boiler simulators): (1) variations in combustor operating procedure; (2) combustion modification (flue gas recirculation and st...
CONTROL OF UTILITY BOILER AND GAS TURBINE POLLUTANT EMISSIONS BY COMBUSTION MODIFICATION - PHASE I
The report gives results of a field study to assess the applicability of combustion modification techniques to control NOx and other pollutant emissions from utility boilers and gas turbines without causing deleterious side effects. Comprehensive, statistically designed tests wer...
The report gives results of an evaluation of combustion modification techniques for coal-, oil-, and gas-fired utility boilers, with respect to NOx control reduction effectiveness, operational impact, thermal efficiency impact, capital and annualized operating costs, and effect o...
The report gives results of an evaluation of combustion modification techniques for coal-, oil-, and gas-fired utility boilers, with repect to NOx control reduction effectiveness, operational impact, thermal efficiency impact, capital and annualized operating costs, and effect on...
ERIC Educational Resources Information Center
Adams, Gerald R.
1973-01-01
This paper concentrates on one principal disruptive behavior-aggression. Several of the basic determinants of aggression have been summarized and some methods of effective control are reviewed. Guidelines for the implementation of a behavior modification program are presented. (Author)
The report gives results of an environmental assessment of combustion modification techniques for stationary internal combustion engines, with respect to NOx control reduction effectiveness, operational impact, thermal efficiency impact, capital and annualized operating costs, an...
Federal Register 2010, 2011, 2012, 2013, 2014
2011-12-05
... From the Federal Register Online via the Government Publishing Office INTERNATIONAL TRADE COMMISSION Certain Video Game Systems and Controllers; Investigations: Terminations, Modifications and Rulings AGENCY: U.S. International Trade Commission. ACTION: Notice. Section 337 of the Tariff Act of...
Optimal Feedback Controlled Assembly of Perfect Crystals.
Tang, Xun; Rupp, Bradley; Yang, Yuguang; Edwards, Tara D; Grover, Martha A; Bevan, Michael A
2016-07-26
Perfectly ordered states are targets in diverse molecular to microscale systems involving, for example, atomic clusters, protein folding, protein crystallization, nanoparticle superlattices, and colloidal crystals. However, there is no obvious approach to control the assembly of perfectly ordered global free energy minimum structures; near-equilibrium assembly is impractically slow, and faster out-of-equilibrium processes generally terminate in defective states. Here, we demonstrate the rapid and robust assembly of perfect crystals by navigating kinetic bottlenecks using closed-loop control of electric field mediated crystallization of colloidal particles. An optimal policy is computed with dynamic programming using a reaction coordinate based dynamic model. By tracking real-time stochastic particle configurations and adjusting applied fields via feedback, the evolution of unassembled particles is guided through polycrystalline states into single domain crystals. This approach to controlling the assembly of a target structure is based on general principles that make it applicable to a broad range of processes from nano- to microscales (where tuning a global thermodynamic variable yields temporal control over thermal sampling of different states via their relative free energies). PMID:27387146
Optimal Control of Distributed Energy Resources using Model Predictive Control
Mayhorn, Ebony T.; Kalsi, Karanjit; Elizondo, Marcelo A.; Zhang, Wei; Lu, Shuai; Samaan, Nader A.; Butler-Purry, Karen
2012-07-22
In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.
The neural optimal control hierarchy for motor control
NASA Astrophysics Data System (ADS)
DeWolf, T.; Eliasmith, C.
2011-10-01
Our empirical, neuroscientific understanding of biological motor systems has been rapidly growing in recent years. However, this understanding has not been systematically mapped to a quantitative characterization of motor control based in control theory. Here, we attempt to bridge this gap by describing the neural optimal control hierarchy (NOCH), which can serve as a foundation for biologically plausible models of neural motor control. The NOCH has been constructed by taking recent control theoretic models of motor control, analyzing the required processes, generating neurally plausible equivalent calculations and mapping them on to the neural structures that have been empirically identified to form the anatomical basis of motor control. We demonstrate the utility of the NOCH by constructing a simple model based on the identified principles and testing it in two ways. First, we perturb specific anatomical elements of the model and compare the resulting motor behavior with clinical data in which the corresponding area of the brain has been damaged. We show that damaging the assigned functions of the basal ganglia and cerebellum can cause the movement deficiencies seen in patients with Huntington's disease and cerebellar lesions. Second, we demonstrate that single spiking neuron data from our model's motor cortical areas explain major features of single-cell responses recorded from the same primate areas. We suggest that together these results show how NOCH-based models can be used to unify a broad range of data relevant to biological motor control in a quantitative, control theoretic framework.
Lassnig, R.; Hollerer, M.; Striedinger, B.; Fian, A.; Stadlober, B.; Winkler, A.
2015-01-01
In this work we present in situ electrical and surface analytical, as well as ex situ atomic force microscopy (AFM) studies on temperature and surface condition induced pentacene layer growth modifications, leading to the selection of optimized deposition conditions and entailing performance improvements. We prepared p++-silicon/silicon dioxide bottom-gate, gold bottom-contact transistor samples and evaluated the pentacene layer growth for three different surface conditions (sputtered, sputtered + carbon and unsputtered + carbon) at sample temperatures during deposition of 200 K, 300 K and 350 K. The AFM investigations focused on the gold contacts, the silicon dioxide channel region and the highly critical transition area. Evaluations of coverage dependent saturation mobilities, threshold voltages and corresponding AFM analysis were able to confirm that the first 3–4 full monolayers contribute to the majority of charge transport within the channel region. At high temperatures and on sputtered surfaces uniform layer formation in the contact–channel transition area is limited by dewetting, leading to the formation of trenches and the partial development of double layer islands within the channel region instead of full wetting layers. By combining the advantages of an initial high temperature deposition (well-ordered islands in the channel) and a subsequent low temperature deposition (continuous film formation for low contact resistance) we were able to prepare very thin (8 ML) pentacene transistors of comparably high mobility. PMID:26543442
Optimizing cosmic shear surveys to measure modifications to gravity on cosmic scales
NASA Astrophysics Data System (ADS)
Kirk, Donnacha; Laszlo, Istvan; Bridle, Sarah; Bean, Rachel
2013-03-01
We consider how upcoming photometric large-scale structure surveys can be optimized to measure the properties of dark energy (DE) and possible cosmic-scale modifications to General Relativity in light of realistic astrophysical and instrumental systematic uncertainties. In particular, we include flexible descriptions of intrinsic alignments (IAs), galaxy bias and photometric redshift uncertainties in a Fisher Matrix analysis of shear, position and position-shear correlations, including complementary cosmological constraints from the cosmic microwave background. We study the impact of survey trade-offs in depth versus breadth, and redshift quality. We parametrize the results in terms of the Dark Energy Task Force figure of merit, and deviations from General Relativity through an analogous modified gravity (MG) figure of merit. We find that IAs weaken the dependence of figure of merit on area and that, for a fixed observing time, halving the area of a Stage IV reduces the figure of merit by 20 per cent when IAs are not included and by only 10 per cent when IAs are included. While reducing photometric redshift scatter improves constraining power, the dependence is shallow. The variation in constraining power is stronger once IAs are included and is slightly more pronounced for MG constraints than for DE. The inclusion of IAs and galaxy position information reduces the required prior on photometric redshift accuracy by an order of magnitude for both the fiducial Stage III and IV surveys, equivalent to a factor of 100 reduction in the number of spectroscopic galaxies required to calibrate the photometric sample.
Yan, Xiaoxu; Xiao, Kang; Liang, Shuai; Lei, Ting; Liang, Peng; Xue, Tao; Yu, Kaichang; Guan, Jing; Huang, Xia
2014-11-01
Baffles are a key component of an airlift membrane bioreactor (MBR), which could enhance membrane surface shear for fouling control. In order to obtain an optimal hydraulic condition of the reactor, the effects of baffle location and size were systematically explored in this study. Computational fluid dynamics (CFD) was used to investigate the hydrodynamics in a bench-scale airlift flat sheet MBR with various baffle locations and sizes. Validated simulation results showed that side baffles were more effective in elevating membrane surface shear than front baffles. The maximum average shear stress was achieved by adjusting baffle size when both front and side baffles were installed. With the optimized baffle configuration, the shear stress was 10-30% higher than that without baffles at a same aeration intensity (specific air demand per membrane area in the range of 0-0.45m(3)m(-2)h(-1)). The effectiveness of baffles was particularly prominent at lower aeration intensities. PMID:25465790
Optimal control of a delayed SLBS computer virus model
NASA Astrophysics Data System (ADS)
Chen, Lijuan; Hattaf, Khalid; Sun, Jitao
2015-06-01
In this paper, a delayed SLBS computer virus model is firstly proposed. To the best of our knowledge, this is the first time to discuss the optimal control of the SLBS model. By using the optimal control strategy, we present an optimal strategy to minimize the total number of the breakingout computers and the cost associated with toxication or detoxication. We show that an optimal control solution exists for the control problem. Some examples are presented to show the efficiency of this optimal control.
Computational methods to obtain time optimal jet engine control
NASA Technical Reports Server (NTRS)
Basso, R. J.; Leake, R. J.
1976-01-01
Dynamic Programming and the Fletcher-Reeves Conjugate Gradient Method are two existing methods which can be applied to solve a general class of unconstrained fixed time, free right end optimal control problems. New techniques are developed to adapt these methods to solve a time optimal control problem with state variable and control constraints. Specifically, they are applied to compute a time optimal control for a jet engine control problem.
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.
Addressing the human factors issues associated with control room modifications
O`Hara, J.; Stubler, W.; Kramer, J.
1998-03-01
Advanced human-system interface (HSI) technology is being integrated into existing nuclear plants as part of plant modifications and upgrades. The result of this trend is that hybrid HSIs are created, i.e., HSIs containing a mixture of conventional (analog) and advanced (digital) technology. The purpose of the present research is to define the potential effects of hybrid HSIs on personnel performance and plant safety and to develop human factors guidance for safety reviews of them where necessary. In support of this objective, human factors issues associated with hybrid HSIs were identified. The issues were evaluated for their potential significance to plant safety, i.e., their human performance concerns have the potential to compromise plant safety. The issues were then prioritized and a subset was selected for design review guidance development.
Controlled nanopatterning & modifications of materials by energetic ions
NASA Astrophysics Data System (ADS)
Sinha, O. P.
2016-05-01
Compound semiconductors (InP, InAs and GaSb) has been exposed to energetic 3kev Ar+ ions for a varying fluence range of 1013 ions/cm2 to 1018 ions/cm2 at room temperature. Morphological modifications of the irradiated surfaces have been investigated by Scanning Tunneling Microscopy (STM) in UHV conditions. It is observed that InP and GaSb have fluence dependent nanopattering e.g. nanoneedle, aligned nanodots, superimposed nanodots ripple like structures while InAs has little fluence dependent behaviour indicating materials dependent growth of features on irradiated surfaces. Moreover, surface roughness and wavelength of the features are also depending on the materials and fluences. The RMS surface roughness has been found to be increased rapidly in the early stage of irradiation followed by slower escalate rate and later tends to saturate indicating influence of the nonlinear processes.
Optimized exposure control in digital mammography
NASA Astrophysics Data System (ADS)
Shramchenko, Nataliya; Blin, Philippe; Mathey, Claude; Klausz, Remy
2004-05-01
A method for the determination of optimal operating points of digital mammography systems is described. The digital mammography equipment uses a flat panel detector and a bi-metal molybdenum/rhodium x-ray tube. An operating point is defined by the selection of the x-ray tube target material, x-ray filtration, kVp and detector entrance dose. Breast thickness and composition are estimated from a low dose pre-exposure, then used to index tables containing sets of operating points. The operating points are determined using a model of the image chain, which computes contrast to noise ratio (CNR) and average glandular dose (AGD) for all possible exposure conditions and breast thickness and composition combinations. The selected operating points are those which provide the required CNR for the lowest AGD. An AGD reduction of 30% to 50% can be achieved for comparable Image Quality, relative to current operating points. Resulting from the optimization process, the rhodium target is used in more than 75% of cases. Measurements of CNR and AGD have been performed on various tissue equivalent materials with good agreement between calculated and measured values. The proposed method provides full Image Quality benefit of digital mammography while minimizing dose to patients in a controlled and predictive way.
Optimal control of orbital transfer vehicles
NASA Technical Reports Server (NTRS)
Vinh, N. X.
1983-01-01
During the past two decades, considerable research effort has been spent to convincingly prove that the use of aerodynamic forces to assist in the orbital transfer can significantly reduce the fuel consumption as compared to the pure propulsive mode. Since in this aeroassisted mode, preliminary maneuvers in the vacuum effect the resulting performance in the atmospheric phase, and vice versa, the two, space and atmospheric maneuvers, are, to a great extent, coupled. This paper summarizes, via optimal control theory, the fundamental results in the problem of orbital transfer using combined propulsive and aerodynamic forces. For the atmospheric phase, the use of Chapman's variables reduced the number of the physical characteristics of the vehicle and the atmosphere to a minimum and hence allows a better generalization of the results. The paper concludes with some illustrative examples.
A modified method of vibration surveillance by using the optimal control at energy performance index
NASA Astrophysics Data System (ADS)
Kaliński, Krzysztof J.; Galewski, Marek A.
2015-06-01
A method of vibration surveillance by using the optimal control at energy performance index has been creatively modified. The suggested original modification depends on consideration of direct relationship between the measured acceleration signal and the optimal control command. The paper presents the results of experiments and Hardware-in-the-loop simulations of a new active vibration reduction algorithm based on the energy performance index idea modified in such a way, that it directly utilises the acceleration feedback signal. Promising prospects towards real application of the modified method in case of the high speed milling are predicted as well.
Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints
Kmet', Tibor; Kmet'ova, Maria
2009-09-09
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.
On a Highly Nonlinear Self-Obstacle Optimal Control Problem
Di Donato, Daniela; Mugnai, Dimitri
2015-10-15
We consider a non-quadratic optimal control problem associated to a nonlinear elliptic variational inequality, where the obstacle is the control itself. We show that, fixed a desired profile, there exists an optimal solution which is not far from it. Detailed characterizations of the optimal solution are given, also in terms of approximating problems.
Skinner Rusk unified formalism for optimal control systems and applications
NASA Astrophysics Data System (ADS)
Barbero-Liñán, María; Echeverría-Enríquez, Arturo; Martín de Diego, David; Muñoz-Lecanda, Miguel C.; Román-Roy, Narciso
2007-10-01
A geometric approach to time-dependent optimal control problems is proposed. This formulation is based on the Skinner and Rusk formalism for Lagrangian and Hamiltonian systems. The corresponding unified formalism developed for optimal control systems allows us to formulate geometrically the necessary conditions given by a weak form of Pontryagin's maximum principle, provided that the differentiability with respect to controls is assumed and the space of controls is open. Furthermore, our method is also valid for implicit optimal control systems and, in particular, for the so-called descriptor systems (optimal control problems including both differential and algebraic equations).
2012-01-01
Background Aspergillus niger was selected as a host for producing itaconic acid due to its versatile and tolerant character in various growth environments, and its extremely high capacity of accumulating the precursor of itaconic acid: citric acid. Expressing the CAD gene from Aspergillus terreus opened the metabolic pathway towards itaconic acid in A. niger. In order to increase the production level, we continued by modifying its genome and optimizing cultivation media. Results Based on the results of previous transcriptomics studies and research from other groups, two genes : gpdA encoding the glyceraldehyde −3-dehydrogenase (GPD) and hbd1 encoding a flavohemoglobin domain (HBD) were overexpressed in A. niger. Besides, new media were designed based on a reference medium for A. terreus. To analyze large numbers of cultures, we developed an approach for screening both fungal transformants and various media in 96-well micro-titer plates. The hbd1 transformants (HBD 2.2/2.5) did not improve itaconic acid titer while the gpdA transformant (GPD 4.3) decreased the itaconic acid production. Using 20 different media, copper was discovered to have a positive influence on itaconic acid production. Effects observed in the micro-titer plate screening were confirmed in controlled batch fermentation. Conclusions The performance of gpdA and hbd1 transformants was found not to be beneficial for itaconic acid production using the tested cultivation conditions. Medium optimization showed that, copper was positively correlated with improved itaconic acid production. Interestingly, the optimal conditions for itaconic acid clearly differ from conditions optimal for citric- and oxalic acid production. PMID:22925689
How Well Can We Control Dyslipidemias Through Lifestyle Modifications?
Riccardi, Gabriele; Vaccaro, Olga; Costabile, Giuseppina; Rivellese, Angela A
2016-07-01
The role for lifestyle modifications to correct dyslipidemia(s) is reviewed. Dietary composition is crucial. Replacing saturated fat with MUFA or n-6 PUFA lowers plasma low-density lipoproteins (LDL) cholesterol and ameliorates the LDL/HDL ratio. Replacing saturated fat with carbohydrates has diverging effects due to the heterogeneity of carbohydrate foods. Diets rich in refined carbohydrates increase fasting and postprandial triglycerides, whereas the consumption of fiber-rich, low GI foods lowers LDL cholesterol with no detrimental effects on triglycerides. The role of polyphenols is debated: available evidence suggests a lowering effect of polyphenol-rich foods on postprandial triglycerides. As for functional foods, health claims on a cholesterol lowering effect of psyllium, beta-glucans and phytosterols are accepted by regulatory agencies. The importance of alcohol intake, weight reduction, and physical activity is discussed. In conclusion, there is evidence that lifestyle affects plasma lipid. A multifactorial approach including multiple changes with additive effects is the best option. This may also ensure feasibility and durability. The traditional Mediterranean way of life can represent a useful model. PMID:27216846
Modification of wave-cut and faulting-controlled landforms.
Hanks, T.C.; Bucknam, R.C.; Lajoie, K.R.; Wallace, R.E.
1984-01-01
From a casual observation that the form of degraded fault scarps resembles the error function, this investigation proceeds through an elementary diffusion equation representation of landform evolution to the application of the resulting equations to the modern topography of scarplike landforms. The value of K = 1 GKG (K = 'mass diffusivity'; 1 GKG = 1m2/ka) may be generally applicable as a good first approximation, to the modification of alluvial terranes within the semiarid regions of the western United States. The Lake Bonneville shoreline K is the basis for dating four sets of fault scarps in west-central Utah. The Drum Mountains fault scarps date at 3.6 to 5.7 ka BP. Fault scarps along the eastern base of the Fish Springs Range are very young, 3 ka BP. We estimate the age of fault scarps along the western flank of the Oquirrh Mountains to be 32 ka B.P. Fault scarps along the NE margin of the Sheeprock Mountains are even older, 53 ka BP. -from Authors
Optimization and quality control of computed radiography
NASA Astrophysics Data System (ADS)
Willis, Charles E.; Weiser, John C.; Leckie, Robert G.; Romlein, John R.; Norton, Gary S.
1994-05-01
Computed radiography (CR) is a relatively new technique for projection radiography. Few hospitals have CR devices in routine service and only a handful have more than one CR unit. As such, the clinical knowledge base does not yet exist to establish quality control (QC) procedures for CR devices. Without assurance that CR systems are operating within nominal limits, efforts to optimize CR performance are limited in value. A complete CR system includes detector plates that vary in response, cassettes, an electro-optical system for developing the image, computer algorithms for processing the raw image, and a hard copy output device. All of these subsystems are subject to variations in performance that can degrade image quality. Using CR manufacturer documentation, we have defined acceptance protocols for two different Fuji CR devices, the FCR 7000 and the AC1+, and have applied these tests to ten individual machines. We have begun to establish baseline performance measures and to determine measurement frequencies. CR QC is only one component of the overall quality control for totally digital radiology departments.
Practical synchronization on complex dynamical networks via optimal pinning control.
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. PMID:26274112
Optimal and suboptimal control technique for aircraft spin recovery
NASA Technical Reports Server (NTRS)
Young, J. W.
1974-01-01
An analytic investigation has been made of procedures for effecting recovery from equilibrium spin conditions for three assumed aircraft configurations. Three approaches which utilize conventional aerodynamic controls are investigated. Included are a constant control recovery mode, optimal recoveries, and a suboptimal control logic patterned after optimal recovery results. The optimal and suboptimal techniques are shown to yield a significant improvement in recovery performance over that attained by using a constant control recovery procedure.
Software Architecture for Simultaneous Process Control and Software Development/Modification
Lenarduzzi, Roberto; Hileman, Michael S; McMillan, David E; Holmes Jr, William; Blankenship, Mark; Wilder, Terry
2011-01-01
A software architecture is described that allows modification of some application code sections while the remainder of the application continues executing. This architecture facilitates long term testing and process control because the overall process need not be stopped and restarted to allow modifications or additions to the software. A working implementation using National Instruments LabVIEW{trademark} sub-panel and shared variable features is described as an example. This architecture provides several benefits in both the program development and execution environments. The software is easier to maintain and it is not necessary to recompile the entire program after a modification.
Gradient Optimization for Analytic conTrols - GOAT
NASA Astrophysics Data System (ADS)
Assémat, Elie; Machnes, Shai; Tannor, David; Wilhelm-Mauch, Frank
Quantum optimal control becomes a necessary step in a number of studies in the quantum realm. Recent experimental advances showed that superconducting qubits can be controlled with an impressive accuracy. However, most of the standard optimal control algorithms are not designed to manage such high accuracy. To tackle this issue, a novel quantum optimal control algorithm have been introduced: the Gradient Optimization for Analytic conTrols (GOAT). It avoids the piecewise constant approximation of the control pulse used by standard algorithms. This allows an efficient implementation of very high accuracy optimization. It also includes a novel method to compute the gradient that provides many advantages, e.g. the absence of backpropagation or the natural route to optimize the robustness of the control pulses. This talk will present the GOAT algorithm and a few applications to transmons systems.
NASA Technical Reports Server (NTRS)
Little, G. R.
1976-01-01
The AN/APQ-153 fire control radar modified to provide angle tracking was evaluated for improved performance. The frequency agile modifications are discussed along with the range-rate improvement modifications, and the radar to computer interface. A parametric design and comparison of noncoherent and coherent radar systems are presented. It is shown that the shuttle rendezvous range and range-rate requirements can be made by a Ku-Band noncoherent pulse radar.
Decentralized optimal control of dynamical systems under uncertainty
NASA Astrophysics Data System (ADS)
Gabasov, R.; Dmitruk, N. M.; Kirillova, F. M.
2011-07-01
The problem of optimal control of a group of interconnected dynamical objects under uncertainty is considered. The cases are examined in which the centralized control of the group of objects is impossible due to delay in the channel for information exchange between the group members. Optimal self-control algorithms in real time for each dynamical object are proposed. Various types of a priori and current information about the behavior of the group members and about uncertainties in the system are examined. The proposed methods supplement the earlier developed optimal control methods for an individual dynamical system and the methods of decentralized optimal control of deterministic objects. The results are illustrated with examples.
A Multiobjective Optimization Framework for Stochastic Control of Complex Systems
Malikopoulos, Andreas; Maroulas, Vasileios; Xiong, Professor Jie
2015-01-01
This paper addresses the problem of minimizing the long-run expected average cost of a complex system consisting of subsystems that interact with each other and the environment. We treat the stochastic control problem as a multiobjective optimization problem of the one-stage expected costs of the subsystems, and we show that the control policy yielding the Pareto optimal solution is an optimal control policy that minimizes the average cost criterion for the entire system. For practical situations with constraints consistent to those we study here, our results imply that the Pareto control policy may be of value in deriving online an optimal control policy in complex systems.
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.
33 CFR 203.47 - Modifications to non-Federal flood control works.
Code of Federal Regulations, 2013 CFR
2013-07-01
... flood control works. 203.47 Section 203.47 Navigation and Navigable Waters CORPS OF ENGINEERS... DISASTER PROCEDURES Rehabilitation Assistance for Flood Control Works Damaged by Flood or Coastal Storm: The Corps Rehabilitation and Inspection Program § 203.47 Modifications to non-Federal flood...
33 CFR 203.47 - Modifications to non-Federal flood control works.
Code of Federal Regulations, 2014 CFR
2014-07-01
... flood control works. 203.47 Section 203.47 Navigation and Navigable Waters CORPS OF ENGINEERS... DISASTER PROCEDURES Rehabilitation Assistance for Flood Control Works Damaged by Flood or Coastal Storm: The Corps Rehabilitation and Inspection Program § 203.47 Modifications to non-Federal flood...
33 CFR 203.47 - Modifications to non-Federal flood control works.
Code of Federal Regulations, 2012 CFR
2012-07-01
... flood control works. 203.47 Section 203.47 Navigation and Navigable Waters CORPS OF ENGINEERS... DISASTER PROCEDURES Rehabilitation Assistance for Flood Control Works Damaged by Flood or Coastal Storm: The Corps Rehabilitation and Inspection Program § 203.47 Modifications to non-Federal flood...
33 CFR 203.47 - Modifications to non-Federal flood control works.
Code of Federal Regulations, 2011 CFR
2011-07-01
... flood control works. 203.47 Section 203.47 Navigation and Navigable Waters CORPS OF ENGINEERS... DISASTER PROCEDURES Rehabilitation Assistance for Flood Control Works Damaged by Flood or Coastal Storm: The Corps Rehabilitation and Inspection Program § 203.47 Modifications to non-Federal flood...
33 CFR 203.47 - Modifications to non-Federal flood control works.
Code of Federal Regulations, 2010 CFR
2010-07-01
... flood control works. 203.47 Section 203.47 Navigation and Navigable Waters CORPS OF ENGINEERS... DISASTER PROCEDURES Rehabilitation Assistance for Flood Control Works Damaged by Flood or Coastal Storm: The Corps Rehabilitation and Inspection Program § 203.47 Modifications to non-Federal flood...
Dolejsi, Erich; Bodenstorfer, Bernhard; Frommlet, Florian
2014-01-01
The prevailing method of analyzing GWAS data is still to test each marker individually, although from a statistical point of view it is quite obvious that in case of complex traits such single marker tests are not ideal. Recently several model selection approaches for GWAS have been suggested, most of them based on LASSO-type procedures. Here we will discuss an alternative model selection approach which is based on a modification of the Bayesian Information Criterion (mBIC2) which was previously shown to have certain asymptotic optimality properties in terms of minimizing the misclassification error. Heuristic search strategies are introduced which attempt to find the model which minimizes mBIC2, and which are efficient enough to allow the analysis of GWAS data. Our approach is implemented in a software package called MOSGWA. Its performance in case control GWAS is compared with the two algorithms HLASSO and d-GWASelect, as well as with single marker tests, where we performed a simulation study based on real SNP data from the POPRES sample. Our results show that MOSGWA performs slightly better than HLASSO, where specifically for more complex models MOSGWA is more powerful with only a slight increase in Type I error. On the other hand according to our simulations GWASelect does not at all control the type I error when used to automatically determine the number of important SNPs. We also reanalyze the GWAS data from the Wellcome Trust Case-Control Consortium and compare the findings of the different procedures, where MOSGWA detects for complex diseases a number of interesting SNPs which are not found by other methods. PMID:25061809
Dolejsi, Erich; Bodenstorfer, Bernhard; Frommlet, Florian
2014-01-01
The prevailing method of analyzing GWAS data is still to test each marker individually, although from a statistical point of view it is quite obvious that in case of complex traits such single marker tests are not ideal. Recently several model selection approaches for GWAS have been suggested, most of them based on LASSO-type procedures. Here we will discuss an alternative model selection approach which is based on a modification of the Bayesian Information Criterion (mBIC2) which was previously shown to have certain asymptotic optimality properties in terms of minimizing the misclassification error. Heuristic search strategies are introduced which attempt to find the model which minimizes mBIC2, and which are efficient enough to allow the analysis of GWAS data. Our approach is implemented in a software package called MOSGWA. Its performance in case control GWAS is compared with the two algorithms HLASSO and d-GWASelect, as well as with single marker tests, where we performed a simulation study based on real SNP data from the POPRES sample. Our results show that MOSGWA performs slightly better than HLASSO, where specifically for more complex models MOSGWA is more powerful with only a slight increase in Type I error. On the other hand according to our simulations GWASelect does not at all control the type I error when used to automatically determine the number of important SNPs. We also reanalyze the GWAS data from the Wellcome Trust Case-Control Consortium and compare the findings of the different procedures, where MOSGWA detects for complex diseases a number of interesting SNPs which are not found by other methods. PMID:25061809
Optimal stochastic control in natural resource management: Framework and examples
Williams, B.K.
1982-01-01
A framework is presented for the application of optimal control methods to natural resource problems. An expression of the optimal control problem appropriate for renewable natural resources is given and its application to Markovian systems is presented in some detail. Three general approaches are outlined for determining optimal control of infinite time horizon systems and three examples from the natural resource literature are used for illustration.
Nanoparticle-Based Surface Modifications for Microtribology Control and Superhydrophobicity
NASA Astrophysics Data System (ADS)
Hurst, Kendall Matthew
2010-11-01
contact" between two contacting surfaces. The studies found that AuNP thin films produced using the lowest initial concentrations of nanoparticles in solution produced estimated real contact areas of around 1%, reducing the adhesion of oxidized Si (100) surfaces from about 37 mJ/m2 down to 0.02 mJ/m 2. In addition, the reducing in real contact area effectively reduced the coefficient of static friction between silicon-based surfaces due to the extremely high dependence of stiction on friction and wear at the microscale. This work also investigated methods of permanently immobilizing AuNP-based films on the silicon surfaces of microstructures in order to create more mechanically robust coatings. The use of organic self-assembled monolayers (SAMs) functionalized with tail-groups known to bond to metallic surfaces were effective in producing much more durable coatings as opposed to non-immobilized AuNP films. Chemical vapor deposition (CVD) techniques were also used to coat rough AuNP films with very thin films of silica (SiO2) to create a robust, rough surface. This method was also very effective in creating a durable coating which is capable of reducing the adhesion energy and friction between two microscale surfaces for extended periods of time. Similar CVD techniques were also used to begin investigating the production of alumina nanoparticle-based superhydrophobic films for use in consumer electronics. Overall, the work presented in this dissertation illustrates that engineered nanoparticle-based surface modifications can be extremely effective in the reduction of the inherent interfacial phenomena that exist on microfabricated systems. This work is can potentially lead us into a new age of the miniaturization of mechanical and electronic devices.
Optimizing the controllability of arbitrary networks with genetic algorithm
NASA Astrophysics Data System (ADS)
Li, Xin-Feng; Lu, Zhe-Ming
2016-04-01
Recently, as the controllability of complex networks attracts much attention, how to optimize networks' controllability has become a common and urgent problem. In this paper, we develop an efficient genetic algorithm oriented optimization tool to optimize the controllability of arbitrary networks consisting of both state nodes and control nodes under Popov-Belevitch-Hautus rank condition. The experimental results on a number of benchmark networks show the effectiveness of this method and the evolution of network topology is captured. Furthermore, we explore how network structure affects its controllability and find that the sparser a network is, the more control nodes are needed to control it and the larger the differences between node degrees, the more control nodes are needed to achieve the full control. Our framework provides an alternative to controllability optimization and can be applied to arbitrary networks without any limitations.
Network Upgrade for the SLC: Control System Modifications
Crane, M.; Mackenzie, R.; Sass, R.; Himel, T.; /SLAC
2011-09-09
Current communications between the SLAC Linear Collider control system central host and the SLCmicros is built upon the SLAC developed SLCNET communication hardware and protocols. We will describe how the Internet Suite of protocols (TCP/IP) are used to replace the SLCNET protocol interface. The major communication pathways and their individual requirements are described. A proxy server is used to reduce the number of total system TCP/IP connections. The SLCmicros were upgraded to use Ethernet and TCP/IP as well as SLCNET. Design choices and implementation experiences are addressed.
Modification of piezoelectric vibratory gyroscope resonator parameters by feedback control.
Loveday, P W; Rogers, C A
1998-01-01
A method for analyzing the effect of feedback control on the dynamics of piezoelectric resonators used in vibratory gyroscopes has been developed. This method can be used to determine the feasibility of replacing the traditional mechanical balancing operations, used to adjust the resonant frequency, by displacement feedback and for determining the velocity feedback required to produce a particular bandwidth. Experiments were performed on a cylindrical resonator with discrete piezoelectric actuation and sensing elements to demonstrate the principles. Good agreement between analysis and experiment was obtained, and it was shown that this type of resonator could be balanced by displacement feedback. The analysis method presented also is applicable to micromachined piezoelectric gyroscopes. PMID:18244281
Optimal dynamic control of resources in a distributed system
NASA Technical Reports Server (NTRS)
Shin, Kang G.; Krishna, C. M.; Lee, Yann-Hang
1989-01-01
The authors quantitatively formulate the problem of controlling resources in a distributed system so as to optimize a reward function and derive optimal control strategies using Markov decision theory. The control variables treated are quite general; they could be control decisions related to system configuration, repair, diagnostics, files, or data. Two algorithms for resource control in distributed systems are derived for time-invariant and periodic environments, respectively. A detailed example to demonstrate the power and usefulness of the approach is provided.
Controlled modification of multiwalled carbon nanotubes with Zno nanostructures
Wang Xiuying; Xia Baiying; Zhu Xingfu; Chen Jiesheng; Qiu Shilun; Li Jixue
2008-04-15
Multiwalled carbon nanotubes (MWNTs) have been successfully modified with ZnO nanostructures by zinc-ammonitum complex ion covalently attached to the MWNTs through the C-N bonds. Flower-like ZnO on the tips of MWNTs and ZnO nanoparticles on the surface of MWNTs have been obtained, respectively, via adjusting the reaction time. The modified MWNTs have been characterized with X-ray diffraction, scanning electron and transmission electron microscopy. A growth mechanism has been proposed in which the soaking time plays a key role in controlling the size, morphology, and site of ZnO nanostructures. Photoluminescence properties of the as-synthesized products have also been investigated. - Multiwalled carbon nanotube (MWNT)/flower-like ZnO heterojunctions and MWNT/ZnO nanoparticle composites were prepared by zinc-ammonitum complex ion covalently attached to the MWNTs through the C-N bonds via adjusting the reaction time. A growth mechanism has been proposed in which the soaking time plays a key role in controlling the size, morphology, and site of ZnO nanostructures.
Optimal coordination and control of posture and movements.
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. PMID:19671443
NASA Astrophysics Data System (ADS)
Kim, C. H.; Park, H. J.; Lee, J.; Lee, H. W.; Lee, K. D.
2015-05-01
This paper develops a discrete optimal control based on the multi-rate observer method for electromagnetic suspension systems in order to levitate the vehicle, maintaining the desired gap. The proposed multi-rate compensator consists of two parts which are the discrete Kalman filter and the optimal control law. The Kalman filter estimates all states with fast sampling rate time, using a slowly measured output from the gap sensor. The optimal control law is determined by linear matrix inequality optimization for the discrete time multiple input system obtained by the lifting operator. The proposed multi-rate controller has the advantages to guarantee the stability of the slow-rate optimal control and maintain the performance of fast-rate control. The simulation and experiment show the effectiveness of the proposed control method.
A multiple objective optimization approach to aircraft control systems design
NASA Technical Reports Server (NTRS)
Tabak, D.; Schy, A. A.; Johnson, K. G.; Giesy, D. P.
1979-01-01
The design of an aircraft lateral control system, subject to several performance criteria and constraints, is considered. While in the previous studies of the same model a single criterion optimization, with other performance requirements expressed as constraints, has been pursued, the current approach involves a multiple criteria optimization. In particular, a Pareto optimal solution is sought.
H2-optimal control with generalized state-space models for use in control-structure optimization
NASA Technical Reports Server (NTRS)
Wette, Matt
1991-01-01
Several advances are provided solving combined control-structure optimization problems. The author has extended solutions from H2 optimal control theory to the use of generalized state space models. The generalized state space models preserve the sparsity inherent in finite element models and hence provide some promise for handling very large problems. Also, expressions for the gradient of the optimal control cost are derived which use the generalized state space models.
Optimal control of blending and melting of copper concentrates
NASA Astrophysics Data System (ADS)
Imanbekova, Ulzhan; Hotra, Oleksandra; Koshimbayev, Shamil; Popiel, Piotr; Tanaś, Jacek
2015-09-01
The mathematical models of the melting process, the optimization criterion and constraints on the input and controlling variables and the values of the conductivities of the melt under the electrodes and the phase voltages are used to solve the optimization problem of the electrical regime of the electric furnace. In this paper the optimal variant of the electrical regime of the furnace for the electromelting and blending processing of copper concentrates is considered, which can be provided by the optimal immersion of electrodes. The optimal parameters of the technological process of electromelting and blending are calculated. The proposed mathematical model could be applied for melting process optimization.
Waterwall corrosion after combustion modifications for NOx control
Davis, K.; Eddings, E.; Harding, S.; Heap, M.; Valentine, J.
1999-07-01
Much of the information concerning the mechanisms contributing to waterwall corrosion in coal fired boilers has been derived from examination of tube/deposit sections collected after the boiler has been taken out of service. In some circles this is referred to as the cut, polish and guess approach. The potential problems associated with staged combustion were recognized when it was first proposed for coal fired boilers. There were concerns about reduced thermal efficiency due to the presence of unburned carbon and the potential for increased waterwall corrosion rated in the lower furnace which is subjected to sub-stoichiometric conditions. Developers claimed that unburned carbon was not a problem and improving coal particle fineness would reduce unburned carbon. Field tests had often shown no significant increase in tube wastage rates. Yet recent experience with plants that have been retrofitted with advanced low-NO{sub x} firing systems is contrary to this optimistic view. Almost invariably, carbon in the fly ash increases and several plants are reporting excessive waterwall wastage tube rates after retrofitting low-NO{sub x} firing systems. Regardless of the reasons, in-furnace NO{sub x} control technologies may not be a low cost panacea for more stringent NO{sub x} emission limits as was originally thought. This paper describes the use of a reacting, computational fluids dynamic model to simulate boilers fitted with advanced low-NO{sub x} firing systems to investigate the link between firing system characteristics and the conditions that might affect waterwall corrosion such as local hydrogen sulfide concentration, heat flux, etc. The model does not predict corrosion directly unless the corrosion rate can be linked to the predicted properties.
Ruiz-Cruz, Riemann; Sanchez, Edgar N; Ornelas-Tellez, Fernando; Loukianov, Alexander G; Harley, Ronald G
2013-12-01
In this paper, the authors propose a particle swarm optimization (PSO) for a discrete-time inverse optimal control scheme of a doubly fed induction generator (DFIG). For the inverse optimal scheme, a control Lyapunov function (CLF) is proposed to obtain an inverse optimal control law in order to achieve trajectory tracking. A posteriori, it is established that this control law minimizes a meaningful cost function. The CLFs depend on matrix selection in order to achieve the control objectives; this matrix is determined by two mechanisms: initially, fixed parameters are proposed for this matrix by a trial-and-error method and then by using the PSO algorithm. The inverse optimal control scheme is illustrated via simulations for the DFIG, including the comparison between both mechanisms. PMID:24273145
Nonlinear model predictive control based on collective neurodynamic optimization.
Yan, Zheng; Wang, Jun
2015-04-01
In general, nonlinear model predictive control (NMPC) entails solving a sequential global optimization problem with a nonconvex cost function or constraints. This paper presents a novel collective neurodynamic optimization approach to NMPC without linearization. Utilizing a group of recurrent neural networks (RNNs), the proposed collective neurodynamic optimization approach searches for optimal solutions to global optimization problems by emulating brainstorming. Each RNN is guaranteed to converge to a candidate solution by performing constrained local search. By exchanging information and iteratively improving the starting and restarting points of each RNN using the information of local and global best known solutions in a framework of particle swarm optimization, the group of RNNs is able to reach global optimal solutions to global optimization problems. The essence of the proposed collective neurodynamic optimization approach lies in the integration of capabilities of global search and precise local search. The simulation results of many cases are discussed to substantiate the effectiveness and the characteristics of the proposed approach. PMID:25608315
Stochastic Optimal Control for Series Hybrid Electric Vehicles
Malikopoulos, Andreas
2013-01-01
Increasing demand for improving fuel economy and reducing emissions has stimulated significant research and investment in hybrid propulsion systems. In this paper, we address the problem of optimizing online the supervisory control in a series hybrid configuration by modeling its operation as a controlled Markov chain using the average cost criterion. We treat the stochastic optimal control problem as a dual constrained optimization problem. We show that the control policy that yields higher probability distribution to the states with low cost and lower probability distribution to the states with high cost is an optimal control policy, defined as an equilibrium control policy. We demonstrate the effectiveness of the efficiency of the proposed controller in a series hybrid configuration and compare it with a thermostat-type controller.
NASA Astrophysics Data System (ADS)
Kabo, K. S.; Yacob, A. R.; Bakar, W. A. W. A.; Buang, N. A.; Bello, A. M.; Ruskam, A.
2016-07-01
Environmentally benign zinc oxide (ZnO) was modified with 0-15% (wt.) potassium through wet impregnation and used in transesterification of rice bran oil (RBO) to form biodiesel. The catalyst was characterized by X-Ray powder Diffraction (XRD), its basic sites determined by back titration and Response Surface Methodology (RSM) Box-Behnken Design (BBD) was used to optimize the modification process variables on the basic sites of the catalyst. The transesterification product, biodiesel was analyzed by Nuclear Magnetic Resonance (NMR) spectroscopy. The result reveals K-modified ZnO with highly increased basic sites. Quadratic model with high regression R2 = 0.9995 was obtained from the ANOVA of modification process, optimization at maximum basic sites criterion gave optimum modification conditions of K-loading = 8.5% (wt.), calcination temperature = 480 oC and time = 4 hours with response and basic sites = 8.14 mmol/g which is in close agreement with the experimental value of 7.64 mmol/g. The catalyst was used and a value of 95.53% biodiesel conversion was obtained and effect of potassium leaching was not significant in the process
A Framework for Optimal Control Allocation with Structural Load Constraints
NASA Technical Reports Server (NTRS)
Frost, Susan A.; Taylor, Brian R.; Jutte, Christine V.; Burken, John J.; Trinh, Khanh V.; Bodson, Marc
2010-01-01
Conventional aircraft generally employ mixing algorithms or lookup tables to determine control surface deflections needed to achieve moments commanded by the flight control system. Control allocation is the problem of converting desired moments into control effector commands. Next generation aircraft may have many multipurpose, redundant control surfaces, adding considerable complexity to the control allocation problem. These issues can be addressed with optimal control allocation. Most optimal control allocation algorithms have control surface position and rate constraints. However, these constraints are insufficient to ensure that the aircraft's structural load limits will not be exceeded by commanded surface deflections. In this paper, a framework is proposed to enable a flight control system with optimal control allocation to incorporate real-time structural load feedback and structural load constraints. A proof of concept simulation that demonstrates the framework in a simulation of a generic transport aircraft is presented.
Optimizing Sensor and Actuator Arrays for ASAC Noise Control
NASA Technical Reports Server (NTRS)
Palumbo, Dan; Cabell, Ran
2000-01-01
This paper summarizes the development of an approach to optimizing the locations for arrays of sensors and actuators in active noise control systems. A type of directed combinatorial search, called Tabu Search, is used to select an optimal configuration from a much larger set of candidate locations. The benefit of using an optimized set is demonstrated. The importance of limiting actuator forces to realistic levels when evaluating the cost function is discussed. Results of flight testing an optimized system are presented. Although the technique has been applied primarily to Active Structural Acoustic Control systems, it can be adapted for use in other active noise control implementations.
Controlled levels of protein modification through a chromatography-mediated bioconjugation
Kwant, Richard L.; Jaffe, Jake; Palmere, Peter J.; Francis, Matthew B.
2015-02-27
Synthetically modified proteins are increasingly finding applications as well-defined scaffolds for materials. In practice it remains difficult to construct bioconjugates with precise levels of modification because of the limited number of repeated functional groups on proteins. This article describes a method to control the level of protein modification in cases where there exist multiple potential modification sites. A protein is first tagged with a handle using any of a variety of modification chemistries. This handle is used to isolate proteins with a particular number of modifications via affinity chromatography, and then the handle is elaborated with a desired moiety usingmore » an oxidative coupling reaction. This method results in a sample of protein with a well-defined number of modifications, and we find it particularly applicable to systems like protein homomultimers in which there is no way to discern between chemically identical subunits. We demonstrate the use of this method in the construction of a protein-templated light-harvesting mimic, a type of system which has historically been difficult to make in a well-defined manner.« less
Controlled levels of protein modification through a chromatography-mediated bioconjugation
Kwant, Richard L.; Jaffe, Jake; Palmere, Peter J.; Francis, Matthew B.
2015-02-27
Synthetically modified proteins are increasingly finding applications as well-defined scaffolds for materials. In practice it remains difficult to construct bioconjugates with precise levels of modification because of the limited number of repeated functional groups on proteins. This article describes a method to control the level of protein modification in cases where there exist multiple potential modification sites. A protein is first tagged with a handle using any of a variety of modification chemistries. This handle is used to isolate proteins with a particular number of modifications via affinity chromatography, and then the handle is elaborated with a desired moiety using an oxidative coupling reaction. This method results in a sample of protein with a well-defined number of modifications, and we find it particularly applicable to systems like protein homomultimers in which there is no way to discern between chemically identical subunits. We demonstrate the use of this method in the construction of a protein-templated light-harvesting mimic, a type of system which has historically been difficult to make in a well-defined manner.
Pilot-optimal multivariable control synthesis by output feedback
NASA Technical Reports Server (NTRS)
Schmidt, D. K.; Innocenti, M.
1981-01-01
A control system design approach for optimal stability augmentation, systems, using limited state feedback theory with the specific inclusion of the human pilot in the loop is presented. The methodology is especially suitable for application to flight vehicles exhibiting nonconventional dynamic characteristics and for which quantitative handling qualities specifications are not available. The design is based on a correlation between pilot ratings and objective function of the optimal control model of the human pilot. Simultaneous optimization for augmentation and pilot gains are required.
Finding Optimal Gains In Linear-Quadratic Control Problems
NASA Technical Reports Server (NTRS)
Milman, Mark H.; Scheid, Robert E., Jr.
1990-01-01
Analytical method based on Volterra factorization leads to new approximations for optimal control gains in finite-time linear-quadratic control problem of system having infinite number of dimensions. Circumvents need to analyze and solve Riccati equations and provides more transparent connection between dynamics of system and optimal gain.
EFFICIENCY OPTIMIZATION CONTROL OF AC INDUCTION MOTORS: INITIAL LABORATORY RESULTS
The report discusses the development of a fuzzy logic, energy-optimizing controller to improve the efficiency of motor/drive combinations that operate at varying loads and speeds. his energy optimizer is complemented by a sensorless speed controller that maintains motor shaft rev...
A criterion for joint optimization of identification and robust control
NASA Technical Reports Server (NTRS)
Bayard, D. S.; Yam, Y.; Mettler, E.
1992-01-01
A criterion for system identification is developed that is consistent with the intended used of the fitted model for modern robust control synthesis. Specifically, a joint optimization problem is posed which simultaneously solves the plant model estimate and control design, so as to optimize robust performance over the set of plants consistent with a specified experimental data set.
A quadratic weight selection algorithm. [for optimal flight control
NASA Technical Reports Server (NTRS)
Broussard, J. R.
1981-01-01
A new numerical algorithm is presented which determines a positive semi-definite state weighting matrix in the linear-quadratic optimal control design problem. The algorithm chooses the weighting matrix by placing closed-loop eigenvalues and eigenvectors near desired locations using optimal feedback gains. A simplified flight control design example is used to illustrate the algorithms capabilities.
Educational Tool for Optimal Controller Tuning Using Evolutionary Strategies
ERIC Educational Resources Information Center
Carmona Morales, D.; Jimenez-Hornero, J. E.; Vazquez, F.; Morilla, F.
2012-01-01
In this paper, an optimal tuning tool is presented for control structures based on multivariable proportional-integral-derivative (PID) control, using genetic algorithms as an alternative to traditional optimization algorithms. From an educational point of view, this tool provides students with the necessary means to consolidate their knowledge on…
Attitude Control Optimization for ROCSAT-2 Operation
NASA Astrophysics Data System (ADS)
Chern, Jeng-Shing; Wu, A.-M.
one revolution. The purpose of this paper is to present the attitude control design optimization such that the maximum solar energy is ingested while minimum maneuvering energy is dissipated. The strategy includes the maneuvering sequence design, the minimization of angular path, the sizing of three magnetic torquers, and the trade-off of the size, number and orientations arrangement of momentum wheels.
The application of quadratic optimal cooperative control synthesis to a CH-47 helicopter
NASA Technical Reports Server (NTRS)
Townsend, Barbara K.
1987-01-01
A control-system design method, quadratic optimal cooperative control synthesis (CCS), is applied to the design of a stability and control augmentation system (SCAS). The CCS design method is different from other design methods in that it does not require detailed a priori design criteria, but instead relies on an explicit optimal pilot-model to create desired performance. The design method, which was developed previously for fixed-wing aircraft, is simplified and modified for application to a Boeing CH-47 helicopter. Two SCAS designs are developed using the CCS design methodology. The resulting CCS designs are then compared with designs obtained using classical/frequency-domain methods and linear quadratic regulator (LQR) theory in a piloted fixed-base simulation. Results indicate that the CCS method, with slight modifications, can be used to produce controller designs which compare favorably with the frequency-domain approach.
Edge orientation for optimizing controllability of complex networks.
Xiao, Yan-Dong; Lao, Song-Yang; Hou, Lv-Lin; Bai, Liang
2014-10-01
Recently, as the controllability of complex networks attracts much attention, how to design and optimize the controllability of networks has become a common and urgent problem in the field of controlling complex networks. Previous work focused on the structural perturbation and neglected the role of edge direction to optimize the network controllability. In a recent work [Phys. Rev. Lett. 103, 228702 (2009)], the authors proposed a simple method to enhance the synchronizability of networks by assignment of link direction while keeping network topology unchanged. However, the controllability is fundamentally different from synchronization. In this work, we systematically propose the definition of assigning direction to optimize controllability, which is called the edge orientation for optimal controllability problem (EOOC). To solve the EOOC problem, we construct a switching network and transfer the EOOC problem to find the maximum independent set of the switching network. We prove that the principle of our optimization method meets the sense of unambiguity and optimum simultaneously. Furthermore, the relationship between the degree-degree correlations and EOOC are investigated by experiments. The results show that the disassortativity pattern could weaken the orientation for optimal controllability, while the assortativity pattern has no correlation with EOOC. All the experimental results of this work verify that the network structure determines the network controllability and the optimization effects. PMID:25375546
Edge orientation for optimizing controllability of complex networks
NASA Astrophysics Data System (ADS)
Xiao, Yan-Dong; Lao, Song-Yang; Hou, Lv-Lin; Bai, Liang
2014-10-01
Recently, as the controllability of complex networks attracts much attention, how to design and optimize the controllability of networks has become a common and urgent problem in the field of controlling complex networks. Previous work focused on the structural perturbation and neglected the role of edge direction to optimize the network controllability. In a recent work [Phys. Rev. Lett. 103, 228702 (2009), 10.1103/PhysRevLett.103.228702], the authors proposed a simple method to enhance the synchronizability of networks by assignment of link direction while keeping network topology unchanged. However, the controllability is fundamentally different from synchronization. In this work, we systematically propose the definition of assigning direction to optimize controllability, which is called the edge orientation for optimal controllability problem (EOOC). To solve the EOOC problem, we construct a switching network and transfer the EOOC problem to find the maximum independent set of the switching network. We prove that the principle of our optimization method meets the sense of unambiguity and optimum simultaneously. Furthermore, the relationship between the degree-degree correlations and EOOC are investigated by experiments. The results show that the disassortativity pattern could weaken the orientation for optimal controllability, while the assortativity pattern has no correlation with EOOC. All the experimental results of this work verify that the network structure determines the network controllability and the optimization effects.
New Applications of Variational Analysis to Optimization and Control
NASA Astrophysics Data System (ADS)
Mordukhovich, Boris S.
We discuss new applications of advanced tools of variational analysis and generalized differentiation to a number of important problems in optimization theory, equilibria, optimal control, and feedback control design. The presented results are largely based on the recent work by the author and his collaborators. Among the main topics considered and briefly surveyed in this paper are new calculus rules for generalized differentiation of nonsmooth and set-valued mappings; necessary and sufficient conditions for new notions of linear subextremality and suboptimality in constrained problems; optimality conditions for mathematical problems with equilibrium constraints; necessary optimality conditions for optimistic bilevel programming with smooth and nonsmooth data; existence theorems and optimality conditions for various notions of Pareto-type optimality in problems of multiobjective optimization with vector-valued and set-valued cost mappings; Lipschitzian stability and metric regularity aspects for constrained and variational systems.
Matching trajectory optimization and nonlinear tracking control for HALE
NASA Astrophysics Data System (ADS)
Lee, Sangjong; Jang, Jieun; Ryu, Hyeok; Lee, Kyun Ho
2014-11-01
This paper concerns optimal trajectory generation and nonlinear tracking control for stratospheric airship platform of VIA-200. To compensate for the mismatch between the point-mass model of optimal trajectory and the 6-DOF model of the nonlinear tracking problem, a new matching trajectory optimization approach is proposed. The proposed idea reduces the dissimilarity of both problems and reduces the uncertainties in the nonlinear equations of motion for stratospheric airship. In addition, its refined optimal trajectories yield better results under jet stream conditions during flight. The resultant optimal trajectories of VIA-200 are full three-dimensional ascent flight trajectories reflecting the realistic constraints of flight conditions and airship performance with and without a jet stream. Finally, 6-DOF nonlinear equations of motion are derived, including a moving wind field, and the vectorial backstepping approach is applied. The desirable tracking performance is demonstrated that application of the proposed matching optimization method enables the smooth linkage of trajectory optimization to tracking control problems.
D0 Silicon Upgrade: Cryolab Control Valve Modification Information for D0-EVMF-H
Rucincki, Russ; /Fermilab
1995-10-26
This engineering note documents some information regarding the solenoid magnet flow valve, EVMF. See also EN-437 'Control Dewar valve sizing' also for further information on this valve. This note documents the modification done to the valve to change it to a Cv = 0.32.
The report gives results of an environmental assessment field testing program on a tangential-coal-fired utility boiler. The aim of the program was to measure multimedia emissions changes as a result of applying combustion modification NOx control. Emissions of trace elements, or...
Federal Register 2010, 2011, 2012, 2013, 2014
2012-01-11
... Motiva, LLC of Dublin, Ohio (``Motiva''). 75 FR 68379 (Nov. 5, 2010). The complaint alleged violations of... COMMISSION Investigations: Terminations, Modifications and Rulings: Certain Video Game Systems and... United States after importation of certain video game systems and controllers by reason of...
CONTROL OF UTILITY BOILER AND GAS TURBINE POLLUTANT EMISSIONS BY COMBUSTION MODIFICATION--PHASE II
The report gives results of Phase II of a field study to assess the applicability of combustion modification (CM) techniques to control NOx and other pollutant emissions from utility boilers and gas turbines without causing deleterious side effects. Comprehensive, statistically d...
Optimization and Control of Electric Power Systems
Lesieutre, Bernard C.; Molzahn, Daniel K.
2014-10-17
The analysis and optimization needs for planning and operation of the electric power system are challenging due to the scale and the form of model representations. The connected network spans the continent and the mathematical models are inherently nonlinear. Traditionally, computational limits have necessitated the use of very simplified models for grid analysis, and this has resulted in either less secure operation, or less efficient operation, or both. The research conducted in this project advances techniques for power system optimization problems that will enhance reliable and efficient operation. The results of this work appear in numerous publications and address different application problems include optimal power flow (OPF), unit commitment, demand response, reliability margins, planning, transmission expansion, as well as general tools and algorithms.
Optimizing and controlling earthmoving operations using spatial technologies
NASA Astrophysics Data System (ADS)
Alshibani, Adel
This thesis presents a model designed for optimizing, tracking, and controlling earthmoving operations. The proposed model utilizes, Genetic Algorithm (GA), Linear Programming (LP), and spatial technologies including Global Positioning Systems (GPS) and Geographic Information Systems (GIS) to support the management functions of the developed model. The model assists engineers and contractors in selecting near optimum crew formations in planning phase and during construction, using GA and LP supported by the Pathfinder Algorithm developed in a GIS environment. GA is used in conjunction with a set of rules developed to accelerate the optimization process and to avoid generating and evaluating hypothetical and unrealistic crew formations. LP is used to determine quantities of earth to be moved from different borrow pits and to be placed at different landfill sites to meet project constraints and to minimize the cost of these earthmoving operations. On the one hand, GPS is used for onsite data collection and for tracking construction equipment in near real-time. On the other hand, GIS is employed to automate data acquisition and to analyze the collected spatial data. The model is also capable of reconfiguring crew formations dynamically during the construction phase while site operations are in progress. The optimization of the crew formation considers: (1) construction time, (2) construction direct cost, or (3) construction total cost. The model is also capable of generating crew formations to meet, as close as possible, specified time and/or cost constraints. In addition, the model supports tracking and reporting of project progress utilizing the earned-value concept and the project ratio method with modifications that allow for more accurate forecasting of project time and cost at set future dates and at completion. The model is capable of generating graphical and tabular reports. The developed model has been implemented in prototype software, using Object
Exact optimal solution for a class of dual control problems
NASA Astrophysics Data System (ADS)
Cao, Suping; Qian, Fucai; Wang, Xiaomei
2016-07-01
This paper considers a discrete-time stochastic optimal control problem for which only measurement equation is partially observed with unknown constant parameters taking value in a finite set of stochastic systems. Because of the fact that the cost-to-go function at each stage contains variance and the non-separability of the variance is so complicated that the dynamic programming cannot be successfully applied, the optimal solution has not been found. In this paper, a new approach to the optimal solution is proposed by embedding the original non-separable problem into a separable auxiliary problem. The theoretical condition on which the optimal solution of the original problem can be attained from a set of solutions of the auxiliary problem is established. In addition, the optimality of the interchanging algorithm is proved and the analytical solution of the optimal control is also obtained. The performance of this controller is illustrated with a simple example.
Technology Transfer Automated Retrieval System (TEKTRAN)
Alternan is a unique branched glucan with alternating a-(1 ' 6) and a-(1 ' 3) backbone linkages. We previously described the modification of alternan to a reduced molecular weight form using dextranase from Penicillium sp. The solution viscosity properties of this modified alternan resemble those ...
A pseudospectral method for optimal control of open quantum systems.
Li, Jr-Shin; Ruths, Justin; Stefanatos, Dionisis
2009-10-28
In this paper, we present a unified computational method based on pseudospectral approximations for the design of optimal pulse sequences in open quantum systems. The proposed method transforms the problem of optimal pulse design, which is formulated as a continuous-time optimal control problem, to a finite-dimensional constrained nonlinear programming problem. This resulting optimization problem can then be solved using existing numerical optimization suites. We apply the Legendre pseudospectral method to a series of optimal control problems on open quantum systems that arise in nuclear magnetic resonance spectroscopy in liquids. These problems have been well studied in previous literature and analytical optimal controls have been found. We find an excellent agreement between the maximum transfer efficiency produced by our computational method and the analytical expressions. Moreover, our method permits us to extend the analysis and address practical concerns, including smoothing discontinuous controls as well as deriving minimum-energy and time-optimal controls. The method is not restricted to the systems studied in this article and is applicable to optimal manipulation of both closed and open quantum systems. PMID:19894930
NASA Technical Reports Server (NTRS)
Harris, Charles D.; Brooks, Cuyler W., Jr.
1988-01-01
Modifications to the NASA Langley 8 Foot Transonic Pressure Tunnel in support of the Lamina Flow Control (LFC) Experiment included the installation of a honeymoon and five screens in the settling chamber upstream of the test section 41-long test section liner that extended from the upstream end of the test section contraction region, through the best section, and into the diffuser. The honeycomb and screens were installed as permanent additions to the facility, and the liner was a temporary addition to be removed at the conclusion of the LFC Experiment. These modifications are briefly described.
A weak Hamiltonian finite element method for optimal control problems
NASA Technical Reports Server (NTRS)
Hodges, Dewey H.; Bless, Robert R.
1989-01-01
A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.
Applying new optimization algorithms to more predictive control
Wright, S.J.
1996-03-01
The connections between optimization and control theory have been explored by many researchers and optimization algorithms have been applied with success to optimal control. The rapid pace of developments in model predictive control has given rise to a host of new problems to which optimization has yet to be applied. Concurrently, developments in optimization, and especially in interior-point methods, have produced a new set of algorithms that may be especially helpful in this context. In this paper, we reexamine the relatively simple problem of control of linear processes subject to quadratic objectives and general linear constraints. We show how new algorithms for quadratic programming can be applied efficiently to this problem. The approach extends to several more general problems in straightforward ways.
A weak Hamiltonian finite element method for optimal control problems
NASA Technical Reports Server (NTRS)
Hodges, Dewey H.; Bless, Robert R.
1990-01-01
A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.
Weak Hamiltonian finite element method for optimal control problems
NASA Technical Reports Server (NTRS)
Hodges, Dewey H.; Bless, Robert R.
1991-01-01
A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.
Control optimization, stabilization and computer algorithms for aircraft applications
NASA Technical Reports Server (NTRS)
1975-01-01
Research related to reliable aircraft design is summarized. Topics discussed include systems reliability optimization, failure detection algorithms, analysis of nonlinear filters, design of compensators incorporating time delays, digital compensator design, estimation for systems with echoes, low-order compensator design, descent-phase controller for 4-D navigation, infinite dimensional mathematical programming problems and optimal control problems with constraints, robust compensator design, numerical methods for the Lyapunov equations, and perturbation methods in linear filtering and control.
Polyhedral Interpolation for Optimal Reaction Control System Jet Selection
NASA Technical Reports Server (NTRS)
Gefert, Leon P.; Wright, Theodore
2014-01-01
An efficient algorithm is described for interpolating optimal values for spacecraft Reaction Control System jet firing duty cycles. The algorithm uses the symmetrical geometry of the optimal solution to reduce the number of calculations and data storage requirements to a level that enables implementation on the small real time flight control systems used in spacecraft. The process minimizes acceleration direction errors, maximizes control authority, and minimizes fuel consumption.
Robust control systems design by H-infinity optimization theory
NASA Technical Reports Server (NTRS)
Chang, B. C.; Li, X. P.; Banda, S. S.; Yeh, H. H.
1991-01-01
In this paper, step-by-step procedures of applying the H-infinity theory to robust control systems design are given. The objective of the paper is to eliminate the possible difficulties a control engineer may encounter in applying H-infinity control theory and to clear up some misconceptions about H-infinity theory like high-gain controller and numerical obstacles, etc. An efficient algorithm is used to compute the optimal H-infinity norm. The Glover and Doyle (1988) controller formulas are slightly modified and used to construct an optimal controller without any numerical difficulties.
Parkes, D. E.; Beardsley, R.; Edmonds, K. W.; Campion, R. P.; Gallagher, B. L.; Rushforth, A. W. E-mail: Andrew.Rushforth@nottingham.ac.uk; Bowe, S.; Isakov, I.; Warburton, P. A.; Cavill, S. A. E-mail: Andrew.Rushforth@nottingham.ac.uk
2014-08-11
Voltage controlled modification of the magnetocrystalline anisotropy in a hybrid piezoelectric/ferromagnet device has been studied using Photoemission Electron Microscopy with X-ray magnetic circular dichroism as the contrast mechanism. The experimental results demonstrate that the large magnetostriction of the epitaxial Fe{sub 81}Ga{sub 19} layer enables significant modification of the domain pattern in laterally confined disc structures. In addition, micromagnetic simulations demonstrate that the strain induced modification of the magnetic anisotropy allows for voltage tuneability of the natural resonance of both the confined spin wave modes and the vortex motion. These results demonstrate the possibility for using voltage induced strain in low-power voltage tuneable magnetic microwave oscillators.
Theory of Optimal Phase-Unlocked Pump-Dump Control
NASA Astrophysics Data System (ADS)
Yan, Yijing
1997-04-01
A novel theory of optimal control via a pair of phase-unlocked pump-dump fields is developed. We first derive a pair of coupled nonlinear control equations for mixed or dissipative quantum systems in the strong response regime. These equations should be solved iteratively, resulting in a locally optimal pair of fields that are however usually too complicated to be realizable. To facilitate this problem, we further develop a hierarchy of reduction and arrive at a variety of simplified control equation pairs. In the weak response regime, we obtain a pair of coupled semi-linear control equations in which the globally optimal pump field at any given pump field, or vice verse, can be evaluated in a non-iterative manor. However, it still requires an iterative solution to the semi-globally optimal pair of pump-dump fields. Further reduction is then devised to consider the pure state control system in the weak response regime. In this case, we derive a generalized eigenequation for the non-iterative solution to the complete set of optimal control field pairs, and further identify the globally optimal one unambiguously. The existence of certain symmetry relation between the pump and dump fields in any optimal pair is also analyzed in the stimulate Raman pumping control configuration and demonstrated numerically.
Control strategy optimization of HVAC plants
Facci, Andrea Luigi; Zanfardino, Antonella; Martini, Fabrizio; Pirozzi, Salvatore; Ubertini, Stefano
2015-03-10
In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting.
Optimal control of Atlantic population Canada geese
Hauser, C.E.; Runge, M.C.; Cooch, E.G.; Johnson, F.A.; Harvey, W.F., IV
2007-01-01
Management of Canada geese (Branta canadensis) can be a balance between providing sustained harvest opportunity while not allowing populations to become overabundant and cause damage. In this paper, we focus on the Atlantic population of Canada geese and use stochastic dynamic programming to determine the optimal harvest strategy over a range of plausible models for population dynamics. There is evidence to suggest that the population exhibits significant age structure, and it is possible to reconstruct age structure from surveys. Consequently the harvest strategy is a function of the age composition, as well as the abundance, of the population. The objective is to maximize harvest while maintaining the number of breeding adults in the population between specified upper and lower limits. In addition, the total harvest capacity is limited and there is uncertainty about the strength of density-dependence. We find that under a density-independent model, harvest is maximized by maintaining the breeding population at the highest acceptable abundance. However if harvest capacity is limited, then the optimal long-term breeding population size is lower than the highest acceptable level, to reduce the risk of the population growing to an unacceptably large size. Under the proposed density-dependent model, harvest is maximized by maintaining the breeding population at an intermediate level between the bounds on acceptable population size; limits to harvest capacity have little effect on the optimal long-term population size. It is clear that the strength of density-dependence and constraints on harvest significantly affect the optimal harvest strategy for this population. Model discrimination might be achieved in the long term, while continuing to meet management goals, by adopting an adaptive management strategy.
Improving Vortex Models via Optimal Control Theory
NASA Astrophysics Data System (ADS)
Hemati, Maziar; Eldredge, Jeff; Speyer, Jason
2012-11-01
Flapping wing kinematics, common in biological flight, can allow for agile flight maneuvers. On the other hand, we currently lack sufficiently accurate low-order models that enable such agility in man-made micro air vehicles. Low-order point vortex models have had reasonable success in predicting the qualitative behavior of the aerodynamic forces resulting from such maneuvers. However, these models tend to over-predict the force response when compared to experiments and high-fidelity simulations, in part because they neglect small excursions of separation from the wing's edges. In the present study, we formulate a constrained minimization problem which allows us to relax the usual edge regularity conditions in favor of empirical determination of vortex strengths. The optimal vortex strengths are determined by minimizing the error with respect to empirical force data, while the vortex positions are constrained to evolve according to the impulse matching model developed in previous work. We consider a flat plate undergoing various canonical maneuvers. The optimized model leads to force predictions remarkably close to the empirical data. Additionally, we compare the optimized and original models in an effort to distill appropriate edge conditions for unsteady maneuvers.
Optimal control of plates using incompatible strains
NASA Astrophysics Data System (ADS)
Jones, G. W.; Mahadevan, L.
2015-09-01
A flat plate will bend into a curved shell if it experiences an inhomogeneous growth field or if constrained appropriately at a boundary. While the forward problem associated with this process is well studied, the inverse problem of designing the boundary conditions or growth fields to achieve a particular shape is much less understood. We use ideas from variational optimization theory to formulate a well posed version of this inverse problem to determine the optimal growth field or boundary condition that will give rise to an arbitrary target shape, optimizing for both closeness to the target shape and for smoothness of the growth field. We solve the resulting system of PDE numerically using finite element methods with examples for both the fully non-symmetric case as well as for simplified one-dimensional and axisymmetric geometries. We also show that the system can also be solved semi-analytically by positing an ansatz for the deformation and growth fields in a circular disk with given thickness profile, leading to paraboloidal, cylindrical and saddle-shaped target shapes, and show how a soft mode can arise from a non-axisymmetric deformation of a structure with axisymmetric material properties.
Optimization of Codon Translation Rates via tRNA Modifications Maintains Proteome Integrity
Nedialkova, Danny D.; Leidel, Sebastian A.
2015-01-01
Summary Proteins begin to fold as they emerge from translating ribosomes. The kinetics of ribosome transit along a given mRNA can influence nascent chain folding, but the extent to which individual codon translation rates impact proteome integrity remains unknown. Here, we show that slower decoding of discrete codons elicits widespread protein aggregation in vivo. Using ribosome profiling, we find that loss of anticodon wobble uridine (U34) modifications in a subset of tRNAs leads to ribosome pausing at their cognate codons in S. cerevisiae and C. elegans. Cells lacking U34 modifications exhibit gene expression hallmarks of proteotoxic stress, accumulate aggregates of endogenous proteins, and are severely compromised in clearing stress-induced protein aggregates. Overexpression of hypomodified tRNAs alleviates ribosome pausing, concomitantly restoring protein homeostasis. Our findings demonstrate that modified U34 is an evolutionarily conserved accelerator of decoding and reveal an unanticipated role for tRNA modifications in maintaining proteome integrity. PMID:26052047
Studies on controllability of directed networks with extremal optimization
NASA Astrophysics Data System (ADS)
Ding, Jin; Lu, Yong-Zai; Chu, Jian
2013-12-01
Almost all natural, social and man-made-engineered systems can be represented by a complex network to describe their dynamic behaviors. To make a real-world complex network controllable with its desired topology, the study on network controllability has been one of the most critical and attractive subjects for both network and control communities. In this paper, based on a given directed-weighted network with both state and control nodes, a novel optimization tool with extremal dynamics to generate an optimal network topology with minimum control nodes and complete controllability under Kalman’s rank condition has been developed. The experimental results on a number of popular benchmark networks show the proposed tool is effective to identify the minimum control nodes which are sufficient to guide the whole network’s dynamics and provide the evolution of network topology during the optimization process. We also find the conclusion: “the sparse networks need more control nodes than the dense, and the homogeneous networks need fewer control nodes compared to the heterogeneous” (Liu et al., 2011 [18]), is also applicable to network complete controllability. These findings help us to understand the network dynamics and make a real-world network under the desired control. Moreover, compared with the relevant research results on structural controllability with minimum driver nodes, the proposed solution methodology may also be applied to other constrained network optimization problems beyond complete controllability with minimum control nodes.
Time-optimal maneuvering control of a rigid spacecraft
NASA Astrophysics Data System (ADS)
Lai, Li-Chun; Yang, Chi-Ching; Wu, Chia-Ju
2007-05-01
The time-optimal rest-to-rest maneuvering control problem of a rigid spacecraft is studied in this paper. By utilizing an iterative procedure, this problem is formulated and solved as a constrained nonlinear programming (NLP) one. In this novel method, the count of control steps is fixed initially and the sampling period is treated as a variable in the optimization process. The optimization object is to minimize the sampling period below a specific minimum value, which is set in advance considering the accuracy of discretization. To generate initial feasible solutions of the NLP problem, a genetic-algorithm-based is also proposed such that the optimization process can be started from many different points to find the globally optimal solution. With the proposed method, one can find a time-optimal rest-to-rest maneuver of the rigid spacecraft between two attitudes. To show the feasibility of the proposed method, simulation results are included for illustration.
Time-optimal control of the magnetically levitated photolithography platen
Redmond, J.; Tucker, S.
1995-01-01
This report summarizes two approaches to time-optimal control of a nonlinear magnetically levitated platen. The system of interest is a candidate technology for next-generation photolithography machines used in the manufacture of integrated circuits. The dynamics and the variable peak control force of the electro-magnetic actuators preclude the direct application of classical time-optimal control methodologies for determining optimal rest-to-rest maneuver strategies. Therefore, this study explores alternate approaches using a previously developed computer simulation. In the first approach, conservative estimates of the available control forces are used to generate suboptimal switching curves. In the second approach, exact solutions are determined iteratively and used as a training set for an artificial neural network. The trained network provides optimal actuator switching times that incorporate the full nonlinearities of the magnetic levitation actuators. Sample problems illustrate the effectiveness of these techniques as compared to traditional proportional-derivative control.
Time dependent optimal switching controls in online selling models
Bradonjic, Milan; Cohen, Albert
2010-01-01
We present a method to incorporate dishonesty in online selling via a stochastic optimal control problem. In our framework, the seller wishes to maximize her average wealth level W at a fixed time T of her choosing. The corresponding Hamilton-Jacobi-Bellmann (HJB) equation is analyzed for a basic case. For more general models, the admissible control set is restricted to a jump process that switches between extreme values. We propose a new approach, where the optimal control problem is reduced to a multivariable optimization problem.
Optimal control of a harmonic oscillator: Economic interpretations
NASA Astrophysics Data System (ADS)
Janová, Jitka; Hampel, David
2013-10-01
Optimal control is a popular technique for modelling and solving the dynamic decision problems in economics. A standard interpretation of the criteria function and Lagrange multipliers in the profit maximization problem is well known. On a particular example, we aim to a deeper understanding of the possible economic interpretations of further mathematical and solution features of the optimal control problem: we focus on the solution of the optimal control problem for harmonic oscillator serving as a model for Phillips business cycle. We discuss the economic interpretations of arising mathematical objects with respect to well known reasoning for these in other problems.
A duality framework for stochastic optimal control of complex systems
Malikopoulos, Andreas A.
2016-01-01
In this study, we address the problem of minimizing the long-run expected average cost of a complex system consisting of interactive subsystems. We formulate a multiobjective optimization problem of the one-stage expected costs of the subsystems and provide a duality framework to prove that the control policy yielding the Pareto optimal solution minimizes the average cost criterion of the system. We provide the conditions of existence and a geometric interpretation of the solution. For practical situations having constraints consistent with those studied here, our results imply that the Pareto control policy may be of value when we seek to derive online the optimal control policy in complex systems.
Optimal active control for Burgers equations
NASA Technical Reports Server (NTRS)
Ikeda, Yutaka
1994-01-01
A method for active fluid flow control based on control theory is discussed. Dynamic programming and fixed point successive approximations are used to accommodate the nonlinear control problem. The long-term goal of this project is to establish an effective method applicable to complex flows such as turbulence and jets. However, in this report, the method is applied to stochastic Burgers equation as an intermediate step towards this goal. Numerical results are compared with those obtained by gradient search methods.
Deterministic methods for multi-control fuel loading optimization
NASA Astrophysics Data System (ADS)
Rahman, Fariz B. Abdul
We have developed a multi-control fuel loading optimization code for pressurized water reactors based on deterministic methods. The objective is to flatten the fuel burnup profile, which maximizes overall energy production. The optimal control problem is formulated using the method of Lagrange multipliers and the direct adjoining approach for treatment of the inequality power peaking constraint. The optimality conditions are derived for a multi-dimensional multi-group optimal control problem via calculus of variations. Due to the Hamiltonian having a linear control, our optimal control problem is solved using the gradient method to minimize the Hamiltonian and a Newton step formulation to obtain the optimal control. We are able to satisfy the power peaking constraint during depletion with the control at beginning of cycle (BOC) by building the proper burnup path forward in time and utilizing the adjoint burnup to propagate the information back to the BOC. Our test results show that we are able to achieve our objective and satisfy the power peaking constraint during depletion using either the fissile enrichment or burnable poison as the control. Our fuel loading designs show an increase of 7.8 equivalent full power days (EFPDs) in cycle length compared with 517.4 EFPDs for the AP600 first cycle.
Optimal actuator location of minimum norm controls for heat equation with general controlled domain
NASA Astrophysics Data System (ADS)
Guo, Bao-Zhu; Xu, Yashan; Yang, Dong-Hui
2016-09-01
In this paper, we study optimal actuator location of the minimum norm controls for a multi-dimensional heat equation with control defined in the space L2 (Ω × (0 , T)). The actuator domain is time-varying in the sense that it is only required to have a prescribed Lebesgue measure for any moment. We select an optimal actuator location so that the optimal control takes its minimal norm over all possible actuator domains. We build a framework of finding the Nash equilibrium so that we can develop a sufficient and necessary condition to characterize the optimal relaxed solutions for both actuator location and corresponding optimal control of the open-loop system. The existence and uniqueness of the optimal classical solutions are therefore concluded. As a result, we synthesize both optimal actuator location and corresponding optimal control into a time-varying feedbacks.
Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control
NASA Technical Reports Server (NTRS)
Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.
2015-01-01
The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.
A Numerical Optimization Approach for Tuning Fuzzy Logic Controllers
NASA Technical Reports Server (NTRS)
Woodard, Stanley E.; Garg, Devendra P.
1998-01-01
This paper develops a method to tune fuzzy controllers using numerical optimization. The main attribute of this approach is that it allows fuzzy logic controllers to be tuned to achieve global performance requirements. Furthermore, this approach allows design constraints to be implemented during the tuning process. The method tunes the controller by parameterizing the membership functions for error, change-in-error and control output. The resulting parameters form a design vector which is iteratively changed to minimize an objective function. The minimal objective function results in an optimal performance of the system. A spacecraft mounted science instrument line-of-sight pointing control is used to demonstrate results.
Optimal Control of the Parametric Oscillator
ERIC Educational Resources Information Center
Andresen, B.; Hoffmann, K. H.; Nulton, J.; Tsirlin, A.; Salamon, P.
2011-01-01
We present a solution to the minimum time control problem for a classical harmonic oscillator to reach a target energy E[subscript T] from a given initial state (q[subscript i], p[subscript i]) by controlling its frequency [omega], [omega][subscript min] less than or equal to [omega] less than or equal to [omega][subscript max]. A brief synopsis…
Towards fault-tolerant optimal control
NASA Technical Reports Server (NTRS)
Chizeck, H. J.; Willsky, A. S.
1979-01-01
The paper considers the design of fault-tolerant controllers that may endow systems with dynamic reliability. Results for jump linear quadratic Gaussian control problems are extended to include random jump costs, trajectory discontinuities, and a simple case of non-Markovian mode transitions.
Optimized synthesis of concurrently checked controllers
Leveugle, R.; Saucier, G. )
1990-04-01
Dedicated controllers (or FSM's) with concurrent checking capabilities are of prime importance in highly dependable applications. This paper presents a new method for introducing on-line test facilities in a controller with a very low overhead. This on-line test consists in detecting illegal paths in the control flow graph. These illegal paths may be due either to permanent faults or to transient errors. The state code flow is compacted through polynomial division. An implicit justifying signature method is applied at the state code level and ensures identical signatures before each join node of the control flow graph. The signatures are then independent of the path followed previously in the graph and the comparison to reference data is greatly facilitated. This property is obtained by a clever state assignment, nearly without area overhead. The controllers can then be checked by signature analysis, either by a built-in monitor or by an external checker.
Optimize control of natural gas plants
Treiber, S.; Walker, J.; Tremblay, M. de ); Delgadillo, R.L.; Velasquez, R.N.; Valarde, M.J.G. )
1994-04-01
Multivariable constraint control (MCS) has a very beneficial and profitable impact on the operation of natural gas plants. The applications described operate completely within a distributed control system (DCS) or programmable logic controllers (PLCs). That makes MCS accessible to almost all gas plant operators. The technology's relative ease of use, low maintenance effort and software sensor,'' make it possible to operate these control applications without increasing technical support staff. MCS improves not only profitability but also regulatory compliance of gas plants. It has been applied to fractionation units, cryogenic units, amine treaters, sulfur recovery units and utilities. The application typically pay for the cost of software and engineering in less than one month. If a DCS is installed within such a project the advanced control applications can generate a payout in less than one year. In the case here (an application on the deethanizers of a 500 MMscfd gas plant) product revenue increased by over $2 million/yr.
OPTIMIZATION OF INTEGRATED URBAN WET-WEATHER CONTROL STRATEGIES
An optimization method for urban wet weather control (WWC) strategies is presented. The developed optimization model can be used to determine the most cost-effective strategies for the combination of centralized storage-release systems and distributed on-site WWC alternatives. T...
Optimization of RMP Coils for ELM Control
NASA Astrophysics Data System (ADS)
Dutta, Someswar; Evans, T. E.; Orlov, D. M.
2015-11-01
Advanced DIII-D RMP coils with improved capabilities are studied using a vacuum island overlap width (VIOW) criterion. Changes in characteristics of the RMP field produced by different geometrical parameters using both ex-vessel (C- and O-) and in-vessel (I- and CP-) coils are discussed. By reducing the poloidal span of each coil, the spacing between them and varying the geometric angle between the coils and the plasma, the resonant field can be adjusted to optimize the edge VIOW criterion while minimizing core resonances. Three separate phase scans using a combination of the as built I-coils and proposed CP-coils are compared for three different equilibria. Two of these equilibria have different edge safety factors and the third one has a different gap between plasma and wall than the standard equilibrium scenario of DIII D. The scan results show that the VIOW correlation criterion is well satisfied in all three cases, resulting in a new way to optimize the RMP coils for the future reactors in order to achieve the ELM suppression criterion over a significantly wider range of fusion plasma operating scenarios. Work supported by the U.S. DOE under DE-FG02-05ER54809 and DE-FC02-04ER54698.
Shape Optimization for Trailing Edge Noise Control
NASA Astrophysics Data System (ADS)
Marsden, Alison; Wang, Meng; Mohammadi, Bijan; Moin, Parviz
2001-11-01
Noise generated by turbulent boundary layers near the trailing edge of lifting surfaces continues to pose a challenge for many applications. In this study, we explore noise reduction strategies through shape optimization. A gradient based shape design method is formulated and implemented for use with large eddy simulation of the flow over an airfoil. The cost function gradient is calculated using the method of incomplete sensitivities (Mohammadi and Pironneau 2001 ph Applied shape Optimization for Fluids, Oxford Univ. Press). This method has the advantage that effects of geometry changes on the flow field can be neglected when computing the gradient of the cost function, making it far more cost effective than solving the full adjoint problem. Validation studies are presented for a model problem of the unsteady laminar flow over an acoustically compact airfoil. A section of the surface is allowed to deform and the cost function is derived based on aeroacoustic theroy. Rapid convergence of the trailing-edge shape and significant reduction of the noise due to vortex shedding and wake instability have been achieved. The addition of constraints and issues of extension to fully turbulent flows past an acoustically noncompact airfoil are also discussed.
Dual structural-control optimization of large space structures
NASA Technical Reports Server (NTRS)
Messac, A.; Turner, J.
1984-01-01
A new approach is proposed for solving dual structural-control optimization problems for high-order flexible space structures where reduced-order structural models are employed. For a given initial structural dessign, a quadratic control cost is minimized subject to a constant-mass constraint. The sensitivity of the optimal control cost with respect to the stuctural design variables is then determined and used to obtain successive structural redesigns using a contrained gradient optimization algorithm. This process is repeated until the constrained control cost sensitivity becomes negligible. A numerical example is presented which demonstrates that this new approach effectively addresses the problem of dual optimization for potentially very high-order structures.
Optimal feedback control of turbulent channel flow
NASA Technical Reports Server (NTRS)
Bewley, Thomas; Choi, Haecheon; Temam, Roger; Moin, Parviz
1993-01-01
Feedback control equations were developed and tested for computing wall normal control velocities to control turbulent flow in a channel with the objective of reducing drag. The technique used is the minimization of a 'cost functional' which is constructed to represent some balance of the drag integrated over the wall and the net control effort. A distribution of wall velocities is found which minimizes this cost functional some time shortly in the future based on current observations of the flow near the wall. Preliminary direct numerical simulations of the scheme applied to turbulent channel flow indicates it provides approximately 17 percent drag reduction. The mechanism apparent when the scheme is applied to a simplified flow situation is also discussed.
Modification of the logic and control system for the 80-ounce injection molding machine
Domer, G.A.
1990-01-01
The modification of the hydraulic logic and control system for the 80-ounce injection molding machine in the Molding and Machining, Plastics, department was required to allow production of near net size thick-walled parts and machining stock from high-shrinkage materials while retaining the original logic for standard product. The control system that was developed allows the new capability of open clamp injection. This capability will replace the present method of purchasing machining stock from an outside source. The control system was implemented with a Giddings Lewis Programmable Industrial Computer 409 (G L PiC 409). Hydraulic modifications included adding Vickers servo valves, an Inductosyn position transducer, and MOOG pressure transducers to perform force and position control. The control system provides two capabilities, NORMAL and SERVO. The NORMAL mode is defined as operating the machine according to original design specifications. The SERVO mode is defined as operating the machine according to a recipe in open loop position control then in closed loop force control. The G L PiC 409 controls the tasks of both modes. A selector switch determines the mode of operation (NORMAL or SERVO). The NORMAL mode uses the original hydraulic circuits, and the SERVO mode diverts fluid into the modified hydraulic circuits. 11 figs.
Cost-effectiveness analysis of optimal control measures for tuberculosis.
Rodrigues, Paula; Silva, Cristiana J; Torres, Delfim F M
2014-10-01
We propose and analyze an optimal control problem where the control system is a mathematical model for tuberculosis that considers reinfection. The control functions represent the fraction of early latent and persistent latent individuals that are treated. Our aim was to study how these control measures should be implemented, for a certain time period, in order to reduce the number of active infected individuals, while minimizing the interventions implementation costs. The optimal intervention is compared along different epidemiological scenarios, by varying the transmission coefficient. The impact of variation of the risk of reinfection, as a result of acquired immunity to a previous infection for treated individuals on the optimal controls and associated solutions, is analyzed. A cost-effectiveness analysis is done, to compare the application of each one of the control measures, separately or in combination. PMID:25245395
Fully efficient time-parallelized quantum optimal control algorithm
NASA Astrophysics Data System (ADS)
Riahi, M. K.; Salomon, J.; Glaser, S. J.; Sugny, D.
2016-04-01
We present a time-parallelization method that enables one to accelerate the computation of quantum optimal control algorithms. We show that this approach is approximately fully efficient when based on a gradient method as optimization solver: the computational time is approximately divided by the number of available processors. The control of spin systems, molecular orientation, and Bose-Einstein condensates are used as illustrative examples to highlight the wide range of applications of this numerical scheme.
Using Chemicals to Optimize Conformance Control in Fractured Reservoirs
Seright, Randall S.; Liang, Jenn-Tai; Schrader, Richard; Hagstrom II, John; Wang, Ying; Kumar, Ananad; Wavrik, Kathryn
2001-10-29
This report describes work performed during the third and final year of the project, Using Chemicals to Optimize Conformance Control in Fractured Reservoirs. This research project had three objectives. The first objective was to develop a capability to predict and optimize the ability of gels to reduce permeability to water more than that to oil or gas. The second objective was to develop procedures for optimizing blocking agent placement in wells where hydraulic fractures cause channeling problems. The third objective was to develop procedures to optimize blocking agent placement in naturally fractured reservoirs.
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. Both solutions achieved the same cumulative fuel consumption demonstrating that the online Pareto control policy is an optimal control policy.
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
Information fusion based optimal control for large civil aircraft system.
Zhen, Ziyang; Jiang, Ju; Wang, Xinhua; Gao, Chen
2015-03-01
Wind disturbance has a great influence on landing security of Large Civil Aircraft. Through simulation research and engineering experience, it can be found that PID control is not good enough to solve the problem of restraining the wind disturbance. This paper focuses on anti-wind attitude control for Large Civil Aircraft in landing phase. In order to improve the riding comfort and the flight security, an information fusion based optimal control strategy is presented to restrain the wind in landing phase for maintaining attitudes and airspeed. Data of Boeing707 is used to establish a nonlinear mode with total variables of Large Civil Aircraft, and then two linear models are obtained which are divided into longitudinal and lateral equations. Based on engineering experience, the longitudinal channel adopts PID control and C inner control to keep longitudinal attitude constant, and applies autothrottle system for keeping airspeed constant, while an information fusion based optimal regulator in the lateral control channel is designed to achieve lateral attitude holding. According to information fusion estimation, by fusing hard constraint information of system dynamic equations and the soft constraint information of performance index function, optimal estimation of the control sequence is derived. Based on this, an information fusion state regulator is deduced for discrete time linear system with disturbance. The simulation results of nonlinear model of aircraft indicate that the information fusion optimal control is better than traditional PID control, LQR control and LQR control with integral action, in anti-wind disturbance performance in the landing phase. PMID:25440950
Shape Optimization for Aerodynamic Noise Control
NASA Astrophysics Data System (ADS)
Marsden, Alison; Wang, Meng; Mohammadi, Bijan; Moin, Parviz
2002-11-01
The objective of this work is to develop optimal shape design methods for reducing airfoil trailing-edge noise. Accurate evaluation of the cost function gradient via classical methods is expensive in unsteady turbulent flow simulations. We have evaluated the method of incomplete sensitivities (Mohammadi and Pironneau), which is inexpensive, and has been successful in previous applications. Gradients are approximated by neglecting changes in the flow field relative to geometrical contributions at each time step. Initial tests applied to a model problem seemed promising, however, in some cases the method was found to break down. A systematic evaluation of the incomplete sensitivities method as applied to the present problem has been carried out by comparison with the full gradient. The contribution to the gradient from changes in the flow field were found to be important. The underlying physical reasoning will be discussed and alternative methods including adjoint approaches and evolutionary algorithms will be explored.
Discrete Mechanics and Optimal Control for Space Trajectory Design
NASA Astrophysics Data System (ADS)
Moore, Ashley
Space trajectory design is often achieved through a combination of dynamical systems theory and optimal control. The union of trajectory design techniques utilizing invariant manifolds of the planar circular restricted three-body problem and the optimal control scheme Discrete Mechanics and Optimal Control (DMOC) facilitates the design of low-energy trajectories in the N-body problem. In particular, DMOC is used to optimize a trajectory from the Earth to the Moon in the 4-body problem, removing the mid-course change in velocity, Delta V, usually necessary for such a trajectory while still exploiting the structure from the invariant manifolds. This thesis also focuses on how to adapt DMOC, a method devised with a constant step size, for the highly nonlinear dynamics involved in trajectory design. Mesh refinement techniques that aim to reduce discretization errors in the solution and energy evolution and their effect on DMOC optimization are explored and compared with trajectories created using time adaptive variational integrators. Furthermore, a time adaptive form of DMOC is developed that allows for a variable step size that is updated throughout the optimization process. Time adapted DMOC is based on a discretization of Hamilton's principle applied to the time adapted Lagrangian of the optimal control problem. Variations of the discrete action of the optimal control Lagrangian lead to discrete Euler-Lagrange equations that can be enforced as constraints for a boundary value problem. This new form of DMOC leads to the accurate and efficient solution of optimal control problems with highly nonlinear dynamics. Time adapted DMOC is tested on several space trajectory problems including the elliptical orbit transfer in the 2-body problem and the reconfiguration of a cubesat.
Optimization of a fluidic temperature control device
NASA Technical Reports Server (NTRS)
Zabsky, J. M.; Rask, D. R.; Starr, J. B.
1970-01-01
Refinements are described to an existing fluidic temperature control system developed under a prior study which modulated temperature at the inlet to the liquid-cooled garment by using existing liquid supply and return lines to transmit signals to a fluidic controller located in the spacecraft. This earlier system produced a limited range of garment inlet temperatures, requiring some bypassing of flow around the suit to make the astronaut comfortable at rest conditions. Refinements were based on a flow visualization study of the key element in the fluidic controller: the fluidic mixing valve. The valve's mixing-ratio range was achieved by making five key changes: (1) geometrical changes to the valve; (2) attenuation of noise generated in proportional amplifier cascades; (3) elimination of vortices at the exit of the fluidic mixing valve; (4) reduction of internal heat transfer; and (5) flow balancing through venting. As a result, the refined system is capable of modulating garment inlet temperature from 45 F to 70 F with a single manual control valve in series with the garment. This control valve signals without changing or bypassing flow through the garment.
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.
NASA Astrophysics Data System (ADS)
Tsuchiya, Takeshi; Ishii, Hirokazu; Uchida, Junichi; Gomi, Hiromi; Matayoshi, Naoki; Okuno, Yoshinori
This study aims to obtain the optimal flights of a helicopter that reduce ground noise during landing approach with an optimization technique, and to conduct flight tests for confirming the effectiveness of the optimal solutions. Past experiments of Japan Aerospace Exploration Agency (JAXA) show that the noise of a helicopter varies significantly according to its flight conditions, especially depending on the flight path angle. We therefore build a simple noise model for a helicopter, in which the level of the noise generated from a point sound source is a function only of the flight path angle. Using equations of motion for flight in a vertical plane, we define optimal control problems for minimizing noise levels measured at points on the ground surface, and obtain optimal controls for specified initial altitudes, flight constraints, and wind conditions. The obtained optimal flights avoid the flight path angle which generates large noise and decrease the flight time, which are different from conventional flight. Finally, we verify the validity of the optimal flight patterns through flight experiments. The actual flights following the optimal paths resulted in noise reduction, which shows the effectiveness of the optimization.
First line nurse managers: optimizing the span of control.
Alidina, S; Funke-Furber, J
1988-05-01
Span of control, the number of people reporting to a manager, is an important management concept. It determines the structure of an organization and has financial, human resource, and quality of care implications. In nursing, the first line manager fills one of the most critical roles in the administration of nursing services. For this manager to perform her responsibilities effectively, an optimal span of control is necessary. Span of control is influenced by a number of factors. By understanding these factors, we can influence them to optimize the span of control of the nurse manager. PMID:3367230
Backward bifurcation and optimal control of Plasmodium Knowlesi malaria
NASA Astrophysics Data System (ADS)
Abdullahi, Mohammed Baba; Hasan, Yahya Abu; Abdullah, Farah Aini
2014-07-01
A deterministic model for the transmission dynamics of Plasmodium Knowlesi malaria with direct transmission is developed. The model is analyzed using dynamical system techniques and it shows that the backward bifurcation occurs for some range of parameters. The model is extended to assess the impact of time dependent preventive (biological and chemical control) against the mosquitoes and vaccination for susceptible humans, while treatment for infected humans. The existence of optimal control is established analytically by the use of optimal control theory. Numerical simulations of the problem, suggest that applying the four control measure can effectively reduce if not eliminate the spread of Plasmodium Knowlesi in a community.
Mechanisms of Molecular Response in the Optimal Control of Photoisomerization
Dietzek, Benjamin; Brueggemann, Ben; Pascher, Torbjoern; Yartsev, Arkady
2006-12-22
We report on adaptive feedback control of photoinduced barrierless isomerization of 1,1'-diethyl-2,2'-cyanine in solution. We compare the effect of different fitness parameters and show that optimal control of the absolute yield of isomerization (photoisomer concentration versus excitation photons) can be achieved, while the relative isomerization yield (photoisomer concentration versus number of relaxed excited-state molecules) is unaffected by adaptive feedback control. The temporal structure of the optimized excitation pulses allows one to draw clear mechanistic conclusions showing the critical importance of coherent nuclear motion for the control of isomerization.
Genetic Algorithm Optimizes Q-LAW Control Parameters
NASA Technical Reports Server (NTRS)
Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard
2008-01-01
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
Hydro- abrasive jet machining modeling for computer control and optimization
NASA Astrophysics Data System (ADS)
Groppetti, R.; Jovane, F.
1993-06-01
Use of hydro-abrasive jet machining (HAJM) for machining a wide variety of materials—metals, poly-mers, ceramics, fiber-reinforced composites, metal-matrix composites, and bonded or hybridized mate-rials—primarily for two- and three-dimensional cutting and also for drilling, turning, milling, and deburring, has been reported. However, the potential of this innovative process has not been explored fully. This article discusses process control, integration, and optimization of HAJM to establish a plat-form for the implementation of real-time adaptive control constraint (ACC), adaptive control optimiza-tion (ACO), and CAD/CAM integration. It presents the approach followed and the main results obtained during the development, implementation, automation, and integration of a HAJM cell and its computer-ized controller. After a critical analysis of the process variables and models reported in the literature to identify process variables and to define a process model suitable for HAJM real-time control and optimi-zation, to correlate process variables and parameters with machining results, and to avoid expensive and time-consuming experiments for determination of the optimal machining conditions, a process predic-tion and optimization model was identified and implemented. Then, the configuration of the HAJM cell, architecture, and multiprogramming operation of the controller in terms of monitoring, control, process result prediction, and process condition optimization were analyzed. This prediction and optimization model for selection of optimal machining conditions using multi-objective programming was analyzed. Based on the definition of an economy function and a productivity function, with suitable constraints relevant to required machining quality, required kerfing depth, and available resources, the model was applied to test cases based on experimental results.
Combining Optimal Control Theory and Molecular Dynamics for Protein Folding
Arkun, Yaman; Gur, Mert
2012-01-01
A new method to develop low-energy folding routes for proteins is presented. The novel aspect of the proposed approach is the synergistic use of optimal control theory with Molecular Dynamics (MD). In the first step of the method, optimal control theory is employed to compute the force field and the optimal folding trajectory for the atoms of a Coarse-Grained (CG) protein model. The solution of this CG optimization provides an harmonic approximation of the true potential energy surface around the native state. In the next step CG optimization guides the MD simulation by specifying the optimal target positions for the atoms. In turn, MD simulation provides an all-atom conformation whose positions match closely the reference target positions determined by CG optimization. This is accomplished by Targeted Molecular Dynamics (TMD) which uses a bias potential or harmonic restraint in addition to the usual MD potential. Folding is a dynamical process and as such residues make different contacts during the course of folding. Therefore CG optimization has to be reinitialized and repeated over time to accomodate these important changes. At each sampled folding time, the active contacts among the residues are recalculated based on the all-atom conformation obtained from MD. Using the new set of contacts, the CG potential is updated and the CG optimal trajectory for the atoms is recomputed. This is followed by MD. Implementation of this repetitive CG optimization - MD simulation cycle generates the folding trajectory. Simulations on a model protein Villin demonstrate the utility of the method. Since the method is founded on the general tools of optimal control theory and MD without any restrictions, it is widely applicable to other systems. It can be easily implemented with available MD software packages. PMID:22238629
Reproducibility, Controllability, and Optimization of Lenr Experiments
NASA Astrophysics Data System (ADS)
Nagel, David J.
2006-02-01
Low-energy nuclear reaction (LENR) measurements are significantly and increasingly reproducible. Practical control of the production of energy or materials by LENR has yet to be demonstrated. Minimization of costly inputs and maximization of desired outputs of LENR remain for future developments.
Linear stochastic optimal control and estimation
NASA Technical Reports Server (NTRS)
Geyser, L. C.; Lehtinen, F. K. B.
1976-01-01
Digital program has been written to solve the LSOCE problem by using a time-domain formulation. LSOCE problem is defined as that of designing controls for linear time-invariant system which is disturbed by white noise in such a way as to minimize quadratic performance index.
Reengineering for optimized control of DC networks
NASA Astrophysics Data System (ADS)
Vintea, Adela; Schiopu, Paul
2015-02-01
The management of the Independent Power Grids is the global body/structure with flexible technological support for Command-Control-Communications and Informatized Management having the responsibility for providing the conditions and information (the informational flux of decision) for the decision-maker aiming at predictable and harmonic administration of the situations (crises) and for generating the harmonic situations (results).
OPTIMAL COST CONTROL STRATEGIES FOR ATTACHED ALGAE
This paper presents a cost-benefit analysis for alternative programs intended for the control of the nuisance growth of an attached alga (Cladophora). Such analyses require that changes in water quality be quantitatively related to the cost of implementation for specific manageme...
Microstructurally Controlled Composites with Optimal Elastodynamic Properties
NASA Astrophysics Data System (ADS)
Sadeghi, Hossein
Periodic composites (PCs) are artificial materials with specially designed microstructure to manage stress waves. The objective of this dissertation is to study various techniques for microstructural design of PCs for a desired elastodynamic response. A mixed variational formulation is studied for band structure calculation of PCs. Dynamic homogenization is studied for calculation of the frequency dependent effective properties of PCs. Optimization techniques are used together with mixed variational formulation and dynamic homogenization to make a computational platform for microstructural design of PCs. Several PCs are designed and fabricated, and various tests are performed for experimental verification. First, band-gap in one- and two-dimensional PCs is investigated experimentally. Mixed variational formulation is used to design samples with band-gaps at frequencies convenient to conduct experiment. Samples are fabricated and their transmission coefficient is measured. Experimental data are compared with theoretical results for evaluation of the band structure. Using constituent materials with temperature dependent material properties, it is also shown that band structure of PCs can be tuned by changing the ambient temperature. Furthermore, dynamic homogenization is used to design a one-dimensional PC for acoustic impedance matching. As a result, the reflection of stress waves at the interface of two impedance matched media becomes zero. Samples are fabricated and ultrasound tests are performed to measure the reflection coefficient for experimental verification. In addition, a one-dimensional PC with metamaterial response is designed to achieve a composite with both high stiffness-to-density ratio and high attenuation at low frequency regime. Samples are fabricated and the attenuation coefficient is measured for experimental verification. Moreover, optimal design of PCs for shock wave mitigation is investigated. A genetic algorithm is used to design the
Integrated structure/control law design by multilevel optimization
NASA Technical Reports Server (NTRS)
Gilbert, Michael G.; Schmidt, David K.
1989-01-01
A new approach to integrated structure/control law design based on multilevel optimization is presented. This new approach is applicable to aircraft and spacecraft and allows for the independent design of the structure and control law. Integration of the designs is achieved through use of an upper level coordination problem formulation within the multilevel optimization framework. The method requires the use of structure and control law design sensitivity information. A general multilevel structure/control law design problem formulation is given, and the use of Linear Quadratic Gaussian (LQG) control law design and design sensitivity methods within the formulation is illustrated. Results of three simple integrated structure/control law design examples are presented. These results show the capability of structure and control law design tradeoffs to improve controlled system performance within the multilevel approach.
Total energy control system autopilot design with constrained parameter optimization
NASA Technical Reports Server (NTRS)
Ly, Uy-Loi; Voth, Christopher
1990-01-01
A description is given of the application of a multivariable control design method (SANDY) based on constrained parameter optimization to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the direct synthesis of a multiloop AFCS inner-loop feedback control system based on total energy control system (TECS) principles. The design procedure offers a structured approach for the determination of a set of stabilizing controller design gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The approach can be extended to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by proper formulation of the design objectives and constraints. Satisfactory designs are usually obtained in few iterations. Performance characteristics of the optimized TECS design have been improved, particularly in the areas of closed-loop damping and control activity in the presence of turbulence.
Parametric optimal bounded feedback control for smart parameter-controllable composite structures
NASA Astrophysics Data System (ADS)
Ying, Z. G.; Ni, Y. Q.; Duan, Y. F.
2015-03-01
Deterministic and stochastic parametric optimal bounded control problems are presented for smart composite structures such as magneto-rheological visco-elastomer based sandwich beam with controllable bounded parameters subjected to initial disturbances and stochastic excitations. The parametric controls by actively adjusting system parameters differ from the conventional additive controls by systemic external inputs. The dynamical programming equations for the optimal parametric controls are derived based on the deterministic and stochastic dynamical programming principles. The optimal bounded functions of controls are firstly obtained from the equations with the bounded control constraints based on the bang-bang control strategy. Then the optimal bounded parametric control laws are obtained by the inversion of the nonlinear functions. The stability of the optimally controlled systems is proved according to the Lyapunov method. Finally, the proposed optimal bounded parametric feedback control strategy is applied to single-degree-of-freedom and two-degree-of-freedom dynamic systems with nonlinear parametric bounded control terms under initial disturbances and earthquake excitations and then to a magneto-rheological visco-elastomer based sandwich beam system with nonlinear parametric bounded control terms under stochastic excitations. The effective vibration suppression is illustrated with numerical results. The proposed optimal parametric control strategy is applicable to other smart composite structures with nonlinear controllable parameters.
Satellite tracking by combined optimal estimation and control techniques.
NASA Technical Reports Server (NTRS)
Dressler, R. M.; Tabak, D.
1971-01-01
Combined optimal estimation and control techniques are applied for the first time to satellite tracking systems. Both radio antenna and optical tracking systems of NASA are considered. The optimal estimation is accomplished using an extended Kalman filter resulting in an estimated state of the satellite and of the tracking system. This estimated state constitutes an input to the optimal controller. The optimal controller treats a linearized system with a quadratic performance index. The maximum principle is applied and a steady-state approximation to the resulting Riccati equation is obtained. A computer program, RATS, implementing this algorithm is described. A feasibility study of real-time implementation, tracking simulations, and parameter sensitivity studies are also reported.
Optimal charge control strategies for stationary photovoltaic battery systems
NASA Astrophysics Data System (ADS)
Li, Jiahao; Danzer, Michael A.
2014-07-01
Battery systems coupled to photovoltaic (PV) modules for example fulfill one major function: they locally decouple PV generation and consumption of electrical power leading to two major effects. First, they reduce the grid load, especially at peak times and therewith reduce the necessity of a network expansion. And second, they increase the self-consumption in households and therewith help to reduce energy expenses. For the management of PV batteries charge control strategies need to be developed to reach the goals of both the distribution system operators and the local power producer. In this work optimal control strategies regarding various optimization goals are developed on the basis of the predicted household loads and PV generation profiles using the method of dynamic programming. The resulting charge curves are compared and essential differences discussed. Finally, a multi-objective optimization shows that charge control strategies can be derived that take all optimization goals into account.
Linear quadratic optimal controller for cable-driven parallel robots
NASA Astrophysics Data System (ADS)
Abdolshah, Saeed; Shojaei Barjuei, Erfan
2015-12-01
In recent years, various cable-driven parallel robots have been investigated for their advantages, such as low structural weight, high acceleration, and large work-space, over serial and conventional parallel systems. However, the use of cables lowers the stiffness of these robots, which in turn may decrease motion accuracy. A linear quadratic (LQ) optimal controller can provide all the states of a system for the feedback, such as position and velocity. Thus, the application of such an optimal controller in cable-driven parallel robots can result in more efficient and accurate motion compared to the performance of classical controllers such as the proportional- integral-derivative controller. This paper presents an approach to apply the LQ optimal controller on cable-driven parallel robots. To employ the optimal control theory, the static and dynamic modeling of a 3-DOF planar cable-driven parallel robot (Feriba-3) is developed. The synthesis of the LQ optimal control is described, and the significant experimental results are presented and discussed.
Optimizing and controlling the operation of heat-exchanger networks
Aguilera, N.; Marchetti, J.L.
1998-05-01
A procedure was developed for on-line optimization and control systems of heat-exchanger networks, which features a two-level control structure, one for a constant configuration control system and the other for a supervisor on-line optimizer. The coordination between levels is achieved by adjusting the formulation of the optimization problem to meet requirements of the adopted control system. The general goal is always to work without losing stream temperature targets while keeping the highest energy integration. The operation constraints used for heat-exchanger and utility units emphasize the computation of heat-exchanger duties rather than intermediate stream temperatures. This simplifies the modeling task and provides clear links with the limits of the manipulated variables. The optimal condition is determined using LP or NLP, depending on the final problem formulation. Degrees of freedom for optimization and equation constraints for considering simple and multiple bypasses are rigorously discussed. An example used shows how the optimization problem can be adjusted to a specific network design, its expected operating space, and the control configuration. Dynamic simulations also show benefits and limitations of this procedure.
Optimizing wind turbine control system parameters
Schluter, L.L.; Vachon, W.A.
1993-08-01
The impending expiration of the levelized period in the Interim Standard Offer Number 4 (ISO4) utility contracts for purchasing wind-generated power in California mandates, more than ever, that windplants be operated in a cost-effective manner. Operating plans and approaches are needed that maximize the net revenue from wind parks--after accounting for operation and maintenance costs. This paper describes a design tool that makes it possible to tailor a control system of a wind turbine (WT) to maximize energy production while minimizing the financial consequences of fatigue damage to key structural components. Plans for code enhancements to include expert systems and fuzzy logic are discussed, and typical results are presented in which the code is applied to study the controls of a generic Danish 15-m horizontal axis wind turbine (HAWT).
Optimizing wind turbine control system parameters
NASA Astrophysics Data System (ADS)
Schluter, Larry L.; Vachon, William A.
1993-05-01
The impending expiration of the levelized period in the Interim Standard Offer Number 4 (ISO4) utility contracts for purchasing wind-generated power in California mandates, more than ever, that windplants be operated in a cost-effective manner. Operating plans and approaches are needed that maximize the net revenue from wind parks--after accounting for operation and maintenance costs. This paper describes a design tool that makes it possible to tailor a control system of a wind turbine (WT) to maximize energy production while minimizing the financial consequences of fatigue damage to key structural components. Plans for code enhancements to include expert systems and fuzzy logic are discussed, and typical results are presented in which the code is applied to study the controls of a generic Danish 15-m horizontal axis wind turbine (HAWT).
Adaptive control based on retrospective cost optimization
NASA Technical Reports Server (NTRS)
Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)
2012-01-01
A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.
Induction factor optimization through variable lift control
NASA Astrophysics Data System (ADS)
Cooney, John; Corke, Thomas; Nelson, Robert; Williams, Theodore
2011-11-01
Due to practical design limitations coupled with the detrimental effects posed by complex wind regimes, modern wind turbines struggle to maintain or even reach ideal operational states. With additional gains through traditional approaches becoming more difficult and costly, active lift control represents a more attractive option for future designs. Here, plasma actuators have been explored experimentally in trailing edge applications for use in attached flow regimes. This authority would be used to drive the axial induction factor toward the ideal given by the Betz limit through distributed lift control thereby enhancing energy capture. Predictions of power improvement achievable by this methodology are made with blade - element momentum theory but will eventually be demonstrated in the field at the Laboratory for Enhanced Wind Energy Design, currently under construction at the University of Notre Dame.
Lyapunov optimal feedback control of a nonlinear inverted pendulum
NASA Technical Reports Server (NTRS)
Grantham, W. J.; Anderson, M. J.
1989-01-01
Liapunov optimal feedback control is applied to a nonlinear inverted pendulum in which the control torque was constrained to be less than the nonlinear gravity torque in the model. This necessitates a control algorithm which 'rocks' the pendulum out of its potential wells, in order to stabilize it at a unique vertical position. Simulation results indicate that a preliminary Liapunov feedback controller can successfully overcome the nonlinearity and bring almost all trajectories to the target.
Control optimization of the cryoplant warm compressor station for EAST
Zhuang, M.; Hu, L. B.; Zhou, Z. W.; Xia, G. H.
2014-01-29
The cryogenic control system for EAST (Experimental Advanced Superconducting Tokamak) was designed based on DeltaV DCS of Emerson Corporation. The automatic control of the cryoplant warm compressors has been implemented. However, with ever-degrading performance of critical equipment, the cryoplant operation in the partial design conditions makes the control system fluctuate and unstable. In this paper, the warm compressor control system was optimized to eliminate the pressure oscillation based on the expert PID theory.
Reversible large-scale modification of cortical networks during neuroprosthetic control.
Ganguly, Karunesh; Dimitrov, Dragan F; Wallis, Jonathan D; Carmena, Jose M
2011-05-01
Brain-machine interfaces (BMIs) provide a framework for studying cortical dynamics and the neural correlates of learning. Neuroprosthetic control has been associated with tuning changes in specific neurons directly projecting to the BMI (hereafter referred to as direct neurons). However, little is known about the larger network dynamics. By monitoring ensembles of neurons that were either causally linked to BMI control or indirectly involved, we found that proficient neuroprosthetic control is associated with large-scale modifications to the cortical network in macaque monkeys. Specifically, there were changes in the preferred direction of both direct and indirect neurons. Notably, with learning, there was a relative decrease in the net modulation of indirect neural activity in comparison with direct activity. These widespread differential changes in the direct and indirect population activity were markedly stable from one day to the next and readily coexisted with the long-standing cortical network for upper limb control. Thus, the process of learning BMI control is associated with differential modification of neural populations based on their specific relation to movement control. PMID:21499255
Optimally Controlled Flexible Fuel Powertrain System
Duncan Sheppard; Bruce Woodrow; Paul Kilmurray; Simon Thwaite
2011-06-30
A multi phase program was undertaken with the stated goal of using advanced design and development tools to create a unique combination of existing technologies to create a powertrain system specification that allowed minimal increase of volumetric fuel consumption when operating on E85 relative to gasoline. Although on an energy basis gasoline / ethanol blends typically return similar fuel economy to straight gasoline, because of its lower energy density (gasoline ~ 31.8MJ/l and ethanol ~ 21.1MJ/l) the volume based fuel economy of gasoline / ethanol blends are typically considerably worse. This project was able to define an initial engine specification envelope, develop specific hardware for the application, and test that hardware in both single and multi-cylinder test engines to verify the ability of the specified powertrain to deliver reduced E85 fuel consumption. Finally, the results from the engine testing were used in a vehicle drive cycle analysis tool to define a final vehicle level fuel economy result. During the course of the project, it was identified that the technologies utilized to improve fuel economy on E85 also enabled improved fuel economy when operating on gasoline. However, the E85 fueled powertrain provided improved vehicle performance when compared to the gasoline fueled powertrain due to the improved high load performance of the E85 fuel. Relative to the baseline comparator engine and considering current market fuels, the volumetric fuel consumption penalty when running on E85 with the fully optimized project powertrain specification was reduced significantly. This result shows that alternative fuels can be utilized in high percentages while maintaining or improving vehicle performance and with minimal or positive impact on total cost of ownership to the end consumer. The justification for this project was two-fold. In order to reduce the US dependence on crude oil, much of which is imported, the US Environmental Protection Agency (EPA
Solving Optimal Control Problems by Exploiting Inherent Dynamical Systems Structures
NASA Astrophysics Data System (ADS)
Flaßkamp, Kathrin; Ober-Blöbaum, Sina; Kobilarov, Marin
2012-08-01
Computing globally efficient solutions is a major challenge in optimal control of nonlinear dynamical systems. This work proposes a method combining local optimization and motion planning techniques based on exploiting inherent dynamical systems structures, such as symmetries and invariant manifolds. Prior to the optimal control, the dynamical system is analyzed for structural properties that can be used to compute pieces of trajectories that are stored in a motion planning library. In the context of mechanical systems, these motion planning candidates, termed primitives, are given by relative equilibria induced by symmetries and motions on stable or unstable manifolds of e.g. fixed points in the natural dynamics. The existence of controlled relative equilibria is studied through Lagrangian mechanics and symmetry reduction techniques. The proposed framework can be used to solve boundary value problems by performing a search in the space of sequences of motion primitives connected using optimized maneuvers. The optimal sequence can be used as an admissible initial guess for a post-optimization. The approach is illustrated by two numerical examples, the single and the double spherical pendula, which demonstrates its benefit compared to standard local optimization techniques.
Optimal Pid Controller Design Using Adaptive Vurpso Algorithm
NASA Astrophysics Data System (ADS)
Zirkohi, Majid Moradi
2015-04-01
The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.
Controllable local modification of fractured Nb-doped SrTiO{sub 3} surfaces.
Chien, T. Y.; Santos, T. S.; Bode, M.; Guisinger, N. P.; Freeland, J. W.
2009-01-01
Nanoscale surface modification of a fractured Nb-doped SrTiO{sub 3} surface is demonstrated in a controlled way by scanning tunneling microscopy. By applying positive voltage pulses, holes can be created and the width and depth of the hole can be controlled by selecting the appropriate bias and pulse duration. The process shows a threshold condition for creation of the holes and change in the local electronic density of state consistent with exposure of the underlying TiO{sub 2} layer by removal of SrO. By applying negative bias, the hole can be partially refilled from the transfer of adsorbates on the tip.
Tischner, Christin; Hofer, Annette; Wulff, Veronika; Stepek, Joanna; Dumitru, Iulia; Becker, Lore; Haack, Tobias; Kremer, Laura; Datta, Alexandre N.; Sperl, Wolfgang; Floss, Thomas; Wurst, Wolfgang; Chrzanowska-Lightowlers, Zofia; De Angelis, Martin Hrabe; Klopstock, Thomas; Prokisch, Holger; Wenz, Tina
2015-01-01
Mitochondrial diseases often exhibit tissue-specific pathologies, but this phenomenon is poorly understood. Here we present regulation of mitochondrial translation by the Mitochondrial Translation Optimization Factor 1, MTO1, as a novel player in this scenario. We demonstrate that MTO1 mediates tRNA modification and controls mitochondrial translation rate in a highly tissue-specific manner associated with tissue-specific OXPHOS defects. Activation of mitochondrial proteases, aberrant translation products, as well as defects in OXPHOS complex assembly observed in MTO1 deficient mice further imply that MTO1 impacts translation fidelity. In our mouse model, MTO1-related OXPHOS deficiency can be bypassed by feeding a ketogenic diet. This therapeutic intervention is independent of the MTO1-mediated tRNA modification and involves balancing of mitochondrial and cellular secondary stress responses. Our results thereby establish mammalian MTO1 as a novel factor in the tissue-specific regulation of OXPHOS and fine tuning of mitochondrial translation accuracy. PMID:25552653
Exploring quantum control landscapes: Topology, features, and optimization scaling
Moore, Katharine W.; Rabitz, Herschel
2011-07-15
Quantum optimal control experiments and simulations have successfully manipulated the dynamics of systems ranging from atoms to biomolecules. Surprisingly, these collective works indicate that the effort (i.e., the number of algorithmic iterations) required to find an optimal control field appears to be essentially invariant to the complexity of the system. The present work explores this matter in a series of systematic optimizations of the state-to-state transition probability on model quantum systems with the number of states N ranging from 5 through 100. The optimizations occur over a landscape defined by the transition probability as a function of the control field. Previous theoretical studies on the topology of quantum control landscapes established that they should be free of suboptimal traps under reasonable physical conditions. The simulations in this work include nearly 5000 individual optimization test cases, all of which confirm this prediction by fully achieving optimal population transfer of at least 99.9% on careful attention to numerical procedures to ensure that the controls are free of constraints. Collectively, the simulation results additionally show invariance of required search effort to system dimension N. This behavior is rationalized in terms of the structural features of the underlying control landscape. The very attractive observed scaling with system complexity may be understood by considering the distance traveled on the control landscape during a search and the magnitude of the control landscape slope. Exceptions to this favorable scaling behavior can arise when the initial control field fluence is too large or when the target final state recedes from the initial state as N increases.
Polynomial method for PLL controller optimization.
Wang, Ta-Chung; Lall, Sanjay; Chiou, Tsung-Yu
2011-01-01
The Phase-Locked Loop (PLL) is a key component of modern electronic communication and control systems. PLL is designed to extract signals from transmission channels. It plays an important role in systems where it is required to estimate the phase of a received signal, such as carrier tracking from global positioning system satellites. In order to robustly provide centimeter-level accuracy, it is crucial for the PLL to estimate the instantaneous phase of an incoming signal which is usually buried in random noise or some type of interference. This paper presents an approach that utilizes the recent development in the semi-definite programming and sum-of-squares field. A Lyapunov function will be searched as the certificate of the pull-in range of the PLL system. Moreover, a polynomial design procedure is proposed to further refine the controller parameters for system response away from the equilibrium point. Several simulation results as well as an experiment result are provided to show the effectiveness of this approach. PMID:22163973
Optimization of structure-control systems with efficiency constraint
NASA Technical Reports Server (NTRS)
Oz, H.; Khot, N. S.
1990-01-01
The structure-control system optimization problem is formulated with constraints on the closed-loop eigenvalues and the efficiency of the reduced order system. The feasibility of the approach is illustrated by designing the ACOSS-FOUR structure with a reduced order system and improving the efficiency characteristics of the structures-control system.
OPTIMIZATION OF DECENTRALIZED BMP CONTROLS IN URBAN AREAS
This paper will present an overview of a recently completed project for the US EPA entitled, Optimization of Urban Wet-weather Flow Control Systems. The focus of this effort is on techniques that are suitable for evaluating decentralized BMP controls. The four major components ...
OPTIMIZATION OF DECENTRALIZED BMP CONTROLS IN URBAN AREAS
This paper will present an overview of a recently completed project for the US EPA entitled Optimization of Urban Wet-weather Flow Control Systems. The focus of this effort is on techniques that are suitable for evaluating decentralized BMP controls. The four major components o...
Optimal Control of a Dengue Epidemic Model with Vaccination
NASA Astrophysics Data System (ADS)
Rodrigues, Helena Sofia; Teresa, M.; Monteiro, T.; Torres, Delfim F. M.
2011-09-01
We present a SIR+ASI epidemic model to describe the interaction between human and dengue fever mosquito populations. A control strategy in the form of vaccination, to decrease the number of infected individuals, is used. An optimal control approach is applied in order to find the best way to fight the disease.
Sensitivity Analysis and Optimal Control of Anthroponotic Cutaneous Leishmania
Zamir, Muhammad; Zaman, Gul; Alshomrani, Ali Saleh
2016-01-01
This paper is focused on the transmission dynamics and optimal control of Anthroponotic Cutaneous Leishmania. The threshold condition R0 for initial transmission of infection is obtained by next generation method. Biological sense of the threshold condition is investigated and discussed in detail. The sensitivity analysis of the reproduction number is presented and the most sensitive parameters are high lighted. On the basis of sensitivity analysis, some control strategies are introduced in the model. These strategies positively reduce the effect of the parameters with high sensitivity indices, on the initial transmission. Finally, an optimal control strategy is presented by taking into account the cost associated with control strategies. It is also shown that an optimal control exists for the proposed control problem. The goal of optimal control problem is to minimize, the cost associated with control strategies and the chances of infectious humans, exposed humans and vector population to become infected. Numerical simulations are carried out with the help of Runge-Kutta fourth order procedure. PMID:27505634
Optimal control of precision paraboloidal shell structronic systems
NASA Astrophysics Data System (ADS)
Tzou, H. S.; Ding, J. H.
2004-09-01
Paraboloidal shells of revolution are commonly used in advanced aerospace, civil and telecommunication structures, e.g., antennas, reflectors, mirrors, rocket fairings, nozzles, solar collectors, dome structures, etc. A structronic shell system is defined as an elastic shell embedded, bonded or laminated with distributed piezoelectric sensors and actuators and it is governed by either in situ or external control electronics. A closed-loop control system of paraboloidal shell structronic system consists of distributed sensors/actuators and controller coupled with an elastic paraboloidal shell. State equation for the paraboloidal shell structronic system is derived and optimal linear quadratic state feedback control is implemented, such that the "best" shell control performance with the least control cost can be achieved. The gain matrix is estimated based on minimizing a performance criterion function. Optimal control effects are compared with controlled responses with other non-optimal control parameters. Control effects of identical-sized sensor/actuator patches at different locations are studied and compared. Modal control effects for different natural modes are also investigated.
Solving the optimal attention allocation problem in manual control
NASA Technical Reports Server (NTRS)
Kleinman, D. L.
1976-01-01
Within the context of the optimal control model of human response, analytic expressions for the gradients of closed-loop performance metrics with respect to human operator attention allocation are derived. These derivatives serve as the basis for a gradient algorithm that determines the optimal attention that a human should allocate among several display indicators in a steady-state manual control task. Application of the human modeling techniques are made to study the hover control task for a CH-46 VTOL flight tested by NASA.
State-Constrained Optimal Control Problems of Impulsive Differential Equations
Forcadel, Nicolas; Rao Zhiping Zidani, Hasnaa
2013-08-01
The present paper studies an optimal control problem governed by measure driven differential systems and in presence of state constraints. The first result shows that using the graph completion of the measure, the optimal solutions can be obtained by solving a reparametrized control problem of absolutely continuous trajectories but with time-dependent state-constraints. The second result shows that it is possible to characterize the epigraph of the reparametrized value function by a Hamilton-Jacobi equation without assuming any controllability assumption.
Optimization of an Aeroservoelastic Wing with Distributed Multiple Control Surfaces
NASA Technical Reports Server (NTRS)
Stanford, Bret K.
2015-01-01
This paper considers the aeroelastic optimization of a subsonic transport wingbox under a variety of static and dynamic aeroelastic constraints. Three types of design variables are utilized: structural variables (skin thickness, stiffener details), the quasi-steady deflection scheduling of a series of control surfaces distributed along the trailing edge for maneuver load alleviation and trim attainment, and the design details of an LQR controller, which commands oscillatory hinge moments into those same control surfaces. Optimization problems are solved where a closed loop flutter constraint is forced to satisfy the required flight margin, and mass reduction benefits are realized by relaxing the open loop flutter requirements.
NASA Astrophysics Data System (ADS)
Zhang, Bo; Zhong, Zhaoping; Song, Zuwei; Ding, Kuan; Chen, Paul; Ruan, Roger
2015-12-01
In order to minimize coke yield during biomass catalytic fast pyrolysis (CFP) process, ethylene diamine tetraacetie acid (EDTA) chemical modification method is carried out to selectively remove the external framework aluminum of HZSM-5 catalyst. X-ray diffraction (XRD), nitrogen (N2)-adsorption and ammonia-temperature programmed desorption (NH3-TPD) techniques are employed to investigate the porosity and acidity characteristics of original and modified HZSM-5 samples. Py-GC/MS and thermo-gravimetric analyzer (TGA) experiments are further conducted to explore the catalytic effect of modified HZSM-5 samples on biomass CFP and to verify the positive effect on coke reduction. Results show that EDTA treatment does not damage the crystal structure of HZSM-5 zeolites, but leads to a slight increase of pore volume and pore size. Meanwhile, the elimination of the strong acid peak indicates the dealumination of outer surface of HZSM-5 zeolites. Treatment time of 2 h (labeled EDTA-2H) is optimal for acid removal and hydrocarbon formation. Among all modified catalysts, EDTA-2H performs the best for deacidification and can obviously increase the yields of positive chemical compositions in pyrolysis products. Besides, EDTA modification can improve the anti-coking properties of HZSM-5 zeolites, and EDTA-2H gives rise to the lowest coke yield.
Optimization of robustness of network controllability against malicious attacks
NASA Astrophysics Data System (ADS)
Xiao, Yan-Dong; Lao, Song-Yang; Hou, Lv-Lin; Bai, Liang
2014-11-01
As the controllability of complex networks has attracted much attention recently, how to design and optimize the robustness of network controllability has become a common and urgent problem in the engineering field. In this work, we propose a method that modifies any given network with strict structural perturbation to effectively enhance its robustness against malicious attacks, called dynamic optimization of controllability. Unlike other structural perturbations, the strict perturbation only swaps the links and keeps the in- and out-degree unchanged. A series of extensive experiments show that the robustness of controllability and connectivity can be improved dramatically. Furthermore, the effectiveness of our method is explained from the views of underlying structure. The analysis results indicate that the optimization algorithm makes networks more homogenous and assortative.
Optimal wavefront control for adaptive segmented mirrors
NASA Technical Reports Server (NTRS)
Downie, John D.; Goodman, Joseph W.
1989-01-01
A ground-based astronomical telescope with a segmented primary mirror will suffer image-degrading wavefront aberrations from at least two sources: (1) atmospheric turbulence and (2) segment misalignment or figure errors of the mirror itself. This paper describes the derivation of a mirror control feedback matrix that assumes the presence of both types of aberration and is optimum in the sense that it minimizes the mean-squared residual wavefront error. Assumptions of the statistical nature of the wavefront measurement errors, atmospheric phase aberrations, and segment misalignment errors are made in the process of derivation. Examples of the degree of correlation are presented for three different types of wavefront measurement data and compared to results of simple corrections.
Parameter optimization in AQM controller design to support TCP traffic
NASA Astrophysics Data System (ADS)
Yang, Wei; Yang, Oliver W.
2004-09-01
TCP congestion control mechanism has been widely investigated and deployed on Internet in preventing congestion collapse. We would like to employ modern control theory to specify quantitatively the control performance of the TCP communication system. In this paper, we make use of a commonly used performance index called the Integral of the Square of the Error (ISE), which is a quantitative measure to gauge the performance of a control system. By applying the ISE performance index into the Proportional-plus-Integral controller based on Pole Placement (PI_PP controller) for active queue management (AQM) in IP routers, we can further tune the parameters for the controller to achieve an optimum control minimizing control errors. We have analyzed the dynamic model of the TCP congestion control under this ISE, and used OPNET simulation tool to verify the derived optimized parameters of the controllers.
Control optimization, stabilization and computer algorithms for aircraft applications
NASA Technical Reports Server (NTRS)
Athans, M. (Editor); Willsky, A. S. (Editor)
1982-01-01
The analysis and design of complex multivariable reliable control systems are considered. High performance and fault tolerant aircraft systems are the objectives. A preliminary feasibility study of the design of a lateral control system for a VTOL aircraft that is to land on a DD963 class destroyer under high sea state conditions is provided. Progress in the following areas is summarized: (1) VTOL control system design studies; (2) robust multivariable control system synthesis; (3) adaptive control systems; (4) failure detection algorithms; and (5) fault tolerant optimal control theory.
Optimal control of information epidemics modeled as Maki Thompson rumors
NASA Astrophysics Data System (ADS)
Kandhway, Kundan; Kuri, Joy
2014-12-01
We model the spread of information in a homogeneously mixed population using the Maki Thompson rumor model. We formulate an optimal control problem, from the perspective of single campaigner, to maximize the spread of information when the campaign budget is fixed. Control signals, such as advertising in the mass media, attempt to convert ignorants and stiflers into spreaders. We show the existence of a solution to the optimal control problem when the campaigning incurs non-linear costs under the isoperimetric budget constraint. The solution employs Pontryagin's Minimum Principle and a modified version of forward backward sweep technique for numerical computation to accommodate the isoperimetric budget constraint. The techniques developed in this paper are general and can be applied to similar optimal control problems in other areas. We have allowed the spreading rate of the information epidemic to vary over the campaign duration to model practical situations when the interest level of the population in the subject of the campaign changes with time. The shape of the optimal control signal is studied for different model parameters and spreading rate profiles. We have also studied the variation of the optimal campaigning costs with respect to various model parameters. Results indicate that, for some model parameters, significant improvements can be achieved by the optimal strategy compared to the static control strategy. The static strategy respects the same budget constraint as the optimal strategy and has a constant value throughout the campaign horizon. This work finds application in election and social awareness campaigns, product advertising, movie promotion and crowdfunding campaigns.
Optimal Control of Transitions between Nonequilibrium Steady States
Zulkowski, Patrick R.; Sivak, David A.; DeWeese, Michael R.
2013-01-01
Biological systems fundamentally exist out of equilibrium in order to preserve organized structures and processes. Many changing cellular conditions can be represented as transitions between nonequilibrium steady states, and organisms have an interest in optimizing such transitions. Using the Hatano-Sasa Y-value, we extend a recently developed geometrical framework for determining optimal protocols so that it can be applied to systems driven from nonequilibrium steady states. We calculate and numerically verify optimal protocols for a colloidal particle dragged through solution by a translating optical trap with two controllable parameters. We offer experimental predictions, specifically that optimal protocols are significantly less costly than naive ones. Optimal protocols similar to these may ultimately point to design principles for biological energy transduction systems and guide the design of artificial molecular machines. PMID:24386112
Optimizing Optics For Remotely Controlled Underwater Vehicles
NASA Astrophysics Data System (ADS)
Billet, A. B.
1984-09-01
The past decade has shown a dramatic increase in the use of unmanned tethered vehicles in worldwide marine fields. These vehicles are used for inspection, debris removal and object retrieval. With advanced robotic technology, remotely operated vehicles (ROVs) are now able to perform a variety of jobs previously accomplished only by divers. The ROVs can be used at greater depths and for riskier jobs, and safety to the diver is increased, freeing him for safer, more cost-effective tasks requiring human capabilities. Secondly, the ROV operation becomes more cost effective to use as work depth increases. At 1000 feet a diver's 10 minutes of work can cost over $100,000 including support personnel, while an ROV operational cost might be 1/20 of the diver cost per day, based on the condition that the cost for ROV operation does not change with depth, as it does for divers. In the ROV operation the television lens must be as good as the human eye, with better light gathering capability than the human eye. The RCV-150 system is an example of these advanced technology vehicles. With the requirements of manueuverability and unusual inspection, a responsive, high performance, compact vehicle was developed. The RCV-150 viewing subsystem consists of a television camera, lights, and topside monitors. The vehicle uses a low light level Newvicon television camera. The camera is equipped with a power-down iris that closes for burn protection when the power is off. The camera can pan f 50 degrees and tilt f 85 degrees on command from the surface. Four independently controlled 250 watt quartz halogen flood lamps illuminate the viewing area as required; in addition, two 250 watt spotlights are fitted. A controlled nine inch CRT monitor provides real time camera pictures for the operator. The RCV-150 vehicle component system consists of the vehicle structure, the vehicle electronics, and hydraulic system which powers the thruster assemblies and the manipulator. For this vehicle, a light
Exploring the complexity of quantum control optimization trajectories.
Nanduri, Arun; Shir, Ofer M; Donovan, Ashley; Ho, Tak-San; Rabitz, Herschel
2015-01-01
The control of quantum system dynamics is generally performed by seeking a suitable applied field. The physical objective as a functional of the field forms the quantum control landscape, whose topology, under certain conditions, has been shown to contain no critical point suboptimal traps, thereby enabling effective searches for fields that give the global maximum of the objective. This paper addresses the structure of the landscape as a complement to topological critical point features. Recent work showed that landscape structure is highly favorable for optimization of state-to-state transition probabilities, in that gradient-based control trajectories to the global maximum value are nearly straight paths. The landscape structure is codified in the metric R ≥ 1.0, defined as the ratio of the length of the control trajectory to the Euclidean distance between the initial and optimal controls. A value of R = 1 would indicate an exactly straight trajectory to the optimal observable value. This paper extends the state-to-state transition probability results to the quantum ensemble and unitary transformation control landscapes. Again, nearly straight trajectories predominate, and we demonstrate that R can take values approaching 1.0 with high precision. However, the interplay of optimization trajectories with critical saddle submanifolds is found to influence landscape structure. A fundamental relationship necessary for perfectly straight gradient-based control trajectories is derived, wherein the gradient on the quantum control landscape must be an eigenfunction of the Hessian. This relation is an indicator of landscape structure and may provide a means to identify physical conditions when control trajectories can achieve perfect linearity. The collective favorable landscape topology and structure provide a foundation to understand why optimal quantum control can be readily achieved. PMID:25377547
Monotonically convergent optimization in quantum control using Krotov's method
Reich, Daniel M.; Koch, Christiane P.; Ndong, Mamadou
2012-03-14
The non-linear optimization method developed by A. Konnov and V. Krotov [Autom. Remote Cont. (Engl. Transl.) 60, 1427 (1999)] has been used previously to extend the capabilities of optimal control theory from the linear to the non-linear Schroedinger equation [S. E. Sklarz and D. J. Tannor, Phys. Rev. A 66, 053619 (2002)]. Here we show that based on the Konnov-Krotov method, monotonically convergent algorithms are obtained for a large class of quantum control problems. It includes, in addition to nonlinear equations of motion, control problems that are characterized by non-unitary time evolution, nonlinear dependencies of the Hamiltonian on the control, time-dependent targets, and optimization functionals that depend to higher than second order on the time-evolving states. We furthermore show that the nonlinear (second order) contribution can be estimated either analytically or numerically, yielding readily applicable optimization algorithms. We demonstrate monotonic convergence for an optimization functional that is an eighth-degree polynomial in the states. For the ''standard'' quantum control problem of a convex final-time functional, linear equations of motion and linear dependency of the Hamiltonian on the field, the second-order contribution is not required for monotonic convergence but can be used to speed up convergence. We demonstrate this by comparing the performance of first- and second-order algorithms for two examples.
Strong stabilization servo controller with optimization of performance criteria.
Sarjaš, Andrej; Svečko, Rajko; Chowdhury, Amor
2011-07-01
Synthesis of a simple robust controller with a pole placement technique and a H(∞) metrics is the method used for control of a servo mechanism with BLDC and BDC electric motors. The method includes solving a polynomial equation on the basis of the chosen characteristic polynomial using the Manabe standard polynomial form and parametric solutions. Parametric solutions are introduced directly into the structure of the servo controller. On the basis of the chosen parametric solutions the robustness of a closed-loop system is assessed through uncertainty models and assessment of the norm ‖•‖(∞). The design procedure and the optimization are performed with a genetic algorithm differential evolution - DE. The DE optimization method determines a suboptimal solution throughout the optimization on the basis of a spectrally square polynomial and Šiljak's absolute stability test. The stability of the designed controller during the optimization is being checked with Lipatov's stability condition. Both utilized approaches: Šiljak's test and Lipatov's condition, check the robustness and stability characteristics on the basis of the polynomial's coefficients, and are very convenient for automated design of closed-loop control and for application in optimization algorithms such as DE. PMID:21501837
Optimized Reactive Power Compensation Using Fuzzy Logic Controller
NASA Astrophysics Data System (ADS)
George, S.; Mini, K. N.; Supriya, K.
2015-03-01
Reactive power flow in a long transmission line plays a vital role in power transfer capability and voltage stability in power system. Traditionally, shunt connected compensators are used to control reactive power in long transmission line. Thyristor controlled reactor is used to control reactive power under lightly loaded condition. By controlling firing angle of thyristor, it is possible to control reactive power in the transmission lines. However, thyristor controlled reactor will inject harmonic current into the system. An attempt to reduce reactive power injection will increase harmonic distortion in the line current and vice versa. Thus, there is a trade-off between reactive power injection and harmonics in current. By optimally controlling the reactive power injection, harmonics in current can be brought within the specified limit. In this paper, a Fuzzy Logic Controller is implemented to obtain optimal control of reactive power of the compensator to maintain voltage and harmonic in current within the limits. An algorithm which optimizes the firing angle in each fuzzy subset by calculating the rank of feasible firing angles is proposed for the construction of rules in Fuzzy Logic Controller. The novelty of the algorithm is that it uses a simple error formula for the calculation of the rank of the feasible firing angles in each fuzzy subset.
Optimal Robust Motion Controller Design Using Multiobjective Genetic Algorithm
Svečko, Rajko
2014-01-01
This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm—differential evolution. PMID:24987749
Optimal periodic control for spacecraft pointing and attitude determination
NASA Technical Reports Server (NTRS)
Pittelkau, Mark E.
1993-01-01
A new approach to autonomous magnetic roll/yaw control of polar-orbiting, nadir-pointing momentum bias spacecraft is considered as the baseline attitude control system for the next Tiros series. It is shown that the roll/yaw dynamics with magnetic control are periodically time varying. An optimal periodic control law is then developed. The control design features a state estimator that estimates attitude, attitude rate, and environmental torque disturbances from Earth sensor and sun sensor measurements; no gyros are needed. The state estimator doubles as a dynamic attitude determination and prediction function. In addition to improved performance, the optimal controller allows a much smaller momentum bias than would otherwise be necessary. Simulation results are given.
Optimal Variable-Structure Control Tracking of Spacecraft Maneuvers
NASA Technical Reports Server (NTRS)
Crassidis, John L.; Vadali, Srinivas R.; Markley, F. Landis
1999-01-01
An optimal control approach using variable-structure (sliding-mode) tracking for large angle spacecraft maneuvers is presented. The approach expands upon a previously derived regulation result using a quaternion parameterization for the kinematic equations of motion. This parameterization is used since it is free of singularities. The main contribution of this paper is the utilization of a simple term in the control law that produces a maneuver to the reference attitude trajectory in the shortest distance. Also, a multiplicative error quaternion between the desired and actual attitude is used to derive the control law. Sliding-mode switching surfaces are derived using an optimal-control analysis. Control laws are given using either external torque commands or reaction wheel commands. Global asymptotic stability is shown for both cases using a Lyapunov analysis. Simulation results are shown which use the new control strategy to stabilize the motion of the Microwave Anisotropy Probe spacecraft.
Optimal startup control of a jacketed tubular reactor.
NASA Technical Reports Server (NTRS)
Hahn, D. R.; Fan, L. T.; Hwang, C. L.
1971-01-01
The optimal startup policy of a jacketed tubular reactor, in which a first-order, reversible, exothermic reaction takes place, is presented. A distributed maximum principle is presented for determining weak necessary conditions for optimality of a diffusional distributed parameter system. A numerical technique is developed for practical implementation of the distributed maximum principle. This involves the sequential solution of the state and adjoint equations, in conjunction with a functional gradient technique for iteratively improving the control function.
Solving bi-objective optimal control problems with rectangular framing
NASA Astrophysics Data System (ADS)
Wijaya, Karunia Putra; Götz, Thomas
2016-06-01
Optimization problems, e.g. arising from epidemiology models, often ask for solutions minimizing multi-criteria objective functions. In this paper we discuss a novel approach for solving bi-objective optimal control problems. The set of non-dominated points is constructed via a decreasing sequence of rectangles. Particular attention is paid to a problem with disconnected set of non-dominated points. Several examples from epidemiology are investigated and show the applicability of the method.
Optimal control of vaccine distribution in a rabies metapopulation model.
Asano, Erika; Gross, Louis J; Lenhart, Suzanne; Real, Leslie A
2008-04-01
We consider an SIR metapopulation model for the spread of rabies in raccoons. This system of ordinary differential equations considers subpopulations connected by movement. Vaccine for raccoons is distributed through food baits. We apply optimal control theory to find the best timing for distribution of vaccine in each of the linked subpopulations across the landscape. This strategy is chosen to limit the disease optimally by making the number of infections as small as possible while accounting for the cost of vaccination. PMID:18613731
Flight evaluation of modifications to a digital electronic engine control system in an F-15 airplane
NASA Technical Reports Server (NTRS)
Burcham, F. W., Jr.; Myers, L. P.; Zeller, J. R.
1983-01-01
The third phase of a flight evaluation of a digital electronic engine control system in an F-15 has recently been completed. It was found that digital electronic engine control software logic changes and augmentor hardware improvements resulted in significant improvements in engine operation. For intermediate to maximum power throttle transients, an increase in altitude capability of up to 8000 ft was found, and for idle to maximum transients, an increase of up to 4000 ft was found. A nozzle instability noted in earlier flight testing was investigated on a test engine at NASA Lewis Research Center, a digital electronic engine control software logic change was developed and evaluated, and no instability occurred in the Phase 3 flight evaluation. The backup control airstart modification was evaluated, and gave an improvement of airstart capability by reducing the minimum airspeed for successful airstarts by 50 to 75 knots.
Modification and testing of an engine and fuel control system for a hydrogen fuelled gas turbine
NASA Astrophysics Data System (ADS)
Funke, H. H.-W.; Börner, S.; Hendrick, P.; Recker, E.
2011-10-01
The control of pollutant emissions has become more and more important by the development of new gas turbines. The use of hydrogen produced by renewable energy sources could be an alternative. Besides the reduction of NOx emissions emerged during the combustion process, another major question is how a hydrogen fuelled gas turbine including the metering unit can be controlled and operated. This paper presents a first insight in modifications on an Auxiliary Power Unit (APU) GTCP 36300 for using gaseous hydrogen as a gas turbine fuel. For safe operation with hydrogen, the metering of hydrogen has to be fast, precise, and secure. So, the quality of the metering unit's control loop has an important influence on this topic. The paper documents the empiric determination of the proportional integral derivative (PID) control parameters for the metering unit.
Chen, Nigel T M; Clarke, Patrick J F; Watson, Tamara L; MacLeod, Colin; Guastella, Adam J
2015-01-01
Social anxiety is thought to be maintained by biased attentional processing towards threatening information. Research has further shown that the experimental attenuation of this bias, through the implementation of attentional bias modification (ABM), may serve to reduce social anxiety vulnerability. However, the mechanisms underlying ABM remain unclear. The present study examined whether inhibitory attentional control was associated with ABM. A non-clinical sample of participants was randomly assigned to receive either ABM or a placebo task. To assess pre-post changes in attentional control, participants were additionally administered an emotional antisaccade task. ABM participants exhibited a subsequent shift in attentional bias away from threat as expected. ABM participants further showed a subsequent decrease in antisaccade cost, indicating a general facilitation of inhibitory attentional control. Mediational analysis revealed that the shift in attentional bias following ABM was independent to the change in attentional control. The findings suggest that the mechanisms of ABM are multifaceted. PMID:25527400
Optimal control of switched linear systems based on Migrant Particle Swarm Optimization algorithm
NASA Astrophysics Data System (ADS)
Xie, Fuqiang; Wang, Yongji; Zheng, Zongzhun; Li, Chuanfeng
2009-10-01
The optimal control problem for switched linear systems with internally forced switching has more constraints than with externally forced switching. Heavy computations and slow convergence in solving this problem is a major obstacle. In this paper we describe a new approach for solving this problem, which is called Migrant Particle Swarm Optimization (Migrant PSO). Imitating the behavior of a flock of migrant birds, the Migrant PSO applies naturally to both continuous and discrete spaces, in which definitive optimization algorithm and stochastic search method are combined. The efficacy of the proposed algorithm is illustrated via a numerical example.
Optimal Discrete Event Supervisory Control of Aircraft Gas Turbine Engines
NASA Technical Reports Server (NTRS)
Litt, Jonathan (Technical Monitor); Ray, Asok
2004-01-01
This report presents an application of the recently developed theory of optimal Discrete Event Supervisory (DES) control that is based on a signed real measure of regular languages. The DES control techniques are validated on an aircraft gas turbine engine simulation test bed. The test bed is implemented on a networked computer system in which two computers operate in the client-server mode. Several DES controllers have been tested for engine performance and reliability.
Integrated control/structure optimization by multilevel decomposition
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Gilbert, Michael G.
1990-01-01
A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The present paper fully decomposes the system into structural and control subsystem designs and produces an improved design. Theory, implementation, and results for the method are presented and compared with the benchmark example.
Integrated control/structure optimization by multilevel decomposition
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Gilbert, Michael G.
1990-01-01
A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The system is fully decomposed into structural and control subsystem designs and an improved design is produced. Theory, implementation, and results for the method are presented and compared with the benchmark example.
Optimal control of large space structures via generalized inverse matrix
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Fang, Xiaowen
1987-01-01
Independent Modal Space Control (IMSC) is a control scheme that decouples the space structure into n independent second-order subsystems according to n controlled modes and controls each mode independently. It is well-known that the IMSC eliminates control and observation spillover caused when the conventional coupled modal control scheme is employed. The independent control of each mode requires that the number of actuators be equal to the number of modelled modes, which is very high for a faithful modeling of large space structures. A control scheme is proposed that allows one to use a reduced number of actuators to control all modeled modes suboptimally. In particular, the method of generalized inverse matrices is employed to implement the actuators such that the eigenvalues of the closed-loop system are as closed as possible to those specified by the optimal IMSC. Computer simulation of the proposed control scheme on a simply supported beam is given.
An optimal performance control scheme for a 3D crane
NASA Astrophysics Data System (ADS)
Maghsoudi, Mohammad Javad; Mohamed, Z.; Husain, A. R.; Tokhi, M. O.
2016-01-01
This paper presents an optimal performance control scheme for control of a three dimensional (3D) crane system including a Zero Vibration shaper which considers two control objectives concurrently. The control objectives are fast and accurate positioning of a trolley and minimum sway of a payload. A complete mathematical model of a lab-scaled 3D crane is simulated in Simulink. With a specific cost function the proposed controller is designed to cater both control objectives similar to a skilled operator. Simulation and experimental studies on a 3D crane show that the proposed controller has better performance as compared to a sequentially tuned PID-PID anti swing controller. The controller provides better position response with satisfactory payload sway in both rail and trolley responses. Experiments with different payloads and cable lengths show that the proposed controller is robust to changes in payload with satisfactory responses.
Advanced launch system trajectory optimization using suboptimal control
NASA Technical Reports Server (NTRS)
Shaver, Douglas A.; Hull, David G.
1993-01-01
The maximum-final mass trajectory of a proposed configuration of the Advanced Launch System is presented. A model for the two-stage rocket is given; the optimal control problem is formulated as a parameter optimization problem; and the optimal trajectory is computed using a nonlinear programming code called VF02AD. Numerical results are presented for the controls (angle of attack and velocity roll angle) and the states. After the initial rotation, the angle of attack goes to a positive value to keep the trajectory as high as possible, returns to near zero to pass through the transonic regime and satisfy the dynamic pressure constraint, returns to a positive value to keep the trajectory high and to take advantage of minimum drag at positive angle of attack due to aerodynamic shading of the booster, and then rolls off to negative values to satisfy the constraints. Because the engines cannot be throttled, the maximum dynamic pressure occurs at a single point; there is no maximum dynamic pressure subarc. To test approximations for obtaining analytical solutions for guidance, two additional optimal trajectories are computed: one using untrimmed aerodynamics and one using no atmospheric effects except for the dynamic pressure constraint. It is concluded that untrimmed aerodynamics has a negligible effect on the optimal trajectory and that approximate optimal controls should be able to be obtained by treating atmospheric effects as perturbations.
A Higher Harmonic Optimal Controller to Optimise Rotorcraft Aeromechanical Behaviour
NASA Technical Reports Server (NTRS)
Leyland, Jane Anne
1996-01-01
Three methods to optimize rotorcraft aeromechanical behavior for those cases where the rotorcraft plant can be adequately represented by a linear model system matrix were identified and implemented in a stand-alone code. These methods determine the optimal control vector which minimizes the vibration metric subject to constraints at discrete time points, and differ from the commonly used non-optimal constraint penalty methods such as those employed by conventional controllers in that the constraints are handled as actual constraints to an optimization problem rather than as just additional terms in the performance index. The first method is to use a Non-linear Programming algorithm to solve the problem directly. The second method is to solve the full set of non-linear equations which define the necessary conditions for optimality. The third method is to solve each of the possible reduced sets of equations defining the necessary conditions for optimality when the constraints are pre-selected to be either active or inactive, and then to simply select the best solution. The effects of maneuvers and aeroelasticity on the systems matrix are modelled by using a pseudo-random pseudo-row-dependency scheme to define the systems matrix. Cases run to date indicate that the first method of solution is reliable, robust, and easiest to use, and that it was superior to the conventional controllers which were considered.
Trees, Jason; Snider, Joseph; Falahpour, Maryam; Guo, Nick; Lu, Kun; Johnson, Douglas C; Poizner, Howard; Liu, Thomas T
2014-01-01
Hyperscanning, an emerging technique in which data from multiple interacting subjects' brains are simultaneously recorded, has become an increasingly popular way to address complex topics, such as "theory of mind." However, most previous fMRI hyperscanning experiments have been limited to abstract social interactions (e.g. phone conversations). Our new method utilizes a virtual reality (VR) environment used for military training, Virtual Battlespace 2 (VBS2), to create realistic avatar-avatar interactions and cooperative tasks. To control the virtual avatar, subjects use a MRI compatible Playstation 3 game controller, modified by removing all extraneous metal components and replacing any necessary ones with 3D printed plastic models. Control of both scanners' operation is initiated by a VBS2 plugin to sync scanner time to the known time within the VR environment. Our modifications include:•Modification of game controller to be MRI compatible.•Design of VBS2 virtual environment for cooperative interactions.•Syncing two MRI machines for simultaneous recording. PMID:26150964
Trees, Jason; Snider, Joseph; Falahpour, Maryam; Guo, Nick; Lu, Kun; Johnson, Douglas C.; Poizner, Howard; Liu, Thomas T.
2014-01-01
Hyperscanning, an emerging technique in which data from multiple interacting subjects’ brains are simultaneously recorded, has become an increasingly popular way to address complex topics, such as “theory of mind.” However, most previous fMRI hyperscanning experiments have been limited to abstract social interactions (e.g. phone conversations). Our new method utilizes a virtual reality (VR) environment used for military training, Virtual Battlespace 2 (VBS2), to create realistic avatar-avatar interactions and cooperative tasks. To control the virtual avatar, subjects use a MRI compatible Playstation 3 game controller, modified by removing all extraneous metal components and replacing any necessary ones with 3D printed plastic models. Control of both scanners’ operation is initiated by a VBS2 plugin to sync scanner time to the known time within the VR environment. Our modifications include:•Modification of game controller to be MRI compatible.•Design of VBS2 virtual environment for cooperative interactions.•Syncing two MRI machines for simultaneous recording. PMID:26150964
Force control of a tri-layer conducting polymer actuator using optimized fuzzy logic control
NASA Astrophysics Data System (ADS)
Itik, Mehmet; Sabetghadam, Mohammadreza; Alici, Gursel
2014-12-01
Conducting polymers actuators (CPAs) are potential candidates for replacing conventional actuators in various fields, such as robotics and biomedical engineering, due to their advantageous properties, which includes their low cost, light weight, low actuation voltage and biocompatibility. As these actuators are very suitable for use in micro-nano manipulation and in injection devices in which the magnitude of the force applied to the target is of crucial importance, the force generated by CPAs needs to be accurately controlled. In this paper, a fuzzy logic (FL) controller with a Mamdani inference system is designed to control the blocking force of a trilayer CPA with polypyrrole electrodes, which operates in air. The particle swarm optimization (PSO) method is employed to optimize the controller’s membership function parameters and therefore enhance the performance of the FL controller. An adaptive neuro-fuzzy inference system model, which can capture the nonlinear dynamics of the actuator, is utilized in the optimization process. The optimized Mamdani FL controller is then implemented on the CPA experimentally, and its performance is compared with a non-optimized fuzzy controller as well as with those obtained from a conventional PID controller. The results presented indicate that the blocking force at the tip of the CPA can be effectively controlled by the optimized FL controller, which shows excellent transient and steady state characteristics but increases the control voltage compared to the non-optimized fuzzy controllers.
Hill, K.
1988-06-01
The use of energy (calories) as the currency to be maximized per unit time in Optimal Foraging Models is considered in light of data on several foraging groups. Observations on the Ache, Cuiva, and Yora foragers suggest men do not attempt to maximize energetic return rates, but instead often concentration on acquiring meat resources which provide lower energetic returns. The possibility that this preference is due to the macronutrient composition of hunted and gathered foods is explored. Indifference curves are introduced as a means of modeling the tradeoff between two desirable commodities, meat (protein-lipid) and carbohydrate, and a specific indifference curve is derived using observed choices in five foraging situations. This curve is used to predict the amount of meat that Mbuti foragers will trade for carbohydrate, in an attempt to test the utility of the approach.
Optimal control for the active above-knee prosthesis.
Popović, D; Oğuztöreli, M N; Stein, R B
1991-01-01
Control of an active above-knee prosthesis has been simulated for a selected gait activity using a hierarchical closed-loop method. An extension of finite-state control, referred to as artificial reflex control, was adopted at the strategic level of control. At the actuator level of control an optimal tracking method, based on dynamic programming, is applied. This deals mainly with the actuator level of control, but considers the interaction of the leg dynamics and the switching effects of artificial reflex control. Optimal tracking at the actuator level of the above-knee prosthesis reduces the on-off effects of finite-state methods, such as artificial reflex control. The proposed method can also be used for the design of prosthetic elements. Specific attention is paid to the limited torque and power in the prosthetic joint actuator, which are imposed by the principle of self-containment in the artificial leg. The hierarchical structure, integrating artificial reflex control and optimal tracking, can be used in real time, as estimated from the number of computer operations required for the suggested method. PMID:2048773
Optimal control strategy for abnormal innate immune response.
Tan, Jinying; Zou, Xiufen
2015-01-01
Innate immune response plays an important role in control and clearance of pathogens following viral infection. However, in the majority of virus-infected individuals, the response is insufficient because viruses are known to use different evasion strategies to escape immune response. In this study, we use optimal control theory to investigate how to control the innate immune response. We present an optimal control model based on an ordinary-differential-equation system from a previous study, which investigated the dynamics and regulation of virus-triggered innate immune signaling pathways, and we prove the existence of a solution to the optimal control problem involving antiviral treatment or/and interferon therapy. We conduct numerical experiments to investigate the treatment effects of different control strategies through varying the cost function and control efficiency. The results show that a separate treatment, that is, only inhibiting viral replication (u1(t)) or enhancing interferon activity (u2(t)), has more advantages for controlling viral infection than a mixed treatment, that is, controlling both (u1(t)) and (u2(t)) simultaneously, including the smallest cost and operability. These findings would provide new insight for developing effective strategies for treatment of viral infectious diseases. PMID:25949271
A duality framework for stochastic optimal control of complex systems
Malikopoulos, Andreas A.
2016-01-01
In this study, we address the problem of minimizing the long-run expected average cost of a complex system consisting of interactive subsystems. We formulate a multiobjective optimization problem of the one-stage expected costs of the subsystems and provide a duality framework to prove that the control policy yielding the Pareto optimal solution minimizes the average cost criterion of the system. We provide the conditions of existence and a geometric interpretation of the solution. For practical situations having constraints consistent with those studied here, our results imply that the Pareto control policy may be of value when we seek to derivemore » online the optimal control policy in complex systems.« less
Optimization of microstructure during deformation processing using control theory principles
Venugopal, S.; Medina, E.A.; Malas, J.C. III; Medeiros, S.; Frazier, W.G.; Mullins, W.M.; Srinivasan, R.
1997-02-01
The development of optimal design and control methods for manufacturing processes is needed for effectively reducing part cost, improving part delivery schedules and producing specified part quality on a repeatable basis. A new strategy for systematically calculating near optimal control parameters for hot deformation processes for microstructural control is presented in this communication. This approach is based on modern control theory and involves developing state-space models from available material behavior and hot deformation process models. The control system design consists of two basic stages and analysis and optimization are critical in both stages. In the first stage, the kinetics of certain dynamic microstructural behavior and the intrinsic hot workability of the material are used, along with an appropriately chosen optimality criterion, to calculate optimum strain, strain-rate, and temperature trajectories for processing. A suitable process simulation model is then used in the second stage to calculate process control parameters, such as ram velocity, die profiles and billet temperature, which approximately achieve the strain, strain-rate, and temperate trajectories calculated in the first stage at selected areas of the workpiece. The validity of this approach has been demonstrated with an example on hot extrusion of steel.
Multidisciplinary optimization of controlled space structures with global sensitivity equations
NASA Technical Reports Server (NTRS)
Padula, Sharon L.; James, Benjamin B.; Graves, Philip C.; Woodard, Stanley E.
1991-01-01
A new method for the preliminary design of controlled space structures is presented. The method coordinates standard finite element structural analysis, multivariable controls, and nonlinear programming codes and allows simultaneous optimization of the structures and control systems of a spacecraft. Global sensitivity equations are a key feature of this method. The preliminary design of a generic geostationary platform is used to demonstrate the multidisciplinary optimization method. Fifteen design variables are used to optimize truss member sizes and feedback gain values. The goal is to reduce the total mass of the structure and the vibration control system while satisfying constraints on vibration decay rate. Incorporating the nonnegligible mass of actuators causes an essential coupling between structural design variables and control design variables. The solution of the demonstration problem is an important step toward a comprehensive preliminary design capability for structures and control systems. Use of global sensitivity equations helps solve optimization problems that have a large number of design variables and a high degree of coupling between disciplines.
A stochastic optimal feedforward and feedback control methodology for superagility
NASA Technical Reports Server (NTRS)
Halyo, Nesim; Direskeneli, Haldun; Taylor, Deborah B.
1992-01-01
A new control design methodology is developed: Stochastic Optimal Feedforward and Feedback Technology (SOFFT). Traditional design techniques optimize a single cost function (which expresses the design objectives) to obtain both the feedforward and feedback control laws. This approach places conflicting demands on the control law such as fast tracking versus noise atttenuation/disturbance rejection. In the SOFFT approach, two cost functions are defined. The feedforward control law is designed to optimize one cost function, the feedback optimizes the other. By separating the design objectives and decoupling the feedforward and feedback design processes, both objectives can be achieved fully. A new measure of command tracking performance, Z-plots, is also developed. By analyzing these plots at off-nominal conditions, the sensitivity or robustness of the system in tracking commands can be predicted. Z-plots provide an important tool for designing robust control systems. The Variable-Gain SOFFT methodology was used to design a flight control system for the F/A-18 aircraft. It is shown that SOFFT can be used to expand the operating regime and provide greater performance (flying/handling qualities) throughout the extended flight regime. This work was performed under the NASA SBIR program. ICS plans to market the software developed as a new module in its commercial CACSD software package: ACET.
Optimal periodic controller for formation flying on libration point orbits
NASA Astrophysics Data System (ADS)
Peng, Haijun; Zhao, Jun; Wu, Zhigang; Zhong, Wanxie
2011-09-01
An optimal periodic controller based on continuous low-thrust is proposed for the stabilization missions of spacecraft station-keeping and formation-keeping along periodic Libration point orbits of the Sun-Earth system. Additionally, a new numerical algorithm is proposed for solving the periodic Riccati differential equation in the design of the optimal periodic controller. Practical missions show that the optimal periodic controller (which is designed with the linear periodic time-varying equation of the relative dynamical model) overcomes the problems and limitations of the time-variant LQR controller. Furthermore, nonlinear numerical simulations are presented for the missions of a leader spacecraft station-keeping and three follower spacecraft formation-keeping. Numerical simulations show that the velocity increments for spacecraft control and relative position errors vary little with changes in the altitude of periodic orbits. In addition, the actual trajectories of the leader and the follower spacecraft track the periodic reference orbit with high accuracy under the perturbation of the eccentric nature of the Earth's orbit and the initial injection errors. In particular, the relative position errors obtained by the optimal periodic controller for spacecraft formation-keeping are all in the range of millimeters.
A multiple objective optimization approach to quality control
NASA Technical Reports Server (NTRS)
Seaman, Christopher Michael
1991-01-01
The use of product quality as the performance criteria for manufacturing system control is explored. The goal in manufacturing, for economic reasons, is to optimize product quality. The problem is that since quality is a rather nebulous product characteristic, there is seldom an analytic function that can be used as a measure. Therefore standard control approaches, such as optimal control, cannot readily be applied. A second problem with optimizing product quality is that it is typically measured along many dimensions: there are many apsects of quality which must be optimized simultaneously. Very often these different aspects are incommensurate and competing. The concept of optimality must now include accepting tradeoffs among the different quality characteristics. These problems are addressed using multiple objective optimization. It is shown that the quality control problem can be defined as a multiple objective optimization problem. A controller structure is defined using this as the basis. Then, an algorithm is presented which can be used by an operator to interactively find the best operating point. Essentially, the algorithm uses process data to provide the operator with two pieces of information: (1) if it is possible to simultaneously improve all quality criteria, then determine what changes to the process input or controller parameters should be made to do this; and (2) if it is not possible to improve all criteria, and the current operating point is not a desirable one, select a criteria in which a tradeoff should be made, and make input changes to improve all other criteria. The process is not operating at an optimal point in any sense if no tradeoff has to be made to move to a new operating point. This algorithm ensures that operating points are optimal in some sense and provides the operator with information about tradeoffs when seeking the best operating point. The multiobjective algorithm was implemented in two different injection molding scenarios
Quadratic Optimization in the Problems of Active Control of Sound
NASA Technical Reports Server (NTRS)
Loncaric, J.; Tsynkov, S. V.; Bushnell, Dennis M. (Technical Monitor)
2002-01-01
We analyze the problem of suppressing the unwanted component of a time-harmonic acoustic field (noise) on a predetermined region of interest. The suppression is rendered by active means, i.e., by introducing the additional acoustic sources called controls that generate the appropriate anti-sound. Previously, we have obtained general solutions for active controls in both continuous and discrete formulations of the problem. We have also obtained optimal solutions that minimize the overall absolute acoustic source strength of active control sources. These optimal solutions happen to be particular layers of monopoles on the perimeter of the protected region. Mathematically, minimization of acoustic source strength is equivalent to minimization in the sense of L(sub 1). By contrast. in the current paper we formulate and study optimization problems that involve quadratic functions of merit. Specifically, we minimize the L(sub 2) norm of the control sources, and we consider both the unconstrained and constrained minimization. The unconstrained L(sub 2) minimization is certainly the easiest problem to address numerically. On the other hand, the constrained approach allows one to analyze sophisticated geometries. In a special case, we call compare our finite-difference optimal solutions to the continuous optimal solutions obtained previously using a semi-analytic technique. We also show that the optima obtained in the sense of L(sub 2) differ drastically from those obtained in the sense of L(sub 1).
An inverter/controller subsystem optimized for photovoltaic applications
NASA Technical Reports Server (NTRS)
Pickrell, R. L.; Osullivan, G.; Merrill, W. C.
1978-01-01
Conversion of solar array dc power to ac power stimulated the specification, design, and simulation testing of an inverter/controller subsystem tailored to the photovoltaic power source characteristics. Optimization of the inverter/controller design is discussed as part of an overall photovoltaic power system designed for maximum energy extraction from the solar array. The special design requirements for the inverter/ controller include: a power system controller (PSC) to control continuously the solar array operating point at the maximum power level based on variable solar insolation and cell temperatures; and an inverter designed for high efficiency at rated load and low losses at light loadings to conserve energy.
Liang, Zhiming; Graham, Kenneth R
2015-10-01
Silver nanowires are attractive components for a number of materials and applications, including silver nanowire (AgNW)-polymer composites, electrically conductive coatings, and transparent electrodes. In this manuscript, the ability of thiols with hydrophobic to ionic end groups to bind to AgNW surfaces is investigated, followed by how the polarity of the surface modifying thiol influences the morphological and electrical properties of both AgNW/PEDOT:PSS blend films and pure AgNW networks. Utilizing surface modification of AgNWs with sodium 3-mercapto-1-propanesulfonate (MPS), morphologically homogeneous AgNW/PEDOT:PSS thin films with an order of magnitude lower sheet resistance at similar transmittance values than unmodified AgNWs are obtained with a one-step processing method. Brief optimization of MPS-AgNW/PEDOT:PSS blends yields a sheet resistance of 22.6 Ω/□ at 81.4% transmittance. PMID:26389535
Control design variable linking for optimization of structural/control systems
NASA Technical Reports Server (NTRS)
Jin, I. M.; Schmit, L. A.
1991-01-01
In this study a method is presented to integrate the design space of structural/control system optimization problems in the case of state feedback control. Conventional structural sizing variables and elements of the feedback gain matrix are both treated as strictly independent design variables in the optimization by extending design variable linking concepts to the control gains. Examples which involve a variety of behavior constraints, including dynamic transient response and control force limits, are effectively solved by using the method presented.
Torque-based optimal acceleration control for electric vehicle
NASA Astrophysics Data System (ADS)
Lu, Dongbin; Ouyang, Minggao
2014-03-01
The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin's maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle(EV) has not been reported. In this paper, the permanent magnet synchronous motor(PMSM) is controlled by the field oriented control(FOC) method and the electric drive system for the EV(including the PMSM, the inverter and the battery) is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming(DP). This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV's acceleration process and the analytical algorithm is easy to be implemented in real-time control.
On large-scale nonlinear programming techniques for solving optimal control problems
Faco, J.L.D.
1994-12-31
The formulation of decision problems by Optimal Control Theory allows the consideration of their dynamic structure and parameters estimation. This paper deals with techniques for choosing directions in the iterative solution of discrete-time optimal control problems. A unified formulation incorporates nonlinear performance criteria and dynamic equations, time delays, bounded state and control variables, free planning horizon and variable initial state vector. In general they are characterized by a large number of variables, mostly when arising from discretization of continuous-time optimal control or calculus of variations problems. In a GRG context the staircase structure of the jacobian matrix of the dynamic equations is exploited in the choice of basic and super basic variables and when changes of basis occur along the process. The search directions of the bound constrained nonlinear programming problem in the reduced space of the super basic variables are computed by large-scale NLP techniques. A modified Polak-Ribiere conjugate gradient method and a limited storage quasi-Newton BFGS method are analyzed and modifications to deal with the bounds on the variables are suggested based on projected gradient devices with specific linesearches. Some practical models are presented for electric generation planning and fishery management, and the application of the code GRECO - Gradient REduit pour la Commande Optimale - is discussed.
Time optimal feedback control of discrete systems with bounded inputs
NASA Technical Reports Server (NTRS)
Chen, Xin; Longman, Richard W.; Klein, George
1990-01-01
Deadbeat control theory gives a feedback solution to the time optimal control of discrete time systems. Experience has shown the results to be impractical because they ignore bounds on the actuator strength. This paper develops two algorithms for generating time optimal control in feedback form for discrete systems with bounded controls. The results are also applicable for generating recovery regions and the set of reachable states. For multiple control problems a method of generating sublayers is developed which decreases off-line and on-line computational effort. Two algorithms are presented with somewhat different computational and storage requirements. The algorithms are practical within certain dimension constraints, and are natural for implementation with parallel processing.
Genetic optimization of fuzzy fractional PD+I controllers.
Jesus, Isabel S; Barbosa, Ramiro S
2015-07-01
Fractional order calculus is a powerful emerging mathematical tool in science and engineering. There is currently an increasing interest in generalizing classical control theories and developing novel control strategies. The genetic algorithms (GA) are a stochastic search and optimization methods based on the reproduction processes found in biological systems, used for solving engineering problems. In the context of process control, the fuzzy logic usually means variables that are described by imprecise terms, and represented by quantities that are qualitative and vague. In this article we consider the development of an optimal fuzzy fractional PD+I controller in which the parameters are tuned by a GA. The performance of the proposed fuzzy fractional control is illustrated through some application examples. PMID:25661162
Optimizing Locomotion Controllers Using Biologically-Based Actuators and Objectives
Wang, Jack M.; Hamner, Samuel R.; Delp, Scott L.; Koltun, Vladlen
2015-01-01
We present a technique for automatically synthesizing walking and running controllers for physically-simulated 3D humanoid characters. The sagittal hip, knee, and ankle degrees-of-freedom are actuated using a set of eight Hill-type musculotendon models in each leg, with biologically-motivated control laws. The parameters of these control laws are set by an optimization procedure that satisfies a number of locomotion task terms while minimizing a biological model of metabolic energy expenditure. We show that the use of biologically-based actuators and objectives measurably increases the realism of gaits generated by locomotion controllers that operate without the use of motion capture data, and that metabolic energy expenditure provides a simple and unifying measurement of effort that can be used for both walking and running control optimization. PMID:26251560
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.
Optimal control of underactuated mechanical systems: A geometric approach
NASA Astrophysics Data System (ADS)
Colombo, Leonardo; Martín De Diego, David; Zuccalli, Marcela
2010-08-01
In this paper, we consider a geometric formalism for optimal control of underactuated mechanical systems. Our techniques are an adaptation of the classical Skinner and Rusk approach for the case of Lagrangian dynamics with higher-order constraints. We study a regular case where it is possible to establish a symplectic framework and, as a consequence, to obtain a unique vector field determining the dynamics of the optimal control problem. These developments will allow us to develop a new class of geometric integrators based on discrete variational calculus.
Optimal control of quaternion propagation errors in spacecraft navigation
NASA Technical Reports Server (NTRS)
Vathsal, S.
1986-01-01
Optimal control techniques are used to drive the numerical error (truncation, roundoff, commutation) in computing the quaternion vector to zero. The normalization of the quaternion is carried out by appropriate choice of a performance index, which can be optimized. The error equations are derived from Friedland's (1978) theoretical development, and a matrix Riccati equation results for the computation of the gain matrix. Simulation results show that a high precision of the order of 10 to the -12th can be obtained using this technique in meeting the q(T)q=1 constraint. The performance of the estimator in the presence of the feedback control that maintains the normalization, is studied.
Fuel optimal control of an experimental multi-mode system
NASA Technical Reports Server (NTRS)
Redmond, J.; Mayer, J. L.; Silverberg, L.
1992-01-01
In this paper, the dynamic characteristics associated with the fuel optimal control of a harmonic oscillator are utilized in the development of a near fuel optimal feedback control strategy for spacecraft vibration suppression. In this scheme, single level thrust actuators are governed by recursive computations of the standard deviations of displacement and velocity at the actuator's locations. The algorithm was tested on an experimental structure possessing a significant number of flexible body modes. The structure's response to both single and multiple mode excitation is presented.
Optimal placement of active elements in control augmented structural synthesis
NASA Technical Reports Server (NTRS)
Sepulveda, A. E.; Jin, I. M.; Schmit, L. A., Jr.
1992-01-01
A methodology for structural/control synthesis is presented in which the optimal location of active members is treated in terms of (0,1) variables. Structural member sizes, control gains and (0,1) placement variables are treated simultaneously as design variables. Optimization is carried out by generating and solving a sequence of explicit approximate problems using a branch and bound strategy. Intermediate design variable and intermediate response quantity concepts are used to enhance the quality of the approximate design problems. Numerical results for example problems are presented to illustrate the efficacy of the design procedure set forth.
Occupant-responsive optimal control of smart facade systems
NASA Astrophysics Data System (ADS)
Park, Cheol-Soo
Windows provide occupants with daylight, direct sunlight, visual contact with the outside and a feeling of openness. Windows enable the use of daylighting and offer occupants a outside view. Glazing may also cause a number of problems: undesired heat gain/loss in winter. An over-lit window can cause glare, which is another major complaint by occupants. Furthermore, cold or hot window surfaces induce asymmetric thermal radiation which can result in thermal discomfort. To reduce the potential problems of window systems, double skin facades and airflow window systems have been introduced in the 1970s. They typically contain interstitial louvers and ventilation openings. The current problem with double skin facades and airflow windows is that their operation requires adequate dynamic control to reach their expected performance. Many studies have recognized that only an optimal control enables these systems to truly act as active energy savers and indoor environment controllers. However, an adequate solution for this dynamic optimization problem has thus far not been developed. The primary objective of this study is to develop occupant responsive optimal control of smart facade systems. The control could be implemented as a smart controller that operates the motorized Venetian blind system and the opening ratio of ventilation openings. The objective of the control is to combine the benefits of large windows with low energy demands for heating and cooling, while keeping visual well-being and thermal comfort at an optimal level. The control uses a simulation model with an embedded optimization routine that allows occupant interaction via the Web. An occupant can access the smart controller from a standard browser and choose a pre-defined mode (energy saving mode, visual comfort mode, thermal comfort mode, default mode, nighttime mode) or set a preferred mode (user-override mode) by moving preference sliders on the screen. The most prominent feature of these systems is the
García-Millán, Eva; Koprivnik, Sandra; Otero-Espinar, Francisco Javier
2015-06-20
This paper proposes an approach to improve drug loading capacity and release properties of poly(2-hydroxyethyl methacrylate) (p(HEMA)) soft contact lenses based on the optimization of the hydrogel composition and microstructural modifications using water during the polymerization process. P(HEMA) based soft contact lenses were prepared by thermal or photopolymerization of 2-hydroxyethyl methacrylate (HEMA) solutions containing ethylene glycol di-methacrylate as crosslinker and different proportions of N-vinyl-2-pyrrolidone (NVP) or methacrylic acid (MA) as co-monomers. Transmittance, water uptake, swelling, microstructure, drug absorption isotherms and in vitro release were characterized using triamcinolone acetonide (TA) as model drug. Best drug loading ratios were obtained with lenses containing the highest amount (200 mM) of MA. Incorporation of 40% V/V of water during the polymerization increases the hydrogel porosity giving a better drug loading capacity. In vitro TA release kinetics shows that MA hydrogels released the drug significantly faster than NVP-hydrogels. Drug release was found to be diffusion controlled and kinetics was shown to be reproducible after consecutive drug loading/release processes. Results of p(HEMA) based soft contact lenses copolymerized with ethylene glycol dimethacrylate (EGDMA) and different co-monomers could be a good alternative to optimize the loading and ocular drug delivery of this corticosteroid drug. PMID:25891253
Stochastic optimal control of single neuron spike trains
NASA Astrophysics Data System (ADS)
Iolov, Alexandre; Ditlevsen, Susanne; Longtin, André
2014-08-01
Objective. External control of spike times in single neurons can reveal important information about a neuron's sub-threshold dynamics that lead to spiking, and has the potential to improve brain-machine interfaces and neural prostheses. The goal of this paper is the design of optimal electrical stimulation of a neuron to achieve a target spike train under the physiological constraint to not damage tissue. Approach. We pose a stochastic optimal control problem to precisely specify the spike times in a leaky integrate-and-fire (LIF) model of a neuron with noise assumed to be of intrinsic or synaptic origin. In particular, we allow for the noise to be of arbitrary intensity. The optimal control problem is solved using dynamic programming when the controller has access to the voltage (closed-loop control), and using a maximum principle for the transition density when the controller only has access to the spike times (open-loop control). Main results. We have developed a stochastic optimal control algorithm to obtain precise spike times. It is applicable in both the supra-threshold and sub-threshold regimes, under open-loop and closed-loop conditions and with an arbitrary noise intensity; the accuracy of control degrades with increasing intensity of the noise. Simulations show that our algorithms produce the desired results for the LIF model, but also for the case where the neuron dynamics are given by more complex models than the LIF model. This is illustrated explicitly using the Morris-Lecar spiking neuron model, for which an LIF approximation is first obtained from a spike sequence using a previously published method. We further show that a related control strategy based on the assumption that there is no noise performs poorly in comparison to our noise-based strategies. The algorithms are numerically intensive and may require efficiency refinements to achieve real-time control; in particular, the open-loop context is more numerically demanding than the closed
Automated design of multiphase space missions using hybrid optimal control
NASA Astrophysics Data System (ADS)
Chilan, Christian Miguel
A modern space mission is assembled from multiple phases or events such as impulsive maneuvers, coast arcs, thrust arcs and planetary flybys. Traditionally, a mission planner would resort to intuition and experience to develop a sequence of events for the multiphase mission and to find the space trajectory that minimizes propellant use by solving the associated continuous optimal control problem. This strategy, however, will most likely yield a sub-optimal solution, as the problem is sophisticated for several reasons. For example, the number of events in the optimal mission structure is not known a priori and the system equations of motion change depending on what event is current. In this work a framework for the automated design of multiphase space missions is presented using hybrid optimal control (HOC). The method developed uses two nested loops: an outer-loop that handles the discrete dynamics and finds the optimal mission structure in terms of the categorical variables, and an inner-loop that performs the optimization of the corresponding continuous-time dynamical system and obtains the required control history. Genetic algorithms (GA) and direct transcription with nonlinear programming (NLP) are introduced as methods of solution for the outer-loop and inner-loop problems, respectively. Automation of the inner-loop, continuous optimal control problem solver, required two new technologies. The first is a method for the automated construction of the NLP problems resulting from the use of a direct solver for systems with different structures, including different numbers of categorical events. The method assembles modules, consisting of parameters and constraints appropriate to each event, sequentially according to the given mission structure. The other new technology is for a robust initial guess generator required by the inner-loop NLP problem solver. Two new methods were developed for cases including low-thrust trajectories. The first method, based on GA
Optimization and Control of Cyber-Physical Vehicle Systems
Bradley, Justin M.; Atkins, Ella M.
2015-01-01
A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined. PMID:26378541
Optimization and Control of Cyber-Physical Vehicle Systems.
Bradley, Justin M; Atkins, Ella M
2015-01-01
A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined. PMID:26378541
Optimizing the lifetimes of phenoxonium cations derived from vitamin E via structural modifications.
Yue, Yanni; Novianti, Maria L; Tessensohn, Malcolm E; Hirao, Hajime; Webster, Richard D
2015-12-28
Systematic synthesis of a number of new phenolic compounds with structures similar to vitamin E led to the identification of several sterically hindered compounds that when electrochemically oxidised in acetonitrile in a -2e(-)/-H(+) process formed phenoxonium diamagnetic cations that were resistant to hydrolysis reactions. The reactivity of the phenoxonium ions was ascertained by performing cyclic voltammetric scans during the addition of carefully controlled quantities of water into acetonitrile solutions, with the data modelled using digital simulation techniques. PMID:26480893
Neural network based optimal control of HVAC&R systems
NASA Astrophysics Data System (ADS)
Ning, Min
Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) systems have wide applications in providing a desired indoor environment for different types of buildings. It is well acknowledged that 30%-40% of the total energy generated is consumed by buildings and HVAC&R systems alone account for more than 50% of the building energy consumption. Low operational efficiency especially under partial load conditions and poor control are part of reasons for such high energy consumption. To improve energy efficiency, HVAC&R systems should be properly operated to maintain a comfortable and healthy indoor environment under dynamic ambient and indoor conditions with the least energy consumption. This research focuses on the optimal operation of HVAC&R systems. The optimization problem is formulated and solved to find the optimal set points for the chilled water supply temperature, discharge air temperature and AHU (air handling unit) fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. The system model is modular in structure, which includes a water-cooled vapor compression chiller model and a two-zone VAV system model. A fuzzy-set based extended transformation approach is then applied to investigate the uncertainties of this model caused by uncertain parameters and the sensitivities of the control inputs with respect to the interested model outputs. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. In order to implement the optimal set points predicted by the
Using Chemicals to Optimize Conformance Control in Fractured Reservoirs
Seright, Randall S.; Liang, Jenn-Tai; Schrader, Richard; Hagstrom II, John; Liu, Jin; Wavrik, Kathryn
1999-09-27
This report describes work performed during the first year of the project, ''Using Chemicals to Optimize Conformance Control in Fractured Reservoirs.'' This research project has three objectives. The first objective is to develop a capability to predict and optimize the ability of gels to reduce permeability to water more than that to oil or gas. The second objective is to develop procedures for optimizing blocking agent placement in wells where hydraulic fractures cause channeling problems. The third objective is to develop procedures to optimize blocking agent placement in naturally fractured reservoirs. This research project consists of three tasks, each of which addresses one of the above objectives. Our work is directed at both injection wells and production wells and at vertical, horizontal, and highly deviated wells.
Optimization of methods for the genetic modification of human T cells.
Bilal, Mahmood Y; Vacaflores, Aldo; Houtman, Jon Cd
2015-11-01
CD4(+) T cells are not only critical in the fight against parasitic, bacterial and viral infections, but are also involved in many autoimmune and pathological disorders. Studies of protein function in human T cells are confined to techniques such as RNA interference (RNAi) owing to ethical reasons and relative simplicity of these methods. However, introduction of RNAi or genes into primary human T cells is often hampered by toxic effects from transfection or transduction methods that yield cell numbers inadequate for downstream assays. Additionally, the efficiency of recombinant DNA expression is frequently low because of multiple factors including efficacy of the method and strength of the targeting RNAs. Here, we describe detailed protocols that will aid in the study of primary human CD4(+) T cells. First, we describe a method for development of effective microRNA/shRNAs using available online algorithms. Second, we illustrate an optimized protocol for high efficacy retroviral or lentiviral transduction of human T-cell lines. Importantly, we demonstrate that activated primary human CD4(+) T cells can be transduced efficiently with lentiviruses, with a highly activated population of T cells receiving the largest number of copies of integrated DNA. We also illustrate a method for efficient lentiviral transduction of hard-to-transduce un-activated primary human CD4(+) T cells. These protocols will significantly assist in understanding the activation and function of human T cells and will ultimately aid in the development or improvement of current drugs that target human CD4(+) T cells. PMID:26027856
Optimization of a photovoltaic pumping system based on the optimal control theory
Betka, A.; Attali, A.
2010-07-15
This paper suggests how an optimal operation of a photovoltaic pumping system based on an induction motor driving a centrifugal pump can be realized. The optimization problem consists in maximizing the daily pumped water quantity via the optimization of the motor efficiency for every operation point. The proposed structure allows at the same time the minimization the machine losses, the field oriented control and the maximum power tracking of the photovoltaic array. This will be attained based on multi-input and multi-output optimal regulator theory. The effectiveness of the proposed algorithm is described by simulation and the obtained results are compared to those of a system working with a constant air gap flux. (author)
Lossless Convexification of Control Constraints for a Class of Nonlinear Optimal Control Problems
NASA Technical Reports Server (NTRS)
Blackmore, Lars; Acikmese, Behcet; Carson, John M.,III
2012-01-01
In this paper we consider a class of optimal control problems that have continuous-time nonlinear dynamics and nonconvex control constraints. We propose a convex relaxation of the nonconvex control constraints, and prove that the optimal solution to the relaxed problem is the globally optimal solution to the original problem with nonconvex control constraints. This lossless convexification enables a computationally simpler problem to be solved instead of the original problem. We demonstrate the approach in simulation with a planetary soft landing problem involving a nonlinear gravity field.
Optimization of Fuzzy Controller of Permanent Magnet Synchronous Motor
NASA Astrophysics Data System (ADS)
Yu, Kuang-Cheng; Hsu, Shou-Ping; Hung, Yung-Hsiang
Present study aims at discussing how to optimize the fuzzy controller of Permanent Magnet Synchronous Motor (PMSM). By reducing the influence of parameter changes of plant using Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) of Taguchi Method and Multi-Criteria Decision Making (MCDM), it shall be possible to improve robust characteristics of control system, thus promoting the output quality and performance of PMSM plant. Meanwhile, an analytical model for the parameters and output quality of fuzzy controllers was set up and optimal parameters were designed using Genetic Algorithm (GA). Generally speaking, PMSM controller has a long-lasting infrastructure without complex computation, of which the Small-The-Better (STB) output features of PMSM include: Overshoot, rise time and settling time. In previous design of controllers, only individual quality characteristics were considered without overall output design of multiple quality characteristics. By using a controller based on fuzzy logic method in cooperation with parameterization method of TOPSIS, this study intended to discuss how to ensure optimum output quality and performance (overshoot, rise time and settling time) under different noise factors (speeds and loads, etc.). With a PC-based infrastructure that combines PC-based motor controller system and Matlab/Simulink software for simulation process, it seeks to obtain optimum parameters of controllers and implement a PMSM fuzzy control system with vector control function. The computer simulation results have proved the validity and feasibility of entire infrastructure with possible desirable effects.
Quantum optimal control of photoelectron spectra and angular distributions
NASA Astrophysics Data System (ADS)
Goetz, R. Esteban; Karamatskou, Antonia; Santra, Robin; Koch, Christiane P.
2016-01-01
Photoelectron spectra and photoelectron angular distributions obtained in photoionization reveal important information on, e.g., charge transfer or hole coherence in the parent ion. Here we show that optimal control of the underlying quantum dynamics can be used to enhance desired features in the photoelectron spectra and angular distributions. To this end, we combine Krotov's method for optimal control theory with the time-dependent configuration interaction singles formalism and a splitting approach to calculate photoelectron spectra and angular distributions. The optimization target can account for specific desired properties in the photoelectron angular distribution alone, in the photoelectron spectrum, or in both. We demonstrate the method for hydrogen and then apply it to argon under strong XUV radiation, maximizing the difference of emission into the upper and lower hemispheres, in order to realize directed electron emission in the XUV regime.
AI approach to optimal var control with fuzzy reactive loads
Abdul-Rahman, K.H.; Shahidehpour, S.M.; Daneshdoost, M.
1995-02-01
This paper presents an artificial intelligence (AI) approach to the optimal reactive power (var) control problem. The method incorporates the reactive load uncertainty in optimizing the overall system performance. The artificial neural network (ANN) enhanced by fuzzy sets is used to determine the memberships of control variables corresponding to the given load values. A power flow solution will determine the corresponding state of the system. Since the resulting system state may not be feasible in real-time, a heuristic method based on the application of sensitivities in expert system is employed to refine the solution with minimum adjustments of control variables. Test cases and numerical results demonstrate the applicability of the proposed approach. Simplicity, processing speed and ability to model load uncertainties make this approach a viable option for on-line var control.
Improved Sensitivity Relations in State Constrained Optimal Control
Bettiol, Piernicola; Frankowska, Hélène; Vinter, Richard B.
2015-04-15
Sensitivity relations in optimal control provide an interpretation of the costate trajectory and the Hamiltonian, evaluated along an optimal trajectory, in terms of gradients of the value function. While sensitivity relations are a straightforward consequence of standard transversality conditions for state constraint free optimal control problems formulated in terms of control-dependent differential equations with smooth data, their verification for problems with either pathwise state constraints, nonsmooth data, or for problems where the dynamic constraint takes the form of a differential inclusion, requires careful analysis. In this paper we establish validity of both ‘full’ and ‘partial’ sensitivity relations for an adjoint state of the maximum principle, for optimal control problems with pathwise state constraints, where the underlying control system is described by a differential inclusion. The partial sensitivity relation interprets the costate in terms of partial Clarke subgradients of the value function with respect to the state variable, while the full sensitivity relation interprets the couple, comprising the costate and Hamiltonian, as the Clarke subgradient of the value function with respect to both time and state variables. These relations are distinct because, for nonsmooth data, the partial Clarke subdifferential does not coincide with the projection of the (full) Clarke subdifferential on the relevant coordinate space. We show for the first time (even for problems without state constraints) that a costate trajectory can be chosen to satisfy the partial and full sensitivity relations simultaneously. The partial sensitivity relation in this paper is new for state constraint problems, while the full sensitivity relation improves on earlier results in the literature (for optimal control problems formulated in terms of Lipschitz continuous multifunctions), because a less restrictive inward pointing hypothesis is invoked in the proof, and because
Health benefit modelling and optimization of vehicular pollution control strategies
NASA Astrophysics Data System (ADS)
Sonawane, Nayan V.; Patil, Rashmi S.; Sethi, Virendra
2012-12-01
This study asserts that the evaluation of pollution reduction strategies should be approached on the basis of health benefits. The framework presented could be used for decision making on the basis of cost effectiveness when the strategies are applied concurrently. Several vehicular pollution control strategies have been proposed in literature for effective management of urban air pollution. The effectiveness of these strategies has been mostly studied as a one at a time approach on the basis of change in pollution concentration. The adequacy and practicality of such an approach is studied in the present work. Also, the assessment of respective benefits of these strategies has been carried out when they are implemented simultaneously. An integrated model has been developed which can be used as a tool for optimal prioritization of various pollution management strategies. The model estimates health benefits associated with specific control strategies. ISC-AERMOD View has been used to provide the cause-effect relation between control options and change in ambient air quality. BenMAP, developed by U.S. EPA, has been applied for estimation of health and economic benefits associated with various management strategies. Valuation of health benefits has been done for impact indicators of premature mortality, hospital admissions and respiratory syndrome. An optimization model has been developed to maximize overall social benefits with determination of optimized percentage implementations for multiple strategies. The model has been applied for sub-urban region of Mumbai city for vehicular sector. Several control scenarios have been considered like revised emission standards, electric, CNG, LPG and hybrid vehicles. Reduction in concentration and resultant health benefits for the pollutants CO, NOx and particulate matter are estimated for different control scenarios. Finally, an optimization model has been applied to determine optimized percentage implementation of specific
Identification problem for a wave equation via optimal control
Lenhart, S.; Liang, M.; Protopopescu, V.
1998-11-01
The authors approximate an identification problem by applying optimal control techniques to a Tikhonov`s regularization. They seek to identify the dispersive coefficient in a wave equation and allow for the case of error or uncertainty in the observations used for the identification.
Quasivelocities and Optimal Control for underactuated Mechanical Systems
Colombo, L.; Martin de Diego, D.
2010-07-28
This paper is concerned with the application of the theory of quasivelocities for optimal control for underactuated mechanical systems. Using this theory, we convert the original problem in a variational second-order lagrangian system subjected to constraints. The equations of motion are geometrically derived using an adaptation of the classical Skinner and Rusk formalism.
Quasivelocities and Optimal Control for underactuated Mechanical Systems
NASA Astrophysics Data System (ADS)
Colombo, L.; de Diego, D. Martín
2010-07-01
This paper is concerned with the application of the theory of quasivelocities for optimal control for underactuated mechanical systems. Using this theory, we convert the original problem in a variational second-order lagrangian system subjected to constraints. The equations of motion are geometrically derived using an adaptation of the classical Skinner and Rusk formalism.
An historical survey of computational methods in optimal control.
NASA Technical Reports Server (NTRS)
Polak, E.
1973-01-01
Review of some of the salient theoretical developments in the specific area of optimal control algorithms. The first algorithms for optimal control were aimed at unconstrained problems and were derived by using first- and second-variation methods of the calculus of variations. These methods have subsequently been recognized as gradient, Newton-Raphson, or Gauss-Newton methods in function space. A much more recent addition to the arsenal of unconstrained optimal control algorithms are several variations of conjugate-gradient methods. At first, constrained optimal control problems could only be solved by exterior penalty function methods. Later algorithms specifically designed for constrained problems have appeared. Among these are methods for solving the unconstrained linear quadratic regulator problem, as well as certain constrained minimum-time and minimum-energy problems. Differential-dynamic programming was developed from dynamic programming considerations. The conditional-gradient method, the gradient-projection method, and a couple of feasible directions methods were obtained as extensions or adaptations of related algorithms for finite-dimensional problems. Finally, the so-called epsilon-methods combine the Ritz method with penalty function techniques.
Discover for Yourself: An Optimal Control Model in Insect Colonies
ERIC Educational Resources Information Center
Winkel, Brian
2013-01-01
We describe the enlightening path of self-discovery afforded to the teacher of undergraduate mathematics. This is demonstrated as we find and develop background material on an application of optimal control theory to model the evolutionary strategy of an insect colony to produce the maximum number of queen or reproducer insects in the colony at…
Time optimal control of pendulum-cart system
Turnau, A.; Korytowski, A.
1994-12-31
We consider the synthesis of time optimal control which steers a pendulum hinged to a cart to a given state (e.g., the upright position), starting from arbitrary initial conditions. The control of the pendulum can system has attracted attention of many authors because of its relatively simple structure and at the same time, nontrivial nonlinearity. Various heuristic approaches combined with 1q stabilization in the vicinity of the target state were used to swing the pendulum up to the upright position and to keep it there. However, time-optimality was not achieved. We construct the time optimal control using a sequence of fixed horizon problems in which the norms of terminal states are minimized. The problems with fixed horizons are solved numerically by means of gradient optimization, with gradients determined from the solution of adjoint equations. Due to embedding the synthesis algorithms in the Matlab - Simulink environment, it is possible to track and visualize the control process as well as the results of simulation experiments.
The Relationship between Pupil Control Ideology and Academic Optimism
ERIC Educational Resources Information Center
Gilbert, Michael J.
2012-01-01
This study investigates the relationship between pupil control ideology and academic optimism. Information was generated through responses to a questionnaire emailed to teachers in two school districts in Central New Jersey. The districts were categorized GH, as determined by the State's district factor grouping. The research concludes that…
A Connection between Singular Stochastic Control and Optimal Stopping
Espen Benth, Fred Reikvam, Kristin
2003-12-15
We show that the value function of a singular stochastic control problem is equal to the integral of the value function of an associated optimal stopping problem. The connection is proved for a general class of diffusions using the method of viscosity solutions.
Optimizing a mobile robot control system using GPU acceleration
NASA Astrophysics Data System (ADS)
Tuck, Nat; McGuinness, Michael; Martin, Fred
2012-01-01
This paper describes our attempt to optimize a robot control program for the Intelligent Ground Vehicle Competition (IGVC) by running computationally intensive portions of the system on a commodity graphics processing unit (GPU). The IGVC Autonomous Challenge requires a control program that performs a number of different computationally intensive tasks ranging from computer vision to path planning. For the 2011 competition our Robot Operating System (ROS) based control system would not run comfortably on the multicore CPU on our custom robot platform. The process of profiling the ROS control program and selecting appropriate modules for porting to run on a GPU is described. A GPU-targeting compiler, Bacon, is used to speed up development and help optimize the ported modules. The impact of the ported modules on overall performance is discussed. We conclude that GPU optimization can free a significant amount of CPU resources with minimal effort for expensive user-written code, but that replacing heavily-optimized library functions is more difficult, and a much less efficient use of time.
Optimal and adaptive control in canine postural regulation.
Schuster, D; Talbott, R E
1980-07-01
For analytic purposes, dogs trained to stand quietly on an oscillating platform can be likened to a fixed-length inverted pendulum with a point mass. Describing function analysis permitted derivation of torque and error values as functions of phase and gain relative to platform movement. A phase criterion was determined for minimization of either control torque at a given error amplitude or error at a given control torque amplitude. Describing functions for dogs with and without vision approached optimal phase. Stretch reflex control involving proportional-plus-rate feedback is not sufficient to account for the approach to optimal phase. Blindfolded labyrinthectomized dogs did not exhibit optimal behavior and the phase constraint for stretch reflex control was satisfied at most frequencies. The observed behavior is best accounted for by a model involving both otolith and visual feedforward (pursuit-precognitive) control processes. Reductions in phase lag by blindfolded dogs during the first few cycles of platform motion provide evidence of adaptive control. PMID:7396044
Combining dynamical decoupling with optimal control for improved QIP.
Grace, Matthew D.; Carroll, Malcolm S.; Dominy, Jason; Witzel, Wayne
2010-03-01
Constructing high-fidelity control pulses that are robust to control and system/environment fluctuations is a crucial objective for quantum information processing (QIP). We combine dynamical decoupling (DD) with optimal control (OC) to identify control pulses that achieve this objective numerically. Previous DD work has shown that general errors up to (but not including) third order can be removed from {pi}- and {pi}/2-pulses without concatenation. By systematically integrating DD and OC, we are able to increase pulse fidelity beyond this limit. Our hybrid method of quantum control incorporates a newly-developed algorithm for robust OC, providing a nested DD-OC approach to generate robust controls. Motivated by solid-state QIP, we also incorporate relevant experimental constraints into this DD-OC formalism. To demonstrate the advantage of our approach, the resulting quantum controls are compared to previous DD results in open and uncertain model systems.
Concurrently adjusting interrelated control parameters to achieve optimal engine performance
Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna
2015-12-01
Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.
FEM Optimization of Spin Forming Using a Fuzzy Control Algorithm
NASA Astrophysics Data System (ADS)
Yoshihara, S.; Ray, P.; MacDonald, B. J.; Koyama, H.; Kawahara, M.
2004-06-01
Finite element (FE) simulation of the manufacturing of a conical nosing such as a pressure vessel from circular tubes, using the spin forming method, was performed on the commercially available software package, ANSYS/LS-DYNA3D. The finite element method (FEM) provides a powerful tool for evaluating the potential to form the pressure vessel with proposed modifications to the process. The use of fuzzy logic inference as a control system to achieve the designed shape of the pressure vessel was investigated using the FEM. The path of the roller as a process parameter was decided by the fuzzy inference control algorithm from information of the result of deformation of each element respectively. The fuzzy control algorithm investigated was validated from the results of the production process time and the deformed shape using FE simulation.
Control of plant cell differentiation by histone modification and DNA methylation.
Ikeuchi, Momoko; Iwase, Akira; Sugimoto, Keiko
2015-12-01
How cells differentiate and acquire diverse arrays of determined states in multicellular organisms is a fundamental and yet unanswered question in biology. Molecular genetic studies over the last few decades have identified many transcriptional regulators that activate or repress gene expression to promote cell differentiation in plant development. What has recently emerged as an additional important regulatory layer is the control at the epigenetic level by which locus-specific DNA methylation and histone modification alter the chromatin state and limit the expression of key developmental regulators to specific windows of time and space. Accumulating evidence suggests that histone acetylation is commonly linked with active transcription and this mechanism is adopted to control sequential progression of cell differentiation. Histone H3 trimethylation at lysine 27 and DNA methylation are both associated with gene repression, and these mechanisms are often utilised to promote and/or maintain the differentiated status of plant cells. PMID:26454697
NASA Technical Reports Server (NTRS)
Bole, Brian; Goebel, Kai; Vachtsevanos, George
2012-01-01
This paper introduces a novel Markov process formulation of stochastic fault growth modeling, in order to facilitate the development and analysis of prognostics-based control adaptation. A metric representing the relative deviation between the nominal output of a system and the net output that is actually enacted by an implemented prognostics-based control routine, will be used to define the action space of the formulated Markov process. The state space of the Markov process will be defined in terms of an abstracted metric representing the relative health remaining in each of the system s components. The proposed formulation of component fault dynamics will conveniently relate feasible system output performance modifications to predictions of future component health deterioration.
The optimal control frequency response problem in manual control. [of manned aircraft systems
NASA Technical Reports Server (NTRS)
Harrington, W. W.
1977-01-01
An optimal control frequency response problem is defined within the context of the optimal pilot model. The problem is designed to specify pilot model control frequencies reflective of important aircraft system properties, such as control feel system dynamics, airframe dynamics, and gust environment, as well as man machine properties, such as task and attention allocation. This is accomplished by determining a bounded set of control frequencies which minimize the total control cost. The bounds are given by zero and the neuromuscular control frequency response for each control actuator. This approach is fully adaptive, i.e., does not depend upon user entered estimates. An algorithm is developed to solve this optimal control frequency response problem. The algorithm is then applied to an attitude hold task for a bare airframe fighter aircraft case with interesting dynamic properties.
Optimally tuned vibration absorbers to control sound transmission
NASA Astrophysics Data System (ADS)
Grissom, Michael; Belegundu, Ashok; Koopmann, Gary
2002-05-01
A design optimization method is proposed for controlling broadband vibration of a structure and it concomitant acoustic radiation using multiple-tuned absorbers. A computationally efficient model of a structure is developed and coupled with a nonlinear optimization search algorithm. The eigenvectors of the original structure are used as repeated basis functions in the analysis of the structural dynamic re-analysis problem. The re-analysis time for acoustic power computations is reduced by calculating and storing modal radiation resistance matrices at discrete frequencies. The matrices are then interpolated within the optimization loop for eigenvalues that fall between stored frequencies. The method is demonstrated by applying multiple-tuned vibration absorbers to an acoustically-excited composite panel. The absorber parameters are optimized with an objective of maximizing the panel's sound power transmission loss. It is shown that in some cases the optimal solution includes vibration absorbers that are tuned very closely in frequency, thus acting effectively as a broadband vibration absorber (BBVA). The numerical model and design optimization method are validated experimentally, and the BBVA is found to be an effective noise abatement tool.
Multi Objective Controller Design for Linear System via Optimal Interpolation
NASA Technical Reports Server (NTRS)
Ozbay, Hitay
1996-01-01
We propose a methodology for the design of a controller which satisfies a set of closed-loop objectives simultaneously. The set of objectives consists of: (1) pole placement, (2) decoupled command tracking of step inputs at steady-state, and (3) minimization of step response transients with respect to envelope specifications. We first obtain a characterization of all controllers placing the closed-loop poles in a prescribed region of the complex plane. In this characterization, the free parameter matrix Q(s) is to be determined to attain objectives (2) and (3). Objective (2) is expressed as determining a Pareto optimal solution to a vector valued optimization problem. The solution of this problem is obtained by transforming it to a scalar convex optimization problem. This solution determines Q(O) and the remaining freedom in choosing Q(s) is used to satisfy objective (3). We write Q(s) = (l/v(s))bar-Q(s) for a prescribed polynomial v(s). Bar-Q(s) is a polynomial matrix which is arbitrary except that Q(O) and the order of bar-Q(s) are fixed. Obeying these constraints bar-Q(s) is now to be 'shaped' to minimize the step response characteristics of specific input/output pairs according to the maximum envelope violations. This problem is expressed as a vector valued optimization problem using the concept of Pareto optimality. We then investigate a scalar optimization problem associated with this vector valued problem and show that it is convex. The organization of the report is as follows. The next section includes some definitions and preliminary lemmas. We then give the problem statement which is followed by a section including a detailed development of the design procedure. We then consider an aircraft control example. The last section gives some concluding remarks. The Appendix includes the proofs of technical lemmas, printouts of computer programs, and figures.
Baliban, Richard C.; DiMaggio, Peter A.; Plazas-Mayorca, Mariana D.; Young, Nicolas L.; Garcia, Benjamin A.; Floudas, Christodoulos A.
2010-01-01
A novel algorithm, PILOT_PTM, has been developed for the untargeted identification of post-translational modifications (PTMs) on a template sequence. The algorithm consists of an analysis of an MS/MS spectrum via an integer linear optimization model to output a rank-ordered list of PTMs that best match the experimental data. Each MS/MS spectrum is analyzed by a preprocessing algorithm to reduce spectral noise and label potential complimentary, offset, isotope, and multiply charged peaks. Postprocessing of the rank-ordered list from the integer linear optimization model will resolve fragment mass errors and will reorder the list of PTMs based on the cross-correlation between the experimental and theoretical MS/MS spectrum. PILOT_PTM is instrument-independent, capable of handling multiple fragmentation technologies, and can address the universe of PTMs for every amino acid on the template sequence. The various features of PILOT_PTM are presented, and it is tested on several modified and unmodified data sets including chemically synthesized phosphopeptides, histone H3-(1–50) polypeptides, histone H3-(1–50) tryptic fragments, and peptides generated from proteins extracted from chromatin-enriched fractions. The data sets consist of spectra derived from fragmentation via collision-induced dissociation, electron transfer dissociation, and electron capture dissociation. The capability of PILOT_PTM is then benchmarked using five state-of-the-art methods, InsPecT, Virtual Expert Mass Spectrometrist (VEMS), Modi, Mascot, and X!Tandem. PILOT_PTM demonstrates superior accuracy on both the small and large scale proteome experiments. A protocol is finally developed for the analysis of a complete LC-MS/MS scan using template sequences generated from SEQUEST and is demonstrated on over 270,000 MS/MS spectra collected from a total chromatin digest. PMID:20103568
NASA Technical Reports Server (NTRS)
Newson, J. R.
1979-01-01
The results of optimal control theory are used to synthesize a feedback filter. The feedback filter is used to force the output of the filtered frequency response to match that of a desired optimal frequency response over a finite frequency range. This matching is accomplished by employing a nonlinear programing algorithm to search for the coefficients of the feedback filter that minimize the error between the optimal frequency response and the filtered frequency response. The method is applied to the synthesis of an active flutter-suppression control law for an aeroelastic wind-tunnel model. It is shown that the resulting control law suppresses flutter over a wide range of subsonic Mach numbers. This is a promising method for synthesizing practical control laws using the results of optimal control theory.
Optimal control in a model of malaria with differential susceptibility
NASA Astrophysics Data System (ADS)
Hincapié, Doracelly; Ospina, Juan
2014-06-01
A malaria model with differential susceptibility is analyzed using the optimal control technique. In the model the human population is classified as susceptible, infected and recovered. Susceptibility is assumed dependent on genetic, physiological, or social characteristics that vary between individuals. The model is described by a system of differential equations that relate the human and vector populations, so that the infection is transmitted to humans by vectors, and the infection is transmitted to vectors by humans. The model considered is analyzed using the optimal control method when the control consists in using of insecticide-treated nets and educational campaigns; and the optimality criterion is to minimize the number of infected humans, while keeping the cost as low as is possible. One first goal is to determine the effects of differential susceptibility in the proposed control mechanism; and the second goal is to determine the algebraic form of the basic reproductive number of the model. All computations are performed using computer algebra, specifically Maple. It is claimed that the analytical results obtained are important for the design and implementation of control measures for malaria. It is suggested some future investigations such as the application of the method to other vector-borne diseases such as dengue or yellow fever; and also it is suggested the possible application of free software of computer algebra like Maxima.
Optimal Load Control via Frequency Measurement and Neighborhood Area Communication
Zhao, CH; Topcu, U; Low, SH
2013-11-01
We propose a decentralized optimal load control scheme that provides contingency reserve in the presence of sudden generation drop. The scheme takes advantage of flexibility of frequency responsive loads and neighborhood area communication to solve an optimal load control problem that balances load and generation while minimizing end-use disutility of participating in load control. Local frequency measurements enable individual loads to estimate the total mismatch between load and generation. Neighborhood area communication helps mitigate effects of inconsistencies in the local estimates due to frequency measurement noise. Case studies show that the proposed scheme can balance load with generation and restore the frequency within seconds of time after a generation drop, even when the loads use a highly simplified power system model in their algorithms. We also investigate tradeoffs between the amount of communication and the performance of the proposed scheme through simulation-based experiments.
Optimal control of Formula One car energy recovery systems
NASA Astrophysics Data System (ADS)
Limebeer, D. J. N.; Perantoni, G.; Rao, A. V.
2014-10-01
The utility of orthogonal collocation methods in the solution of optimal control problems relating to Formula One racing is demonstrated. These methods can be used to optimise driver controls such as the steering, braking and throttle usage, and to optimise vehicle parameters such as the aerodynamic down force and mass distributions. Of particular interest is the optimal usage of energy recovery systems (ERSs). Contemporary kinetic energy recovery systems are studied and compared with future hybrid kinetic and thermal/heat ERSs known as ERS-K and ERS-H, respectively. It is demonstrated that these systems, when properly controlled, can produce contemporary lap time using approximately two-thirds of the fuel required by earlier generation (2013 and prior) vehicles.
A forward method for optimal stochastic nonlinear and adaptive control
NASA Technical Reports Server (NTRS)
Bayard, David S.
1988-01-01
A computational approach is taken to solve the optimal nonlinear stochastic control problem. The approach is to systematically solve the stochastic dynamic programming equations forward in time, using a nested stochastic approximation technique. Although computationally intensive, this provides a straightforward numerical solution for this class of problems and provides an alternative to the usual dimensionality problem associated with solving the dynamic programming equations backward in time. It is shown that the cost degrades monotonically as the complexity of the algorithm is reduced. This provides a strategy for suboptimal control with clear performance/computation tradeoffs. A numerical study focusing on a generic optimal stochastic adaptive control example is included to demonstrate the feasibility of the method.
Optimal control of systems with capacity: Related noises
NASA Technical Reports Server (NTRS)
Ruan, Milfang; Choudhury, Ajit K.
1991-01-01
In the ordinary theory of optimal control (LQR and Kalman filter), the variances of the actuators and the sensors are assumed to be known (not related to the capacities of the devices). This assumption is not true in practice. Generally, a device with greater capacity to exert actuating forces and a sensor capable of sensing greater sensing range will generate noise of greater power spectral density. When the ordinary theory of optimal control is used to estimate the errors of the outputs in such cases it will lead to faulty results, because the capacities of such devices are unknown before the system is designed. The performance of the system designed by the ordinary theory will not be optimal as the variances of the sensors and the actuators are neither known nor constant. The interaction between the control system and structure could be serious because the ordinary method will lead to greater feedback (Kalman gain) matrices. Methods which can optimize the performance of systems when noises of the actuators and the sensors are related to their capacities are developed. These methods will result in smaller feedback (Kalman gain) matrix.
Solving inverse problems of identification type by optimal control methods
Lenhart, S.; Protopopescu, V.; Yong, J.
1997-05-01
Inverse problems of identification type for nonlinear equations are considered within the framework of optimal control theory. The rigorous solution of any particular problem depends on the functional setting, type of equation, and unknown quantity (or quantities) to be determined. Here we present only the general articulations of the formalism. Compared to classical regularization methods (e.g. Tikhonov coupled with optimization schemes), our approach presents several advantages, namely: (i) a systematic procedure to solve inverse problems of identification type; (ii) an explicit expression for the approximations of the solution; and (iii) a convenient numerical solution of these approximations. {copyright} {ital 1997 American Institute of Physics.}
Solving inverse problems of identification type by optimal control methods
Lenhart, S.; Protopopescu, V.; Jiongmin Yong
1997-06-01
Inverse problems of identification type for nonlinear equations are considered within the framework of optimal control theory. The rigorous solution of any particular problem depends on the functional setting, type of equation, and unknown quantity (or quantities) to be determined. Here the authors present only the general articulations of the formalism. Compared to classical regularization methods (e.g. Tikhonov coupled with optimization schemes), their approach presents several advantages, namely: (i) a systematic procedure to solve inverse problems of identification type; (ii) an explicit expression for the approximations of the solution; and (iii) a convenient numerical solution of these approximations.
Optimal control for Rydberg quantum technology building blocks
NASA Astrophysics Data System (ADS)
Müller, Matthias M.; Pichler, Thomas; Montangero, Simone; Calarco, Tommaso
2016-04-01
We consider a platform for quantum technology based on Rydberg atoms in optical lattices where each atom encodes one qubit of information and external lasers can manipulate their state. We demonstrate how optimal control theory enables the functioning of two specific building blocks on this platform: We engineer an optimal protocol to perform a two-qubit phase gate and to transfer the information within the lattice among specific sites. These two elementary operations allow to design very general operations like storage of atoms and entanglement purification as, for example, needed for quantum repeaters.
The controlled growth method - A tool for structural optimization
NASA Technical Reports Server (NTRS)
Hajela, P.; Sobieszczanski-Sobieski, J.
1981-01-01
An adaptive design variable linking scheme in a NLP based optimization algorithm is proposed and evaluated for feasibility of application. The present scheme, based on an intuitive effectiveness measure for each variable, differs from existing methodology in that a single dominant variable controls the growth of all others in a prescribed optimization cycle. The proposed method is implemented for truss assemblies and a wing box structure for stress, displacement and frequency constraints. Substantial reduction in computational time, even more so for structures under multiple load conditions, coupled with a minimal accompanying loss in accuracy, vindicates the algorithm.
NASA Technical Reports Server (NTRS)
Williams, David E.; Spector Lawrence N.
2010-01-01
Node 1 (Unity) flew to International Space Station (ISS) on Flight 2A. Node 1 was the first module of the United States On-Orbit Segment (USOS) launched to ISS. The Node 1 ISS Environmental Control and Life Support (ECLS) design featured limited ECLS capability. The main purpose of Node 1 was to provide internal storage by providing four stowage rack locations within the module and to allow docking of multiple modules and a truss segment to it. The ECLS subsystems inside Node 1 were routed through the element prior to launch to allow for easy integration of the attached future elements, particularly the Habitation Module which was planned to be located at the nadir docking port of Node 1. After Node I was on-orbit, the Program decided not to launch the Habitation Module and instead, to replace it with Node 3 (Tranquility). In 2007, the Program became concerned with a potential Russian docking port approach issue for the Russian FGB nadir docking port after Node 3 is attached to Node 1. To solve this concern the Program decided to relocate Node 3 from Node I nadir to Node 1 port. To support the movement of Node 3 the Program decided to build a modification kit for Node 1, an on-orbit feedthrough leak test device, and new vestibule jumpers to support the ECLS part of the relocation. This paper provides a design overview of the modification kit for Node 1, a summary of the Node 1 ECLS re-verification to support the Node 3 relocation from Node 1 nadir to Node 1 port, and a status of the ECLS modification kit installation into Node 1.
NASA Technical Reports Server (NTRS)
Williams, David E.; Spector, Lawrence N.
2009-01-01
Node 1 (Unity) flew to International Space Station (ISS) on Flight 2A. Node 1 was the first module of the United States On-Orbit Segment (USOS) launched to ISS. The Node 1 ISS Environmental Control and Life Support (ECLS) design featured limited ECLS capability. The main purpose of Node 1 was to provide internal storage by providing four stowage rack locations within the module and to allow docking of multiple modules and a truss segment to it. The ECLS subsystems inside Node 1 were routed through the element prior to launch to allow for easy integration of the attached future elements, particularly the Habitation Module which was planned to be located at the nadir docking port of Node 1. After Node 1 was on-orbit, the Program decided not to launch the Habitation Module and instead, to replace it with Node 3 (Tranquility). In 2007, the Program became concerned with a potential Russian docking port approach issue for the Russian FGB nadir docking port after Node 3 is attached to Node 1. To solve this concern the Program decided to relocate Node 3 from Node 1 nadir to Node 1 port. To support the movement of Node 3 the Program decided to build a modification kit for Node 1, an on-orbit feedthrough leak test device, and new vestibule jumpers to support the ECLS part of the relocation. This paper provides a design overview of the modification kit, a summary of the Node 1 ECLS re-verification to support the Node 3 relocation from Node 1 nadir to Node 1 port, and a status of the ECLS modification kit installation into Node 1.
Multiobjective Optimization of Low-Energy Trajectories Using Optimal Control on Dynamical Channels
NASA Technical Reports Server (NTRS)
Coffee, Thomas M.; Anderson, Rodney L.; Lo, Martin W.
2011-01-01
We introduce a computational method to design efficient low-energy trajectories by extracting initial solutions from dynamical channels formed by invariant manifolds, and improving these solutions through variational optimal control. We consider trajectories connecting two unstable periodic orbits in the circular restricted 3-body problem (CR3BP). Our method leverages dynamical channels to generate a range of solutions, and approximates the areto front for impulse and time of flight through a multiobjective optimization of these solutions based on primer vector theory. We demonstrate the application of our method to a libration orbit transfer in the Earth-Moon system.
Control and optimization system and method for chemical looping processes
Lou, Xinsheng; Joshi, Abhinaya; Lei, Hao
2014-06-24
A control system for optimizing a chemical loop system includes one or more sensors for measuring one or more parameters in a chemical loop. The sensors are disposed on or in a conduit positioned in the chemical loop. The sensors generate one or more data signals representative of an amount of solids in the conduit. The control system includes a data acquisition system in communication with the sensors and a controller in communication with the data acquisition system. The data acquisition system receives the data signals and the controller generates the control signals. The controller is in communication with one or more valves positioned in the chemical loop. The valves are configured to regulate a flow of the solids through the chemical loop.
Control and optimization system and method for chemical looping processes
Lou, Xinsheng; Joshi, Abhinaya; Lei, Hao
2015-02-17
A control system for optimizing a chemical loop system includes one or more sensors for measuring one or more parameters in a chemical loop. The sensors are disposed on or in a conduit positioned in the chemical loop. The sensors generate one or more data signals representative of an amount of solids in the conduit. The control system includes a data acquisition system in communication with the sensors and a controller in communication with the data acquisition system. The data acquisition system receives the data signals and the controller generates the control signals. The controller is in communication with one or more valves positioned in the chemical loop. The valves are configured to regulate a flow of the solids through the chemical loop.
An inverter/controller subsystem optimized for photovoltaic applications
NASA Technical Reports Server (NTRS)
Pickrell, R. L.; Merrill, W. C.; Osullivan, G.
1978-01-01
Conversion of solar array dc power to ac power stimulated the specification, design, and simulation testing of an inverter/controller subsystem tailored to the photovoltaic power source characteristics. This paper discusses the optimization of the inverter/controller design as part of an overall Photovoltaic Power System (PPS) designed for maximum energy extraction from the solar array. The special design requirements for the inverter/controller include: (1) a power system controller (PSC) to control continuously the solar array operating point at the maximum power level based on variable solar insolation and cell temperatures; and (2) an inverter designed for high efficiency at rated load and low losses at light loadings to conserve energy. It must be capable of operating connected to the utility line at a level set by an external controller (PSC).
Design of Life Extending Controls Using Nonlinear Parameter Optimization
NASA Technical Reports Server (NTRS)
Lorenzo, Carl F.; Holmes, Michael S.; Ray, Asok
1998-01-01
This report presents the conceptual development of a life extending control system where the objective is to achieve high performance and structural durability of the plant. A life extending controller is designed for a reusable rocket engine via damage mitigation in both the fuel and oxidizer turbines while achieving high performance for transient responses of the combustion chamber pressure and the O2/H2 mixture ratio. This design approach makes use of a combination of linear and nonlinear controller synthesis techniques and also allows adaptation of the life extending controller module to augment a conventional performance controller of a rocket engine. The nonlinear aspect of the design is achieved using nonlinear parameter optimization of a prescribed control structure.
Object Correlation and Maneuver Detection Using Optimal Control Performance Metrics
NASA Astrophysics Data System (ADS)
Holzinger, M.; Scheeres, D.
2010-09-01
Object correlation and maneuver detection are persistent problems in space surveillance and space object catalog maintenance. This paper demonstrates the utility of using quadratic trajectory control cost, an analog to the trajectory L2-norm in control, as a distance metric with which to both correlate object tracks and detect maneuvers using Uncorrelated Tracks (UCTs), real-time sensor measurement residuals, and prior state uncertainty. State and measurement uncertainty are incorporated into the computation, and distributions of optimal control usage are computed. Both UCT correlation as well as maneuver detection are demonstrated in several scenarios Potential avenues for future research and contributions are summarized.
Development of a digital adaptive optimal linear regulator flight controller
NASA Technical Reports Server (NTRS)
Berry, P.; Kaufman, H.
1975-01-01
Digital adaptive controllers have been proposed as a means for retaining uniform handling qualities over the flight envelope of a high-performance aircraft. Towards such an implementation, an explicit adaptive controller, which makes direct use of online parameter identification, has been developed and applied to the linearized lateral equations of motion for a typical fighter aircraft. The system is composed of an online weighted least-squares parameter identifier, a Kalman state filter, and a model following control law designed using optimal linear regulator theory. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for onboard implementation.
Optimal Control of Hybrid Systems in Air Traffic Applications
NASA Astrophysics Data System (ADS)
Kamgarpour, Maryam
Growing concerns over the scalability of air traffic operations, air transportation fuel emissions and prices, as well as the advent of communication and sensing technologies motivate improvements to the air traffic management system. To address such improvements, in this thesis a hybrid dynamical model as an abstraction of the air traffic system is considered. Wind and hazardous weather impacts are included using a stochastic model. This thesis focuses on the design of algorithms for verification and control of hybrid and stochastic dynamical systems and the application of these algorithms to air traffic management problems. In the deterministic setting, a numerically efficient algorithm for optimal control of hybrid systems is proposed based on extensions of classical optimal control techniques. This algorithm is applied to optimize the trajectory of an Airbus 320 aircraft in the presence of wind and storms. In the stochastic setting, the verification problem of reaching a target set while avoiding obstacles (reach-avoid) is formulated as a two-player game to account for external agents' influence on system dynamics. The solution approach is applied to air traffic conflict prediction in the presence of stochastic wind. Due to the uncertainty in forecasts of the hazardous weather, and hence the unsafe regions of airspace for aircraft flight, the reach-avoid framework is extended to account for stochastic target and safe sets. This methodology is used to maximize the probability of the safety of aircraft paths through hazardous weather. Finally, the problem of modeling and optimization of arrival air traffic and runway configuration in dense airspace subject to stochastic weather data is addressed. This problem is formulated as a hybrid optimal control problem and is solved with a hierarchical approach that decouples safety and performance. As illustrated with this problem, the large scale of air traffic operations motivates future work on the efficient
Control design variable linking for optimization of structural/control systems
NASA Technical Reports Server (NTRS)
Jin, Ik Min; Schmit, Lucien A.
1993-01-01
A method is presented to integrate the design space of structural/control system optimization problems in the case of linear state feedback control. Conventional structural sizing variables and elements of the feedback gain matrix are both treated as strictly independent design variables in optimization by extending design variable linking concepts to the control gains. Several approximation concepts including new control design variable linking schemes are used to formulate the integrated structural/control optimization problem as a sequence of explicit nonlinear mathematical programming problems. Examples which involve a variety of behavior constraints, including constraints on dynamic stability, damped frequencies, control effort, peak transient displacement, acceleration, and control force limits, are effectively solved by using the method presented.
NASA Astrophysics Data System (ADS)
Liu, Chao; Yang, Guigeng; Zhang, Yiqun
2015-01-01
The electrostatically controlled deployable membrane reflector (ECDMR) is a promising scheme to construct large size and high precision space deployable reflector antennas. This paper presents a novel design method for the large size and small F/D ECDMR considering the coupled structure-electrostatic problem. First, the fully coupled structural-electrostatic system is described by a three field formulation, in which the structure and passive electrical field is modeled by finite element method, and the deformation of the electrostatic domain is predicted by a finite element formulation of a fictitious elastic structure. A residual formulation of the structural-electrostatic field finite element model is established and solved by Newton-Raphson method. The coupled structural-electrostatic analysis procedure is summarized. Then, with the aid of this coupled analysis procedure, an integrated optimization method of membrane shape accuracy and stress uniformity is proposed, which is divided into inner and outer iterative loops. The initial state of relatively high shape accuracy and uniform stress distribution is achieved by applying the uniform prestress on the membrane design shape and optimizing the voltages, in which the optimal voltage is computed by a sensitivity analysis. The shape accuracy is further improved by the iterative prestress modification using the reposition balance method. Finally, the results of the uncoupled and coupled methods are compared and the proposed optimization method is applied to design an ECDMR. The results validate the effectiveness of this proposed methods.
A Nonlinear Fuel Optimal Reaction Jet Control Law
Breitfeller, E.; Ng, L.C.
2002-06-30
We derive a nonlinear fuel optimal attitude control system (ACS) that drives the final state to the desired state according to a cost function that weights the final state angular error relative to the angular rate error. Control is achieved by allowing the pulse-width-modulated (PWM) commands to begin and end anywhere within a control cycle, achieving a pulse width pulse time (PWPT) control. We show through a MATLAB{reg_sign} Simulink model that this steady-state condition may be accomplished, in the absence of sensor noise or model uncertainties, with the theoretical minimum number of actuator cycles. The ability to analytically achieve near-zero drift rates is particularly important in applications such as station-keeping and sensor imaging. Consideration is also given to the fact that, for relatively small sensor and model errors, the controller requires significantly fewer actuator cycles to reach the final state error than a traditional proportional-integral-derivative (PID) controller. The optimal PWPT attitude controller may be applicable for a high performance kinetic energy kill vehicle.
Self-Contained Automated Methodology for Optimal Flow Control
NASA Technical Reports Server (NTRS)
Joslin, Ronald D.; Gunzburger, Max D.; Nicolaides, Roy A.; Erlebacherl, Gordon; Hussaini, M. Yousuff
1997-01-01
This paper describes a self-contained, automated methodology for active flow control which couples the time-dependent Navier-Stokes system with an adjoint Navier-Stokes system and optimality conditions from which optimal states, i.e., unsteady flow fields and controls (e.g., actuators), may be determined. The problem of boundary layer instability suppression through wave cancellation is used as the initial validation case to test the methodology. Here, the objective of control is to match the stress vector along a portion of the boundary to a given vector; instability suppression is achieved by choosing the given vector to be that of a steady base flow. Control is effected through the injection or suction of fluid through a single orifice on the boundary. The results demonstrate that instability suppression can be achieved without any a priori knowledge of the disturbance, which is significant because other control techniques have required some knowledge of the flow unsteadiness such as frequencies, instability type, etc. The present methodology has been extended to three dimensions and may potentially be applied to separation control, re-laminarization, and turbulence control applications using one to many sensors and actuators.
Vision-based stereo ranging as an optimal control problem
NASA Technical Reports Server (NTRS)
Menon, P. K. A.; Sridhar, B.; Chatterji, G. B.
1992-01-01
The recent interest in the use of machine vision for flight vehicle guidance is motivated by the need to automate the nap-of-the-earth flight regime of helicopters. Vision-based stereo ranging problem is cast as an optimal control problem in this paper. A quadratic performance index consisting of the integral of the error between observed image irradiances and those predicted by a Pade approximation of the correspondence hypothesis is then used to define an optimization problem. The necessary conditions for optimality yield a set of linear two-point boundary-value problems. These two-point boundary-value problems are solved in feedback form using a version of the backward sweep method. Application of the ranging algorithm is illustrated using a laboratory image pair.
Engineering adiabaticity at an avoided crossing with optimal control
NASA Astrophysics Data System (ADS)
Chasseur, T.; Theis, L. S.; Sanders, Y. R.; Egger, D. J.; Wilhelm, F. K.
2015-04-01
We investigate ways to optimize adiabaticity and diabaticity in the Landau-Zener model with nonuniform sweeps. We show how diabaticity can be engineered with a pulse consisting of a linear sweep augmented by an oscillating term. We show that the oscillation leads to jumps in populations whose value can be accurately modeled using a model of multiple, photon-assisted Landau-Zener transitions, which generalizes work by Wubs et al. [New J. Phys. 7, 218 (2005)], 10.1088/1367-2630/7/1/218. We extend the study on diabaticity using methods derived from optimal control. We also show how to preserve adiabaticity with optimal pulses at limited time, finding a nonuniform quantum speed limit.
Mirabelli, Maria C.; Golan, Rachel; Greenwald, Roby; Raysoni, Amit U.; Holguin, Fernando; Kewada, Priya; Winquist, Andrea; Flanders, W. Dana; Sarnat, Jeremy A.
2015-01-01
Background Effects of traffic-related exposures on respiratory health are well documented, but little information is available about whether asthma control influences individual susceptibility. We analyzed data from the Atlanta Commuter Exposure study to evaluate modification of associations between rush-hour commuting, in-vehicle air pollution, and selected respiratory health outcomes by asthma control status. Methods Between 2009 and 2011, 39 adults participated in Atlanta Commuter Exposure, and each conducted two scripted rush-hour highway commutes. In-vehicle particulate components were measured during all commutes. Among adults with asthma, we evaluated asthma control by questionnaire and spirometry. Exhaled nitric oxide, forced expiratory volume in 1 second (FEV1), and other metrics of respiratory health were measured precommute and 0, 1, 2, and 3 hours postcommute. We used mixed effects linear regression to evaluate associations between commute-related exposures and postcommute changes in metrics of respiratory health by level of asthma control. Results We observed increased exhaled nitric oxide across all levels of asthma control compared with precommute measurements, with largest postcommute increases observed among participants with below-median asthma control (2 hours postcommute: 14.6% [95% confidence interval {CI} = 5.7, 24.2]; 3 hours postcommute: 19.5% [95% CI = 7.8, 32.5]). No associations between in-vehicle pollutants and percent of predicted FEV1 were observed, although higher PM2.5 was associated with lower FEV1 % predicted among participants with below-median asthma control (3 hours postcommute: −7.2 [95% CI = −11.8, −2.7]). Conclusions Level of asthma control may influence respiratory response to in-vehicle exposures experienced during rush-hour commuting. PMID:25901844
NASA Astrophysics Data System (ADS)
Mathew, Reuble; Shi Yang, Hong Yi; Hall, Kimberley
2015-03-01
Optimal quantum control (OQC), which iteratively optimizes the control Hamiltonian to achieve a target quantum state, is a versatile approach for manipulating quantum systems. For optically-active transitions, OQC can be implemented using femtosecond pulse shaping which provides control over the amplitude and/or phase of the electric field. Optical pulse shaping has been employed to optimize physical processes such as nonlinear optical signals, photosynthesis, and has recently been applied to optimizing single-qubit gates in multiple semiconductor quantum dots. In this work, we examine the use of numerical pulse shape optimization for optimal quantum control of multiple qubits confined to quantum dots as a function of their electronic structure parameters. The numerically optimized pulse shapes were found to produce high fidelity quantum gates for a range of transition frequencies, dipole moments, and arbitrary initial and final states. This work enhances the potential for scalability by reducing the laser resources required to control multiple qubits.
Optimal Control of Quantum Measurement for Superconducting Phase Qubits
NASA Astrophysics Data System (ADS)
Wilhelm, Frank; Egger, Daniel
2015-03-01
Pulses to steer the time evolution of quantum systems can be designed with optimal control theory. In most cases it is the coherent processes that can be controlled and one optimizes the time evolution towards a target unitary process, sometimes also in the presence of non-controllable incoherent processes. Here we show how to extend the GRAPE algorithm in the case where the incoherent processes are controllable and the target time evolution is a non-unitary quantum channel. We perform a gradient search on a fidelity measure based on Choi matrices. We illustrate our algorithm by optimizing a phase qubit measurement pulse. We show how this technique can lead to large measurement contrast close to 99%. We also show, within the validity of our model, that this algorithm can produce short 1.4 ns pulses with 98.2% contrast. Work posted at arXiv:1408.6086, in press at Physical Review A Supported by the EU through SCALEQIT.
Nonlinear Burn Control and Operating Point Optimization in ITER
NASA Astrophysics Data System (ADS)
Boyer, Mark; Schuster, Eugenio
2013-10-01
Control of the fusion power through regulation of the plasma density and temperature will be essential for achieving and maintaining desired operating points in fusion reactors and burning plasma experiments like ITER. In this work, a volume averaged model for the evolution of the density of energy, deuterium and tritium fuel ions, alpha-particles, and impurity ions is used to synthesize a multi-input multi-output nonlinear feedback controller for stabilizing and modulating the burn condition. Adaptive control techniques are used to account for uncertainty in model parameters, including particle confinement times and recycling rates. The control approach makes use of the different possible methods for altering the fusion power, including adjusting the temperature through auxiliary heating, modulating the density and isotopic mix through fueling, and altering the impurity density through impurity injection. Furthermore, a model-based optimization scheme is proposed to drive the system as close as possible to desired fusion power and temperature references. Constraints are considered in the optimization scheme to ensure that, for example, density and beta limits are avoided, and that optimal operation is achieved even when actuators reach saturation. Supported by the NSF CAREER award program (ECCS-0645086).
Optimal control law for classical and multiconjugate adaptive optics
NASA Astrophysics Data System (ADS)
Le Roux, Brice; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Mugnier, Laurent M.; Fusco, Thierry
2004-07-01
Classical adaptive optics (AO) is now a widespread technique for high-resolution imaging with astronomical ground-based telescopes. It generally uses simple and efficient control algorithms. Multiconjugate adaptive optics (MCAO) is a more recent and very promising technique that should extend the corrected field of view. This technique has not yet been experimentally validated, but simulations already show its high potential. The importance for MCAO of an optimal reconstruction using turbulence spatial statistics has already been demonstrated through open-loop simulations. We propose an optimal closed-loop control law that accounts for both spatial and temporal statistics. The prior information on the turbulence, as well as on the wave-front sensing noise, is expressed in a state-space model. The optimal phase estimation is then given by a Kalman filter. The equations describing the system are given and the underlying assumptions explained. The control law is then derived. The gain brought by this approach is demonstrated through MCAO numerical simulations representative of astronomical observation on a 8-m-class telescope in the near infrared. We also discuss the application of this control approach to classical AO. Even in classical AO, the technique could be relevant especially for future extreme AO systems.
Optimal control law for classical and multiconjugate adaptive optics.
Le Roux, Brice; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Mugnier, Laurent M; Fusco, Thierry
2004-07-01
Classical adaptive optics (AO) is now a widespread technique for high-resolution imaging with astronomical ground-based telescopes. It generally uses simple and efficient control algorithms. Multiconjugate adaptive optics (MCAO) is a more recent and very promising technique that should extend the corrected field of view. This technique has not yet been experimentally validated, but simulations already show its high potential. The importance for MCAO of an optimal reconstruction using turbulence spatial statistics has already been demonstrated through open-loop simulations. We propose an optimal closed-loop control law that accounts for both spatial and temporal statistics. The prior information on the turbulence, as well as on the wave-front sensing noise, is expressed in a state-space model. The optimal phase estimation is then given by a Kalman filter. The equations describing the system are given and the underlying assumptions explained. The control law is then derived. The gain brought by this approach is demonstrated through MCAO numerical simulations representative of astronomical observation on a 8-m-class telescope in the near infrared. We also discuss the application of this control approach to classical AO. Even in classical AO, the technique could be relevant especially for future extreme AO systems. PMID:15260258
Optimization of removal function in computer controlled optical surfacing
NASA Astrophysics Data System (ADS)
Chen, Xi; Guo, Peiji; Ren, Jianfeng
2010-10-01
The technical principle of computer controlled optical surfacing (CCOS) and the common method of optimizing removal function that is used in CCOS are introduced in this paper. A new optimizing method time-sharing synthesis of removal function is proposed to solve problems of the removal function being far away from Gaussian type and slow approaching of the removal function error that encountered in the mode of planet motion or translation-rotation. Detailed time-sharing synthesis of using six removal functions is discussed. For a given region on the workpiece, six positions are selected as the centers of the removal function; polishing tool controlled by the executive system of CCOS revolves around each centre to complete a cycle in proper order. The overall removal function obtained by the time-sharing process is the ratio of total material removal in six cycles to time duration of the six cycles, which depends on the arrangement and distribution of the six removal functions. Simulations on the synthesized overall removal functions under two different modes of motion, i.e., planet motion and translation-rotation are performed from which the optimized combination of tool parameters and distribution of time-sharing synthesis removal functions are obtained. The evaluation function when optimizing is determined by an approaching factor which is defined as the ratio of the material removal within the area of half of the polishing tool coverage from the polishing center to the total material removal within the full polishing tool coverage area. After optimization, it is found that the optimized removal function obtained by time-sharing synthesis is closer to the ideal Gaussian type removal function than those by the traditional methods. The time-sharing synthesis method of the removal function provides an efficient way to increase the convergence speed of the surface error in CCOS for the fabrication of aspheric optical surfaces, and to reduce the intermediate- and high
Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System
Chen, Jilin; Wang, Li; Xu, Shiqing; Hou, Yuanlong
2013-01-01
Motion control of gun barrels is an ongoing topic for the development of gun control equipments possessing excellent performances. In this paper, a typical fractional order PID control strategy is employed for the gun control system. To obtain optimal parameters of the controller, a multiobjective optimization scheme is developed from the loop-shaping perspective. To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. To enhance the robustness of the algorithm for different problems, an adapting scheme of the mutation operation is further employed. With assistance of the evolutionary algorithm, the optimal solution for the specified problem is selected. The numerical simulation results show that the control system can rapidly follow the demand signal with high accuracy and high robustness, demonstrating the efficiency of the proposed controller parameter tuning method. PMID:23766721
Optimal Parametric Discrete Event Control: Problem and Solution
Griffin, Christopher H
2008-01-01
We present a novel optimization problem for discrete event control, similar in spirit to the optimal parametric control problem common in statistical process control. In our problem, we assume a known finite state machine plant model $G$ defined over an event alphabet $\\Sigma$ so that the plant model language $L = \\LanM(G)$ is prefix closed. We further assume the existence of a \\textit{base control structure} $M_K$, which may be either a finite state machine or a deterministic pushdown machine. If $K = \\LanM(M_K)$, we assume $K$ is prefix closed and that $K \\subseteq L$. We associate each controllable transition of $M_K$ with a binary variable $X_1,\\dots,X_n$ indicating whether the transition is enabled or not. This leads to a function $M_K(X_1,\\dots,X_n)$, that returns a new control specification depending upon the values of $X_1,\\dots,X_n$. We exhibit a branch-and-bound algorithm to solve the optimization problem $\\min_{X_1,\\dots,X_n}\\max_{w \\in K} C(w)$ such that $M_K(X_1,\\dots,X_n) \\models \\Pi$ and $\\LanM(M_K(X_1,\\dots,X_n)) \\in \\Con(L)$. Here $\\Pi$ is a set of logical assertions on the structure of $M_K(X_1,\\dots,X_n)$, and $M_K(X_1,\\dots,X_n) \\models \\Pi$ indicates that $M_K(X_1,\\dots,X_n)$ satisfies the logical assertions; and, $\\Con(L)$ is the set of controllable sublanguages of $L$.
Coherent control of multiple vibrational excitations for optimal detection
NASA Astrophysics Data System (ADS)
McGrane, S. D.; Scharff, R. J.; Greenfield, M.; Moore, D. S.
2009-10-01
While the means to selectively excite a single vibrational mode using ultrafast pulse shaping are well established, the subsequent problem of selectively exciting multiple vibrational modes simultaneously has been largely neglected. The coherent control of multiple vibrational excitations has applications in control of chemistry, chemical detection and molecular vibrational quantum information processing. Using simulations and experiments, we demonstrate that multiple vibrational modes can be selectively excited with the concurrent suppression of multiple interfering modes by orders of magnitude. While the mechanism of selectivity is analogous to that of single mode selectivity, the interferences required to select multiple modes require complicated non-intuitive pulse trains. Additionally, we show that selective detection can be achieved by the optimal pulse shape, even when the nature of the interfering species is varied, suggesting that optimized detection should be practical in real world applications. Experimental measurements of the multiplex coherent anti-Stokes Raman spectra (CARS) and CARS decay times of toluene, acetone, cis-stilbene and nitromethane liquids are reported, along with optimizations attempting to selectively excite nitromethane in a mixture of the four solvents. The experimental implementation exhibits a smaller degree of signal to background enhancement than predicted, which is primarily attributed to the single objective optimization methodology and not to fundamental limitations.
Human energy - optimal control of disturbance rejection during constrained standing.
Mihelj, M; Munih, M; Ponikvar, M
2003-01-01
An optimal control system that enables a subject to stand without hand support in the sagittal plane was designed. The subject was considered as a double inverted pendulum structure with a voluntarily controlled degree of freedom in the upper trunk and artificially controlled degree of freedom in the ankle joints. The control system design was based on a minimization of cost function that estimated the effort of the ankle joint muscles through observation of the ground reaction force position relative to the ankle joint axis. By maintaining the centre of pressure close to the ankle joint axis the objective of the upright stance is fulfilled with minimal ankle muscle energy cost. The performance of the developed controller was evaluated in a simulation-based study. The results were compared with the responses of an unimpaired subject to different disturbances in the sagittal plane. The proposed cost function was shown to produce a reasonable approximation of human natural behaviour. PMID:12936049
Microgravity vibration isolation: Optimal preview and feedback control
NASA Technical Reports Server (NTRS)
Hampton, R. D.; Knospe, C. R.; Grodsinsky, C. M.; Allaire, P. E.; Lewis, D. W.
1992-01-01
In order to achieve adequate low-frequency vibration isolation for certain space experiments an active control is needed, due to inherent passive-isolator limitations. Proposed here are five possible state-space models for a one-dimensional vibration isolation system with a quadratic performance index. The five models are subsets of a general set of nonhomogeneous state space equations which includes disturbance terms. An optimal control is determined, using a differential equations approach, for this class of problems. This control is expressed in terms of constant, Linear Quadratic Regulator (LQR) feedback gains and constant feedforward (preview) gains. The gains can be easily determined numerically. They result in a robust controller and offers substantial improvements over a control that uses standard LQR feedback alone.
NASA Technical Reports Server (NTRS)
Armand, J. P.
1972-01-01
An extension of classical methods of optimal control theory for systems described by ordinary differential equations to distributed-parameter systems described by partial differential equations is presented. An application is given involving the minimum-mass design of a simply-supported shear plate with a fixed fundamental frequency of vibration. An optimal plate thickness distribution in analytical form is found. The case of a minimum-mass design of an elastic sandwich plate whose fundamental frequency of free vibration is fixed. Under the most general conditions, the optimization problem reduces to the solution of two simultaneous partial differential equations involving the optimal thickness distribution and the modal displacement. One equation is the uniform energy distribution expression which was found by Ashley and McIntosh for the optimal design of one-dimensional structures with frequency constraints, and by Prager and Taylor for various design criteria in one and two dimensions. The second equation requires dynamic equilibrium at the preassigned vibration frequency.
Flight control systems research. [optimization of F-8 aircraft control system
NASA Technical Reports Server (NTRS)
Whitaker, H. P.; Baram, Y.; Cheng, Y.
1973-01-01
Theoretical development is reported for the parameter optimization design technique needed for digital flight control system design. The results of an example case study applying the optimization technique for continuous systems to an F-8 aircraft feedback control system are presented. The concept of evolving the simplest system configuration that is capable of meeting a specified set of performance requirements is illustrated in this work.
Application of constrained optimization to active control of aeroelastic response
NASA Technical Reports Server (NTRS)
Newsom, J. R.; Mukhopadhyay, V.
1981-01-01
Active control of aeroelastic response is a complex in which the designer usually tries to satisfy many criteria which are often conflicting. To further complicate the design problem, the state space equations describing this type of control problem are usually of high order, involving a large number of states to represent the flexible structure and unsteady aerodynamics. Control laws based on the standard Linear-Quadratic-Gaussian (LQG) method are of the same high order as the aeroelastic plant. To overcome this disadvantage of the LQG mode, an approach developed for designing low order optimal control laws which uses a nonlinear programming algorithm to search for the values of the control law variables that minimize a composite performance index, was extended to the constrained optimization problem. The method involves searching for the values of the control law variables that minimize a basic performance index while satisfying several inequality constraints that describe the design criteria. The method is applied to gust load alleviation of a drone aircraft.
Investigation of Optimal Control Allocation for Gust Load Alleviation in Flight Control
NASA Technical Reports Server (NTRS)
Frost, Susan A.; Taylor, Brian R.; Bodson, Marc
2012-01-01
Advances in sensors and avionics computation power suggest real-time structural load measurements could be used in flight control systems for improved safety and performance. A conventional transport flight control system determines the moments necessary to meet the pilot's command, while rejecting disturbances and maintaining stability of the aircraft. Control allocation is the problem of converting these desired moments into control effector commands. In this paper, a framework is proposed to incorporate real-time structural load feedback and structural load constraints in the control allocator. Constrained optimal control allocation can be used to achieve desired moments without exceeding specified limits on monitored load points. Minimization of structural loads by the control allocator is used to alleviate gust loads. The framework to incorporate structural loads in the flight control system and an optimal control allocation algorithm will be described and then demonstrated on a nonlinear simulation of a generic transport aircraft with flight dynamics and static structural loads.
A model for HIV/AIDS pandemic with optimal control
NASA Astrophysics Data System (ADS)
Sule, Amiru; Abdullah, Farah Aini
2015-05-01
Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is pandemic. It has affected nearly 60 million people since the detection of the disease in 1981 to date. In this paper basic deterministic HIV/AIDS model with mass action incidence function are developed. Stability analysis is carried out. And the disease free equilibrium of the basic model was found to be locally asymptotically stable whenever the threshold parameter (RO) value is less than one, and unstable otherwise. The model is extended by introducing two optimal control strategies namely, CD4 counts and treatment for the infective using optimal control theory. Numerical simulation was carried out in order to illustrate the analytic results.
Neural optimal control of flexible spacecraft slew maneuver
NASA Astrophysics Data System (ADS)
Nayeri, M. Reza Dehghan; Alasty, Aria; Daneshjou, Kamran
2004-11-01
This paper deals with the problem of optimal large-angle single-axis maneuvers of a flexible spacecraft with simultaneous vibration suppression of elastic modes. A spacecraft model with a cylindrical hub and one flexible appendage and tip mass is considered. Gravity gradient torque is considered as a disturbance torque. Multilayer perceptron neural networks are used to design a Neural Optimal Controller (NOC) for this multivariable non-linear maneuver. For NOC training, an off-line training procedure based on backpropagation through time algorithm is developed to minimize the general quadratic cost function in forward and backward pass stages. The proposed controller is also applicable to simultaneous multi-axis reorientation of a flexible spacecraft. Simulation results are presented to show that very fast reference pitch angle trajectory tracking and vibration suppression are accomplished.
Noise-resistant optimal spin squeezing via quantum control
NASA Astrophysics Data System (ADS)
Pichler, T.; Caneva, T.; Montangero, S.; Lukin, M. D.; Calarco, T.
2016-01-01
Entangled atomic states, such as spin-squeezed states, represent a promising resource for a new generation of quantum sensors and atomic clocks. We demonstrate that optimal control techniques can be used to substantially enhance the degree of spin squeezing in strongly interacting many-body systems, even in the presence of noise and imperfections. Specifically, we present a protocol that is robust to noise and outperforms conventional methods. Potential experimental implementations are discussed.
Optimal feedback control infinite dimensional parabolic evolution systems: Approximation techniques
NASA Technical Reports Server (NTRS)
Banks, H. T.; Wang, C.
1989-01-01
A general approximation framework is discussed for computation of optimal feedback controls in linear quadratic regular problems for nonautonomous parabolic distributed parameter systems. This is done in the context of a theoretical framework using general evolution systems in infinite dimensional Hilbert spaces. Conditions are discussed for preservation under approximation of stabilizability and detectability hypotheses on the infinite dimensional system. The special case of periodic systems is also treated.
Implicit methods for efficient musculoskeletal simulation and optimal control
van den Bogert, Antonie J.; Blana, Dimitra; Heinrich, Dieter
2011-01-01
The ordinary differential equations for musculoskeletal dynamics are often numerically stiff and highly nonlinear. Consequently, simulations require small time steps, and optimal control problems are slow to solve and have poor convergence. In this paper, we present an implicit formulation of musculoskeletal dynamics, which leads to new numerical methods for simulation and optimal control, with the expectation that we can mitigate some of these problems. A first order Rosenbrock method was developed for solving forward dynamic problems using the implicit formulation. It was used to perform real-time dynamic simulation of a complex shoulder arm system with extreme dynamic stiffness. Simulations had an RMS error of only 0.11 degrees in joint angles when running at real-time speed. For optimal control of musculoskeletal systems, a direct collocation method was developed for implicitly formulated models. The method was applied to predict gait with a prosthetic foot and ankle. Solutions were obtained in well under one hour of computation time and demonstrated how patients may adapt their gait to compensate for limitations of a specific prosthetic limb design. The optimal control method was also applied to a state estimation problem in sports biomechanics, where forces during skiing were estimated from noisy and incomplete kinematic data. Using a full musculoskeletal dynamics model for state estimation had the additional advantage that forward dynamic simulations, could be done with the same implicitly formulated model to simulate injuries and perturbation responses. While these methods are powerful and allow solution of previously intractable problems, there are still considerable numerical challenges, especially related to the convergence of gradient-based solvers. PMID:22102983
Characterizations of Overtaking Optimality for Controlled Diffusion Processes
Jasso-Fuentes, Hector Hernandez-Lerma, Onesimo
2008-06-15
In this paper we give conditions for (the existence and) several characterizations of overtaking optimal policies for a general class of controlled diffusion processes. Our characterization results are of a lexicographical type; namely, first we identify the class of so-called canonical policies, and then within this class we search for policies with some special feature-for instance, canonical policies that in addition maximize the bias.
NASA Technical Reports Server (NTRS)
Hyland, D. C.; Bernstein, D. S.
1987-01-01
The underlying philosophy and motivation of the optimal projection/maximum entropy (OP/ME) stochastic modeling and reduced control design methodology for high order systems with parameter uncertainties are discussed. The OP/ME design equations for reduced-order dynamic compensation including the effect of parameter uncertainties are reviewed. The application of the methodology to several Large Space Structures (LSS) problems of representative complexity is illustrated.
Optimal control of a low wing-loading STOL aircraft
NASA Technical Reports Server (NTRS)
Cunningham, T. B.
1976-01-01
Linear optimal quadratic control theory is applied to a low wing-loading STOL aircraft for ride quality and flight path following. Design criteria include minimum rms response to wind turbulence and desired transient response characteristics. Design techniques include proper choosing of design versus evaluation models, choosing appropriate performance index responses, and use of classical evaluation techniques. Results are obtained through a combination of frequency response shaping and gust observation. Effects of control rate and authority saturation are examined with a new rapid calculation of random input describing functions. Parameter sensitivity is also evaluated using a Liapunov type matrix equation.
Optimizing aircraft performance with adaptive, integrated flight/propulsion control
NASA Technical Reports Server (NTRS)
Smith, R. H.; Chisholm, J. D.; Stewart, J. F.
1991-01-01
The Performance-Seeking Control (PSC) integrated flight/propulsion adaptive control algorithm presented was developed in order to optimize total aircraft performance during steady-state engine operation. The PSC multimode algorithm minimizes fuel consumption at cruise conditions, while maximizing excess thrust during aircraft accelerations, climbs, and dashes, and simultaneously extending engine service life through reduction of fan-driving turbine inlet temperature upon engagement of the extended-life mode. The engine models incorporated by the PSC are continually upgraded, using a Kalman filter to detect anomalous operations. The PSC algorithm will be flight-demonstrated by an F-15 at NASA-Dryden.
NASA Technical Reports Server (NTRS)
Schmidt, Phillip; Garg, Sanjay; Holowecky, Brian
1992-01-01
A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.
Control of mould level fluctuation through the modification of steel composition
NASA Astrophysics Data System (ADS)
Li, Yang; Zhang, Xiao-huan; Lan, Peng; Zhang, Jia-quan
2013-02-01
Periodic mould level fluctuation (MLF) during slab casting is a bottleneck for upgrading the surface quality and casting speed especially for hypoperitectic (HP) or ultralow carbon steels. The uneven growth of the initially solidified shell is verified to be one of the important inducements to MLF due to related unsteady bulging in the secondary cooling zone. It is shown that the solidification mode of steels and the contraction behavior can be modified through chemical composition optimization within given composition limits. For high strength low alloy (HSLA) steels, the actual peritectic points calculated by Thermo-Calc software may change remarkably with the slight variations of alloying element contents. Accordingly, the narrow limit of chemical composition of HP steels through optimization is proven to be one of the effective factors to control the popular MLF phenomenon during slab casting.
Biomechanical modeling and optimal control of human posture.
Menegaldo, Luciano Luporini; Fleury, Agenor de Toledo; Weber, Hans Ingo
2003-11-01
The present work describes the biomechanical modeling of human postural mechanics in the saggital plane and the use of optimal control to generate open-loop raising-up movements from a squatting position. The biomechanical model comprises 10 equivalent musculotendon actuators, based on a 40 muscles model, and three links (shank, thigh and HAT-Head, Arms and Trunk). Optimal control solutions are achieved through algorithms based on the Consistent Approximations Theory (Schwartz and Polak, 1996), where the continuous non-linear dynamics is represented in a discrete space by means of a Runge-Kutta integration and the control signals in a spline-coefficient functional space. This leads to non-linear programming problems solved by a sequential quadratic programming (SQP) method. Due to the highly non-linear and unstable nature of the posture dynamics, numerical convergence is difficult, and specific strategies must be implemented in order to allow convergence. Results for control (muscular excitations) and angular trajectories are shown using two final simulation times, as well as specific control strategies are discussed. PMID:14522212
Acoustic control in enclosures using optimally designed Helmholtz resonators
NASA Astrophysics Data System (ADS)
Driesch, Patricia Lynne
A virtual design methodology is developed to minimize the noise in enclosures with optimally designed, passive, acoustic absorbers (Helmholtz resonators). A series expansion of eigen functions is used to represent the acoustic absorbers as external volume velocities, eliminating the need for a solution of large matrix eigen value problems. A determination of this type (efficient model/reevaluation approach) significantly increases the design possibilities when optimization techniques are implemented. As a benchmarking exercise, this novel methodology was experimentally validated for a narrowband acoustic assessment of two optimally designed Helmholtz resonators coupled to a 2D enclosure. The resonators were tuned to the two lowest resonance frequencies of a 30.5 by 40.6 by 2.5 cm (12 x 16 x 1 inch) cavity with the resonator volume occupying only 2% of the enclosure volume. A maximum potential energy reduction of 12.4 dB was obtained at the second resonance of the cavity. As a full-scale demonstration of the efficacy of the proposed design method, the acoustic response from 90--190 Hz of a John Deere 7000 Ten series tractor cabin was investigated. The lowest cabin mode, referred to as a "boom" mode, proposes a significant challenge to a noise control engineer since its anti-node is located near the head of the operator and often generates unacceptable sound pressure levels. Exploiting the low frequency capability of Helmholtz resonators, lumped parameter models of these resonators were coupled to the enclosure via an experimentally determined acoustic model of the tractor cabin. The virtual design methodology uses gradient optimization techniques as a post processor for the modeling and analysis of the unmodified acoustic interior to determine optimal resonator characteristics. Using two optimally designed Helmholtz resonators; potential energy was experimentally reduced by 3.4 and 10.3 dB at 117 and 167 Hz, respectively.
Debbarma, Sanjoy; Saikia, Lalit Chandra; Sinha, Nidul
2014-03-01
Present work focused on automatic generation control (AGC) of a three unequal area thermal systems considering reheat turbines and appropriate generation rate constraints (GRC). A fractional order (FO) controller named as I(λ)D(µ) controller based on crone approximation is proposed for the first time as an appropriate technique to solve the multi-area AGC problem in power systems. A recently developed metaheuristic algorithm known as firefly algorithm (FA) is used for the simultaneous optimization of the gains and other parameters such as order of integrator (λ) and differentiator (μ) of I(λ)D(µ) controller and governor speed regulation parameters (R). The dynamic responses corresponding to optimized I(λ)D(µ) controller gains, λ, μ, and R are compared with that of classical integer order (IO) controllers such as I, PI and PID controllers. Simulation results show that the proposed I(λ)D(µ) controller provides more improved dynamic responses and outperforms the IO based classical controllers. Further, sensitivity analysis confirms the robustness of the so optimized I(λ)D(µ) controller to wide changes in system loading conditions and size and position of SLP. Proposed controller is also found to have performed well as compared to IO based controllers when SLP takes place simultaneously in any two areas or all the areas. Robustness of the proposed I(λ)D(µ) controller is also tested against system parameter variations. PMID:24139308
Spacecraft attitude control using neuro-fuzzy approximation of the optimal controllers
NASA Astrophysics Data System (ADS)
Kim, Sung-Woo; Park, Sang-Young; Park, Chandeok
2016-01-01
In this study, a neuro-fuzzy controller (NFC) was developed for spacecraft attitude control to mitigate large computational load of the state-dependent Riccati equation (SDRE) controller. The NFC was developed by training a neuro-fuzzy network to approximate the SDRE controller. The stability of the NFC was numerically verified using a Lyapunov-based method, and the performance of the controller was analyzed in terms of approximation ability, steady-state error, cost, and execution time. The simulations and test results indicate that the developed NFC efficiently approximates the SDRE controller, with asymptotic stability in a bounded region of angular velocity encompassing the operational range of rapid-attitude maneuvers. In addition, it was shown that an approximated optimal feedback controller can be designed successfully through neuro-fuzzy approximation of the optimal open-loop controller.
Comparative study of flare control laws. [optimal control of b-737 aircraft approach and landing
NASA Technical Reports Server (NTRS)
Nadkarni, A. A.; Breedlove, W. J., Jr.
1979-01-01
A digital 3-D automatic control law was developed to achieve an optimal transition of a B-737 aircraft between various initial glid slope conditions and the desired final touchdown condition. A discrete, time-invariant, optimal, closed-loop control law presented for a linear regulator problem, was extended to include a system being acted upon by a constant disturbance. Two forms of control laws were derived to solve this problem. One method utilized the feedback of integral states defined appropriately and augmented with the original system equations. The second method formulated the problem as a control variable constraint, and the control variables were augmented with the original system. The control variable constraint control law yielded a better performance compared to feedback control law for the integral states chosen.
Multigrid one shot methods for optimal control problems: Infinite dimensional control
NASA Technical Reports Server (NTRS)
Arian, Eyal; Taasan, Shlomo
1994-01-01
The multigrid one shot method for optimal control problems, governed by elliptic systems, is introduced for the infinite dimensional control space. ln this case, the control variable is a function whose discrete representation involves_an increasing number of variables with grid refinement. The minimization algorithm uses Lagrange multipliers to calculate sensitivity gradients. A preconditioned gradient descent algorithm is accelerated by a set of coarse grids. It optimizes for different scales in the representation of the control variable on different discretization levels. An analysis which reduces the problem to the boundary is introduced. It is used to approximate the two level asymptotic convergence rate, to determine the amplitude of the minimization steps, and the choice of a high pass filter to be used when necessary. The effectiveness of the method is demonstrated on a series of test problems. The new method enables the solutions of optimal control problems at the same cost of solving the corresponding analysis problems just a few times.
A multilevel control system for the large space telescope. [numerical analysis/optimal control
NASA Technical Reports Server (NTRS)
Siljak, D. D.; Sundareshan, S. K.; Vukcevic, M. B.
1975-01-01
A multilevel scheme was proposed for control of Large Space Telescope (LST) modeled by a three-axis-six-order nonlinear equation. Local controllers were used on the subsystem level to stabilize motions corresponding to the three axes. Global controllers were applied to reduce (and sometimes nullify) the interactions among the subsystems. A multilevel optimization method was developed whereby local quadratic optimizations were performed on the subsystem level, and global control was again used to reduce (nullify) the effect of interactions. The multilevel stabilization and optimization methods are presented as general tools for design and then used in the design of the LST Control System. The methods are entirely computerized, so that they can accommodate higher order LST models with both conceptual and numerical advantages over standard straightforward design techniques.
Infinite horizon optimal impulsive control with applications to Internet congestion control
NASA Astrophysics Data System (ADS)
Avrachenkov, Konstantin; Habachi, Oussama; Piunovskiy, Alexey; Zhang, Yi
2015-04-01
We investigate infinite-horizon deterministic optimal control problems with both gradual and impulsive controls, where any finitely many impulses are allowed simultaneously. Both discounted and long-run time-average criteria are considered. We establish very general and at the same time natural conditions, under which the dynamic programming approach results in an optimal feedback policy. The established theoretical results are applied to the Internet congestion control, and by solving analytically and nontrivially the underlying optimal control problems, we obtain a simple threshold-based active queue management scheme, which takes into account the main parameters of the transmission control protocols, and improves the fairness among the connections in a given network.
Optimal Control of Gene Mutation in DNA Replication
Yu, Juanyi; Li, Jr-Shin; Tarn, Tzyh-Jong
2012-01-01
We propose a molecular-level control system view of the gene mutations in DNA replication from the finite field concept. By treating DNA sequences as state variables, chemical mutagens and radiation as control inputs, one cell cycle as a step increment, and the measurements of the resulting DNA sequence as outputs, we derive system equations for both deterministic and stochastic discrete-time, finite-state systems of different scales. Defining the cost function as a summation of the costs of applying mutagens and the off-trajectory penalty, we solve the deterministic and stochastic optimal control problems by dynamic programming algorithm. In addition, given that the system is completely controllable, we find that the global optimum of both base-to-base and codon-to-codon deterministic mutations can always be achieved within a finite number of steps. PMID:22454557
Perturbing engine performance measurements to determine optimal engine control settings
Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna
2014-12-30
Methods and systems for optimizing a performance of a vehicle engine are provided. The method includes determining an initial value for a first engine control parameter based on one or more detected operating conditions of the vehicle engine, determining a value of an engine performance variable, and artificially perturbing the determined value of the engine performance variable. The initial value for the first engine control parameter is then adjusted based on the perturbed engine performance variable causing the engine performance variable to approach a target engine performance variable. Operation of the vehicle engine is controlled based on the adjusted initial value for the first engine control parameter. These acts are repeated until the engine performance variable approaches the target engine performance variable.
Simulation and optimal control of wind-farm boundary layers
NASA Astrophysics Data System (ADS)
Meyers, Johan; Goit, Jay
2014-05-01
In large wind farms, the effect of turbine wakes, and their interaction leads to a reduction in farm efficiency, with power generated by turbines in a farm being lower than that of a lone-standing turbine by up to 50%. In very large wind farms or `deep arrays', this efficiency loss is related to interaction of the wind farms with the planetary boundary layer, leading to lower wind speeds at turbine level. Moreover, for these cases it has been demonstrated both in simulations and wind-tunnel experiments that the wind-farm energy extraction is dominated by the vertical turbulent transport of kinetic energy from higher regions in the boundary layer towards the turbine level. In the current study, we investigate the use of optimal control techniques combined with Large-Eddy Simulations (LES) of wind-farm boundary layer interaction for the increase of total energy extraction in very large `infinite' wind farms. We consider the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the turbulent flow field, maximizing the wind farm power. For the simulation of wind-farm boundary layers we use large-eddy simulations in combination with actuator-disk and actuator-line representations of wind turbines. Simulations are performed in our in-house pseudo-spectral code SP-Wind that combines Fourier-spectral discretization in horizontal directions with a fourth-order finite-volume approach in the vertical direction. For the optimal control study, we consider the dynamic control of turbine-thrust coefficients in an actuator-disk model. They represent the effect of turbine blades that can actively pitch in time, changing the lift- and drag coefficients of the turbine blades. Optimal model-predictive control (or optimal receding horizon control) is used, where the model simply consists of the full LES equations, and the time horizon is approximately 280 seconds. The optimization is performed using a
Optimal placement of actuators and sensors in control augmented structural optimization
NASA Technical Reports Server (NTRS)
Sepulveda, A. E.; Schmit, L. A., Jr.
1990-01-01
A control-augmented structural synthesis methodology is presented in which actuator and sensor placement is treated in terms of (0,1) variables. Structural member sizes and control variables are treated simultaneously as design variables. A multiobjective utopian approach is used to obtain a compromise solution for inherently conflicting objective functions such as strucutal mass control effort and number of actuators. Constraints are imposed on transient displacements, natural frequencies, actuator forces and dynamic stability as well as controllability and observability of the system. The combinatorial aspects of the mixed - (0,1) continuous variable design optimization problem are made tractable by combining approximation concepts with branch and bound techniques. Some numerical results for example problems are presented to illustrate the efficacy of the design procedure set forth.
Finite-horizon control-constrained nonlinear optimal control using single network adaptive critics.
Heydari, Ali; Balakrishnan, Sivasubramanya N
2013-01-01
To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline. PMID:24808214
Multiresolution strategies for the numerical solution of optimal control problems
NASA Astrophysics Data System (ADS)
Jain, Sachin
There exist many numerical techniques for solving optimal control problems but less work has been done in the field of making these algorithms run faster and more robustly. The main motivation of this work is to solve optimal control problems accurately in a fast and efficient way. Optimal control problems are often characterized by discontinuities or switchings in the control variables. One way of accurately capturing the irregularities in the solution is to use a high resolution (dense) uniform grid. This requires a large amount of computational resources both in terms of CPU time and memory. Hence, in order to accurately capture any irregularities in the solution using a few computational resources, one can refine the mesh locally in the region close to an irregularity instead of refining the mesh uniformly over the whole domain. Therefore, a novel multiresolution scheme for data compression has been designed which is shown to outperform similar data compression schemes. Specifically, we have shown that the proposed approach results in fewer grid points in the grid compared to a common multiresolution data compression scheme. The validity of the proposed mesh refinement algorithm has been verified by solving several challenging initial-boundary value problems for evolution equations in 1D. The examples have demonstrated the stability and robustness of the proposed algorithm. The algorithm adapted dynamically to any existing or emerging irregularities in the solution by automatically allocating more grid points to the region where the solution exhibited sharp features and fewer points to the region where the solution was smooth. Thereby, the computational time and memory usage has been reduced significantly, while maintaining an accuracy equivalent to the one obtained using a fine uniform mesh. Next, a direct multiresolution-based approach for solving trajectory optimization problems is developed. The original optimal control problem is transcribed into a
Optimal planning of LEO active debris removal based on hybrid optimal control theory
NASA Astrophysics Data System (ADS)
Yu, Jing; Chen, Xiao-qian; Chen, Li-hu
2015-06-01
The mission planning of Low Earth Orbit (LEO) active debris removal problem is studied in this paper. Specifically, the Servicing Spacecraft (SSc) and several debris exist on near-circular near-coplanar LEOs. The SSc should repeatedly rendezvous with the debris, and de-orbit them until all debris are removed. Considering the long-duration effect of J2 perturbation, a linear dynamics model is used for each rendezvous. The purpose of this paper is to find the optimal service sequence and rendezvous path with minimum total rendezvous cost (Δv) for the whole mission, and some complex constraints (communication time window constraint, terminal state constraint, and time distribution constraint) should be satisfied meanwhile. Considering this mission as a hybrid optimal control problem, a mathematical model is proposed, as well as the solution method. The proposed approach is demonstrated by a typical active debris removal problem. Numerical experiments show that (1) the model and solution method proposed in this paper can effectively address the planning problem of LEO debris removal; (2) the communication time window constraint and the J2 perturbation have considerable influences on the optimization results; and (3) under the same configuration, some suboptimal sequences are equivalent to the optimal one since their difference in Δv cost is very small.
Combined structures-controls optimization of lattice trusses
NASA Technical Reports Server (NTRS)
Balakrishnan, A. V.
1991-01-01
The role that distributed parameter model can play in CSI is demonstrated, in particular in combined structures controls optimization problems of importance in preliminary design. Closed form solutions can be obtained for performance criteria such as rms attitude error, making possible analytical solutions of the optimization problem. This is in contrast to the need for numerical computer solution involving the inversion of large matrices in traditional finite element model (FEM) use. Another advantage of the analytic solution is that it can provide much needed insight into phenomena that can otherwise be obscured or difficult to discern from numerical computer results. As a compromise in level of complexity between a toy lab model and a real space structure, the lattice truss used in the EPS (Earth Pointing Satellite) was chosen. The optimization problem chosen is a generic one: of minimizing the structure mass subject to a specified stability margin and to a specified upper bond on the rms attitude error, using a co-located controller and sensors. Standard FEM treating each bar as a truss element is used, while the continuum model is anisotropic Timoshenko beam model. Performance criteria are derived for each model, except that for the distributed parameter model, explicit closed form solutions was obtained. Numerical results obtained by the two model show complete agreement.
A fuzzy-based optimal reactive power control
Abdul-Rahman, K.H.; Shahidehpour, S.M. . Dept. of Electrical and Computer Engineering)
1993-05-01
This paper presents a mathematical formulation for the optimal reactive power control problem using the fuzzy set theory. The objectives are to minimize real power losses and improve the voltage profile of a given system. Transmission loses are expressed in terms of voltage increments by relating the control variables, i.e., tap positions of transformers and reactive power injections of VAR sources, to the voltage increments in a modified Jacobian matrix. This specific formulation of the problem does not require the Jacobian matrix inversion, and hence it will save computation time and memory space. The objective function and the constraints are modeled by fuzzy sets. Linear membership functions of the fuzzy sets are defined and the fuzzy linear optimization problem is formulated. The solution space in this case is defined as the intersection of the fuzzy sets describing the constraints and the objective functions. Each solution is characterized by a parameter that determines the degree of satisfaction with the solution. The optimal solution is the one with the maximum value for the satisfaction parameter. Results for the application of this approach on test systems reveal its numerous advantages.
Fundamental role of bistability in optimal homeostatic control
NASA Astrophysics Data System (ADS)
Wang, Guanyu
2013-03-01
Bistability is a fundamental phenomenon in nature and has a number of fine properties. However, these properties are consequences of bistability at the physiological level, which do not explain why it had to emerge during evolution. Using optimal homeostasis as the first principle and Pontryagin's Maximum Principle as the optimization approach, I find that bistability emerges as an indispensable control mechanism. Because the mathematical model is general and the result is independent of parameters, it is likely that most biological systems use bistability to control homeostasis. Glucose homeostasis represents a good example. It turns out that bistability is the only solution to a dilemma in glucose homeostasis: high insulin efficiency is required for rapid plasma glucose clearance, whereas an insulin sparing state is required to guarantee the brain's safety during fasting. This new perspective can illuminate studies on the twin epidemics of obesity and diabetes and the corresponding intervening strategies. For example, overnutrition and sedentary lifestyle may represent sudden environmental changes that cause the lose of optimality, which may contribute to the marked rise of obesity and diabetes in our generation.
Optimal control and cold war dynamics between plant and herbivore.
Low, Candace; Ellner, Stephen P; Holden, Matthew H
2013-08-01
Herbivores eat the leaves that a plant needs for photosynthesis. However, the degree of antagonism between plant and herbivore may depend critically on the timing of their interactions and the intrinsic value of a leaf. We present a model that investigates whether and when the timing of plant defense and herbivore feeding activity can be optimized by evolution so that their interactions can move from antagonistic to neutral. We assume that temporal changes in environmental conditions will affect intrinsic leaf value, measured as potential carbon gain. Using optimal-control theory, we model herbivore evolution, first in response to fixed plant strategies and then under coevolutionary dynamics in which the plant also evolves in response to the herbivore. In the latter case, we solve for the evolutionarily stable strategies of plant defense induction and herbivore hatching rate under different ecological conditions. Our results suggest that the optimal strategies for both plant and herbivore are to avoid direct conflict. As long as the plant has the capability for moderately lethal defense, the herbivore will modify its hatching rate to avoid plant defenses, and the plant will never have to use them. Insights from this model offer a possible solution to the paradox of sublethal defenses and provide a mechanism for stable plant-herbivore interactions without the need for natural enemy control. PMID:23852361
Structural/control system optimization with variable actuator masses
NASA Technical Reports Server (NTRS)
Jin, Ik M.; Sepulveda, Abdon E.
1993-01-01
A method is presented to integrate the design space for structural/control system optimization problems in the case of linear state feedback control. Nonstructural lumped masses and control system design variables as well as structural sizing variables are all treated equally as independent design variables in the optimization process. Structural and control design variable linking schemes are used in order to avoid a prohibitively large increase in the total number of independent design variables. When actuator masses are treated as nonstructural lumped mass design variables, special consideration is given to the relation between the transient peak responses and the required actuator masses which is formulated as a behavior constraint form. The original nonlinear mathematical programming problem based on a finite element formulation and linear state feedback is replaced by a sequence of explicit approximate problems exploiting various approximation concepts such as design variable linkings, temporary constraint deletion and first order Taylor series expansion of nonlinear behavior constraints in terms of intermediate design variables. Examples which involve a variety of dynamic behavior constraints (including constraints on closed-loop eigenvalues, peak transient displacements, peak actuator forces, and relations between the peak responses and the actuator masses) are effectively solved by using the method presented.
Escobar-Ramirez, Adelma; Vercoutter-Edouart, Anne-Sophie; Mortuaire, Marlène; Huvent, Isabelle; Hardivillé, Stephan; Hoedt, Esthelle; Lefebvre, Tony; Pierce, Annick
2015-01-01
Delta-lactoferrin is a transcription factor, the expression of which is downregulated or silenced in case of breast cancer. It possesses antitumoral activities and when it is re-introduced in mammary epithelial cancer cell lines, provokes antiproliferative effects. It is posttranslationally modified and our earlier investigations showed that the O-GlcNAcylation/phosphorylation interplay plays a major role in the regulation of both its stability and transcriptional activity. Here, we report the covalent modification of delta-lactoferrin with the small ubiquitin-like modifier SUMO-1. Mutational and reporter gene analyses identified five different lysine residues at K13, K308, K361, K379 and K391 as SUMO acceptor sites. The SUMOylation deficient M5S mutant displayed enhanced transactivation capacity on a delta-lactoferrin responsive promoter, suggesting that SUMO-1 negatively regulates the transactivation function of delta-lactoferrin. K13, K308 and K379 are the main SUMO sites and among them, K308, which is located in a SUMOylation consensus motif of the NDSM-like type, is a key SUMO site involved in repression of delta-lactoferrin transcriptional activity. K13 and K379 are both targeted by other posttranslational modifications. We demonstrated that K13 is the main acetylation site and that favoring acetylation at K13 reduced SUMOylation and increased delta-lactoferrin transcriptional activity. K379, which is either ubiquitinated or SUMOylated, is a pivotal site for the control of delta-lactoferrin stability. We showed that SUMOylation competes with ubiquitination and protects delta-lactoferrin from degradation by positively regulating its stability. Collectively, our results indicate that multi-SUMOylation occurs on delta-lactoferrin to repress its transcriptional activity. Reciprocal occupancy of K13 by either SUMO-1 or an acetyl group may contribute to the establishment of finely regulated mechanisms to control delta-lactoferrin transcriptional activity. Moreover
Spacecraft flight control with the new phase space control law and optimal linear jet select
NASA Technical Reports Server (NTRS)
Bergmann, E. V.; Croopnick, S. R.; Turkovich, J. J.; Work, C. C.
1977-01-01
An autopilot designed for rotation and translation control of a rigid spacecraft is described. The autopilot uses reaction control jets as control effectors and incorporates a six-dimensional phase space control law as well as a linear programming algorithm for jet selection. The interaction of the control law and jet selection was investigated and a recommended configuration proposed. By means of a simulation procedure the new autopilot was compared with an existing system and was found to be superior in terms of core memory, central processing unit time, firings, and propellant consumption. But it is thought that the cycle time required to perform the jet selection computations might render the new autopilot unsuitable for existing flight computer applications, without modifications. The new autopilot is capable of maintaining attitude control in the presence of a large number of jet failures.
NASA Astrophysics Data System (ADS)
Lal, Surbhi; Goodrich, Glenn P.; Brinson, Bruce E.; Halas, N. J.
2004-03-01
It is well known that a variety of fundamental photophysical processes, such as absorption, fluorescence, and Raman scattering, are greatly substantially modified in the vicinity of metal surfaces or structures such as gratings, island films or colloids. [1] The collective electromagnetic resonances, or plasmon resonances, supported by metallic structures, as well as modifications in the local electromagnetic mode density near these structures, are responsible for influencing the radiating dipole of vicinal fluorophores. Nanoshells are dielectric core-metal shell nanoparticles whose plasmon resonance can be controllably tuned by varying the relative dimensions of its core and shell layers [2]. Nanoshells provide a practical substrate for the systematic investigation of the role of the plasmon-induced near field in fluorescence enhancement and quenching. We have fabricated two systems for the study of lanthanide ions and molecular fluorophores, respectively, at controlled distances above a nanoshell surface. Initial results examining the fluorophore-metal distance dependence and dependence on plasmon resonance detuning with respect to excitations in the fluorophore will be discussed. [1] Moskovits, M., Rev. Mod. Phys. 57, 783 (1985) [2] S. Oldenburg, R. D. Averitt, S. Westcott, and N. J. Halas, Chem. Phys. Lett. 288, 243 (1998); E. Prodan, C. Radloff, N. J. Halas and P. J. Nordlander, Science 301, 419 (2003).
Chen, Jun; Hu, Lei; Deng, Jinxia; Xing, Xianran
2015-06-01
Negative thermal expansion (NTE) is an intriguing physical property of solids, which is a consequence of a complex interplay among the lattice, phonons, and electrons. Interestingly, a large number of NTE materials have been found in various types of functional materials. In the last two decades good progress has been achieved to discover new phenomena and mechanisms of NTE. In the present review article, NTE is reviewed in functional materials of ferroelectrics, magnetics, multiferroics, superconductors, temperature-induced electron configuration change and so on. Zero thermal expansion (ZTE) of functional materials is emphasized due to the importance for practical applications. The NTE functional materials present a general physical picture to reveal a strong coupling role between physical properties and NTE. There is a general nature of NTE for both ferroelectrics and magnetics, in which NTE is determined by either ferroelectric order or magnetic one. In NTE functional materials, a multi-way to control thermal expansion can be established through the coupling roles of ferroelectricity-NTE, magnetism-NTE, change of electron configuration-NTE, open-framework-NTE, and so on. Chemical modification has been proved to be an effective method to control thermal expansion. Finally, challenges and questions are discussed for the development of NTE materials. There remains a challenge to discover a "perfect" NTE material for each specific application for chemists. The future studies on NTE functional materials will definitely promote the development of NTE materials. PMID:25864730
Optimization and planning of emergency evacuation routes considering traffic control.
Li, Guo; Zhang, Lijun; Wang, Zhaohua
2014-01-01
Emergencies, especially major ones, happen fast, randomly, as well as unpredictably, and generally will bring great harm to people's life and the economy. Therefore, governments and lots of professionals devote themselves to taking effective measures and providing optimal evacuation plans. This paper establishes two different emergency evacuation models on the basis of the maximum flow model (MFM) and the minimum-cost maximum flow model (MC-MFM), and proposes corresponding algorithms for the evacuation from one source node to one designated destination (one-to-one evacuation). Ulteriorly, we extend our evaluation model from one source node to many designated destinations (one-to-many evacuation). At last, we make case analysis of evacuation optimization and planning in Beijing, and obtain the desired evacuation routes and effective traffic control measures from the perspective of sufficiency and practicability. Both analytical and numerical results support that our models are feasible and practical. PMID:24991636
Optimization and Planning of Emergency Evacuation Routes Considering Traffic Control
Zhang, Lijun; Wang, Zhaohua
2014-01-01
Emergencies, especially major ones, happen fast, randomly, as well as unpredictably, and generally will bring great harm to people's life and the economy. Therefore, governments and lots of professionals devote themselves to taking effective measures and providing optimal evacuation plans. This paper establishes two different emergency evacuation models on the basis of the maximum flow model (MFM) and the minimum-cost maximum flow model (MC-MFM), and proposes corresponding algorithms for the evacuation from one source node to one designated destination (one-to-one evacuation). Ulteriorly, we extend our evaluation model from one source node to many designated destinations (one-to-many evacuation). At last, we make case analysis of evacuation optimization and planning in Beijing, and obtain the desired evacuation routes and effective traffic control measures from the perspective of sufficiency and practicability. Both analytical and numerical results support that our models are feasible and practical. PMID:24991636
Towards Quantum Cybernetics:. Optimal Feedback Control in Quantum Bio Informatics
NASA Astrophysics Data System (ADS)
Belavkin, V. P.
2009-02-01
A brief account of the quantum information dynamics and dynamical programming methods for the purpose of optimal control in quantum cybernetics with convex constraints and cońcave cost and bequest functions of the quantum state is given. Consideration is given to both open loop and feedback control schemes corresponding respectively to deterministic and stochastic semi-Markov dynamics of stable or unstable systems. For the quantum feedback control scheme with continuous observations we exploit the separation theorem of filtering and control aspects for quantum stochastic micro-dynamics of the total system. This allows to start with the Belavkin quantum filtering equation and derive the generalized Hamilton-Jacobi-Bellman equation using standard arguments of classical control theory. This is equivalent to a Hamilton-Jacobi equation with an extra linear dissipative term if the control is restricted to only Hamiltonian terms in the filtering equation. A controlled qubit is considered as an example throughout the development of the formalism. Finally, we discuss optimum observation strategies to obtain a pure quantum qubit state from a mixed one.
Quantum demolition filtering and optimal control of unstable systems.
Belavkin, V P
2012-11-28
A brief account of the quantum information dynamics and dynamical programming methods for optimal control of quantum unstable systems is given to both open loop and feedback control schemes corresponding respectively to deterministic and stochastic semi-Markov dynamics of stable or unstable systems. For the quantum feedback control scheme, we exploit the separation theorem of filtering and control aspects as in the usual case of quantum stable systems with non-demolition observation. This allows us to start with the Belavkin quantum filtering equation generalized to demolition observations and derive the generalized Hamilton-Jacobi-Bellman equation using standard arguments of classical control theory. This is equivalent to a Hamilton-Jacobi equation with an extra linear dissipative term if the control is restricted to Hamiltonian terms in the filtering equation. An unstable controlled qubit is considered as an example throughout the development of the formalism. Finally, we discuss optimum observation strategies to obtain a pure quantum qubit state from a mixed one. PMID:23091216
Modelling Optimal Control of Cholera in Communities Linked by Migration.
Njagarah, J B H; Nyabadza, F
2015-01-01
A mathematical model for the dynamics of cholera transmission with permissible controls between two connected communities is developed and analysed. The dynamics of the disease in the adjacent communities are assumed to be similar, with the main differences only reflected in the transmission and disease related parameters. This assumption is based on the fact that adjacent communities often have different living conditions and movement is inclined toward the community with better living conditions. Community specific reproduction numbers are given assuming movement of those susceptible, infected, and recovered, between communities. We carry out sensitivity analysis of the model parameters using the Latin Hypercube Sampling scheme to ascertain the degree of effect the parameters and controls have on progression of the infection. Using principles from optimal control theory, a temporal relationship between the distribution of controls and severity of the infection is ascertained. Our results indicate that implementation of controls such as proper hygiene, sanitation, and vaccination across both affected communities is likely to annihilate the infection within half the time it would take through self-limitation. In addition, although an infection may still break out in the presence of controls, it may be up to 8 times less devastating when compared with the case when no controls are in place. PMID:26246850
Optimal control of diarrhea transmission in a flood evacuation zone
NASA Astrophysics Data System (ADS)
Erwina, N.; Aldila, D.; Soewono, E.
2014-03-01
Evacuation of residents and diarrhea disease outbreak in evacuation zone have become serious problem that frequently happened during flood periods. Limited clean water supply and infrastructure in evacuation zone contribute to a critical spread of diarrhea. Transmission of diarrhea disease can be reduced by controlling clean water supply and treating diarrhea patients properly. These treatments require significant amount of budget, which may not be fulfilled in the fields. In his paper, transmission of diarrhea disease in evacuation zone using SIRS model is presented as control optimum problem with clean water supply and rate of treated patients as input controls. Existence and stability of equilibrium points and sensitivity analysis are investigated analytically for constant input controls. Optimum clean water supply and rate of treatment are found using optimum control technique. Optimal results for transmission of diarrhea and the corresponding controls during the period of observation are simulated numerically. The optimum result shows that transmission of diarrhea disease can be controlled with proper combination of water supply and rate of treatment within allowable budget.
Modelling Optimal Control of Cholera in Communities Linked by Migration
Njagarah, J. B. H.; Nyabadza, F.
2015-01-01
A mathematical model for the dynamics of cholera transmission with permissible controls between two connected communities is developed and analysed. The dynamics of the disease in the adjacent communities are assumed to be similar, with the main differences only reflected in the transmission and disease related parameters. This assumption is based on the fact that adjacent communities often have different living conditions and movement is inclined toward the community with better living conditions. Community specific reproduction numbers are given assuming movement of those susceptible, infected, and recovered, between communities. We carry out sensitivity analysis of the model parameters using the Latin Hypercube Sampling scheme to ascertain the degree of effect the parameters and controls have on progression of the infection. Using principles from optimal control theory, a temporal relationship between the distribution of controls and severity of the infection is ascertained. Our results indicate that implementation of controls such as proper hygiene, sanitation, and vaccination across both affected communities is likely to annihilate the infection within half the time it would take through self-limitation. In addition, although an infection may still break out in the presence of controls, it may be up to 8 times less devastating when compared with the case when no controls are in place. PMID:26246850
Hybrid intelligent control concepts for optimal data fusion
NASA Astrophysics Data System (ADS)
Llinas, James
1994-02-01
In the post-Cold War era, Naval surface ship operations will be largely conducted in littoral waters to support regional military missions of all types, including humanitarian and evacuation activities, and amphibious mission execution. Under these conditions, surface ships will be much more isolated and vulnerable to a variety of threats, including maneuvering antiship missiles. To deal with these threats, the optimal employment of multiple shipborne sensors for maximum vigilance is paramount. This paper characterizes the sensor management problem as one of intelligent control, identifies some of the key issues in controller design, and presents one approach to controller design which is soon to be implemented and evaluated. It is argued that the complexity and hierarchical nature of problem formulation demands a hybrid combination of knowledge-based methods and scheduling techniques from 'hard' real-time systems theory for its solution.
Optimizing pain control through the use of implantable pumps
Ilias, Wilfried; Todoroff, Boris
2008-01-01
Intrathecal therapy represents an effective and well established treatment of nonmalignant as well as malignant pain. Devices available include mechanical constant flow pumps as well as electronic variable flow pumps with patient-controlled bolus release. The latter provide faster dose finding, individual pain control, and good acceptance by patients. New technologies such as membrane pumps and rechargeable devices are expected to be developed to clinical perfection. The available drugs for intrathecal therapy are listed according to the polyanalgesic consensus on intrathecal therapy. The integration of remote patient-controlled analgesia into electronic implantable devices, and the peptide analgesic ziconotide, have significantly improved intrathecal therapy. Complications include infections, catheter ruptures or disconnections, catheter granulomas, and technical dysfunctions. Further possibilities for optimizing intrathecal therapy include development of new drugs, drug side effects, catheter and pump technologies, and surgical techniques. PMID:22915907
Optimal control of CPR procedure using hemodynamic circulation model
Lenhart, Suzanne M.; Protopopescu, Vladimir A.; Jung, Eunok
2007-12-25
A method for determining a chest pressure profile for cardiopulmonary resuscitation (CPR) includes the steps of representing a hemodynamic circulation model based on a plurality of difference equations for a patient, applying an optimal control (OC) algorithm to the circulation model, and determining a chest pressure profile. The chest pressure profile defines a timing pattern of externally applied pressure to a chest of the patient to maximize blood flow through the patient. A CPR device includes a chest compressor, a controller communicably connected to the chest compressor, and a computer communicably connected to the controller. The computer determines the chest pressure profile by applying an OC algorithm to a hemodynamic circulation model based on the plurality of difference equations.
Finite element solution of optimal control problems with inequality constraints
NASA Technical Reports Server (NTRS)
Bless, Robert R.; Hodges, Dewey H.
1990-01-01
A finite-element method based on a weak Hamiltonian form of the necessary conditions is summarized for optimal control problems. Very crude shape functions (so simple that element numerical quadrature is not necessary) can be used to develop an efficient procedure for obtaining candidate solutions (i.e., those which satisfy all the necessary conditions) even for highly nonlinear problems. An extension of the formulation allowing for discontinuities in the states and derivatives of the states is given. A theory that includes control inequality constraints is fully developed. An advanced launch vehicle (ALV) model is presented. The model involves staging and control constraints, thus demonstrating the full power of the weak formulation to date. Numerical results are presented along with total elapsed computer time required to obtain the results. The speed and accuracy in obtaining the results make this method a strong candidate for a real-time guidance algorithm.
Optimal feedback control of a bioreactor with a remote sensor
NASA Technical Reports Server (NTRS)
Niranjan, S. C.; San, K. Y.
1988-01-01
Sensors used to monitor bioreactor conditions directly often perform poorly in the face of adverse nonphysiological conditions. One way to circumvent this is to use a remote sensor block. However, such a configuration usually causes a significant time lag between measurements and the actual state values. Here, the problem of implementing feedback control strategies for such systems, described by nonlinear equations, is addressed. The problem is posed as an optimal control problem with a linear quadratic performance index. The linear control law so obtained is used to implement feedback. A global linearization technique as well as an expansion using Taylor series is used to linearize the nonlinear system, and the feedback is subsequently implemented.
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.
Optimal control of electric drive with simultaneous control inputs for motor current and flux
NASA Astrophysics Data System (ADS)
Pansyuk, V. I.
1984-08-01
A detailed mathematical analysis of the optimal control of a dc electric drive with a variable magnetic flux is presented. Expressions are found for the optimal controller. When this controller uses real time microprocessors control hardware, formulas are also derived for the various portions of the optimal process as well as the logic expressions for the switching of these parts of the process. The resulting optimal process differs from previous determinations in that the braking portion, when a resistance moment is present, contains a free run-down (passive braking) region, before and after which there can be regions of active braking, when the motor produces an electromagnetic moment. In one numerical example of step dc motor control, which is used to compare the optimal process found here with one developed earlier, power losses are found to be reduced by 5.44% with the new process. The entire solution of the problem using the procedure presented here reduces to finding the conditional extremum of some function of several variables whose number is no greater than the dimensionality of the system and does not lead to a boundary value problem.
Rear-heavy car control by adaptive linear optimal preview
NASA Astrophysics Data System (ADS)
Thommyppillai, M.; Evangelou, S.; Sharp, R. S.
2010-05-01
Adaptive linear optimal preview control theory is applied to a simple but non-linear car model, with parameters chosen to make the rear axle saturate first in any quasi-steady manoeuvre. The tendency of such a car to spin above a critical speed, which is a function of its running state, causes control to be especially difficult when operating near to the limit of the rear-axle force system. As in previous work, trim states and optimal gains are computed off-line for a given speed and a full range of lateral accelerations. Gain-scheduling with interpolation over trims and gain sets is used to keep the control appropriate to the running conditions, as they change. Simulations of manoeuvres are used to test and demonstrate the system capability. It is shown that utilising the rear-axle lateral-slip ratio as the scheduling variable, in the case of this rear-heavy car, gives excellent tracking, even when the tyres are run close to full saturation. It is implied by this and previous work that the general case can be treated effectively by monitoring both front- and rear-axle slips and scheduling on a worst-case basis.
Intelligent controller for optimized sootblowing. Phase 2 results
Bangham, M.; Patton, J.; Abeledo, H.; Liberatore, I.
1998-07-01
This paper summarizes results generated during Phase 2 of a Small-business Technology Transfer (STTR) project entitled Intelligent Controller for Optimized Sootblowing (ICOS), funded by the US Department of Energy. The project was conducted by DHR Technologies, a Division of OAO Technologies Solutions, Inc. (DHR) and the Operations Research Department at the George Washington University (GWU), with support from Baltimore Gas and Electric Company's Brandon Shores Station Unit No. 1 (BSU1). The objective of the project is to advance the state-of-the-art in automated sootblowing control for large coal-fired utility boilers. The results of the Phase 2 study suggest that the maximum possible efficiency improvement, which could potentially be gained at a large coal-fired unit using an optimized sootblowing controller, is on the order of about 60--80 Btu/kWh, depending on load. An improvement of this magnitude, which translates into yearly fuel savings of about $700,000 for a large unit, could potentially be attained at a poorly operated unit. At a well-run unit, such as BGE's Brandon Shores Unit No. 1, the potential savings are more modest, about 10 Btu/kWh. For BSU1, this potential improvement equates to fuel savings of about $60,000 per year.