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.
Bahrami, Arash; Tonelli, Marco; Sahu, Sarata C; Singarapu, Kiran K; Eghbalnia, Hamid R; Markley, John L
2012-01-01
ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. With a [(13)C,(15)N]-labeled protein sample loaded into the NMR spectrometer, ADAPT-NMR delivers complete backbone resonance assignments and secondary structure in an optimal fashion without human intervention. ADAPT-NMR achieves this by implementing a strategy in which the goal of optimal assignment in each step determines the subsequent step by analyzing the current sum of available data. ADAPT-NMR is the first iterative and fully automated approach designed specifically for the optimal assignment of proteins with fast data collection as a byproduct of this goal. ADAPT-NMR evaluates the current spectral information, and uses a goal-directed objective function to select the optimal next data collection step(s) and then directs the NMR spectrometer to collect the selected data set. ADAPT-NMR extracts peak positions from the newly collected data and uses this information in updating the analysis resonance assignments and secondary structure. The goal-directed objective function then defines the next data collection step. The procedure continues until the collected data support comprehensive peak identification, resonance assignments at the desired level of completeness, and protein secondary structure. We present test cases in which ADAPT-NMR achieved results in two days or less that would have taken two months or more by manual approaches. PMID:22427982
Optimism versus Pessimism and Academic Achievement Evaluation
ERIC Educational Resources Information Center
Harpaz-Itay, Yifat; Kaniel, Shlomo
2012-01-01
This article integrates three central theories of optimism-pessimism (OP). The combination of the shared components of these theories--outcome expectancies, emotions, and behavioral intention--may produce an integrative academic achievement evaluation. Little has been written regarding the differentiation between general and domain-specific OP, a…
Academic Optimism and Student Achievement in Urban Elementary Schools
ERIC Educational Resources Information Center
Smith, Page A.; Hoy, Wayne K.
2007-01-01
Purpose: The aim of this study was two-fold: to demonstrate a general construct of schools called academic optimism and to show it was related to student achievement in urban elementary schools, even controlling for socioeconomic factors, and school size. Design/methodology/approach: Data were collected from 99 urban elementary schools in Texas…
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.
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 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.
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.
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.
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.
The Effects of Academic Optimism on Elementary Reading Achievement
ERIC Educational Resources Information Center
Bevel, Raymona K.; Mitchell, Roxanne M.
2012-01-01
Purpose: The purpose of this paper is to explore the relationship between academic optimism (AO) and elementary reading achievement (RA). Design/methodology/approach: Using correlation and hierarchical linear regression, the authors examined school-level effects of AO on fifth grade reading achievement in 29 elementary schools in Alabama.…
Optimal achieved blood pressure in acute intracerebral hemorrhage
Arima, Hisatomi; Heeley, Emma; Delcourt, Candice; Hirakawa, Yoichiro; Wang, Xia; Woodward, Mark; Robinson, Thompson; Stapf, Christian; Parsons, Mark; Lavados, Pablo M.; Huang, Yining; Wang, Jiguang; Chalmers, John
2015-01-01
Objectives: To investigate the effects of intensive blood pressure (BP) lowering according to baseline BP levels and optimal achieved BP levels in patients with acute intracerebral hemorrhage (ICH). Methods: INTERACT2 was an open, blinded endpoint, randomized controlled trial in 2,839 patients with ICH within 6 hours of onset and elevated systolic BP (SBP) (150–220 mm Hg) who were allocated to receive intensive (target SBP <140 mm Hg within 1 hour, with lower limit of 130 mm Hg for treatment cessation) or guideline-recommended (target SBP <180 mm Hg) BP-lowering treatment. Outcome was physical function across all 7 levels of the modified Rankin Scale at 90 days. Results: Analysis of the randomized comparisons showed that intensive BP lowering produced comparable benefits on physical function at 90 days in 5 subgroups defined by baseline SBP of <160, 160–169, 170–179, 180–189, and ≥190 mm Hg (p homogeneity = 0.790). Analyses of achieved BP showed linear increases in the risk of physical dysfunction for achieved SBP above 130 mm Hg for both hyperacute (1–24 hours) and acute (2–7 days) phases while modest increases were also observed for achieved SBP below 130 mm Hg. Conclusions: Intensive BP lowering appears beneficial across a wide range of baseline SBP levels, and target SBP level of 130–139 mm Hg is likely to provide maximum benefit in acute ICH. Classification of evidence: This study provides Class I evidence that the effect of intensive BP lowering on physical function is not influenced by baseline BP. PMID:25552575
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
BIOMONITORING TO ACHIEVE CONTROL OF TOXIC EFFLUENTS
This 48 - page Technology Transfer Report provides a case study of how water quality-based toxicity control procedures can be combined with chemical analyses and biological stream surveys to achieve more effective water pollution control. t describes how regulatory agencies used ...
Collective Responsibility, Academic Optimism, and Student Achievement in Taiwan Elementary Schools
ERIC Educational Resources Information Center
Wu, Hsin-Chieh
2012-01-01
Previous research indicates that collective efficacy, faculty trust in students and parents, and academic emphasis together formed a single latent school construct, called academic optimism. In the U.S., academic optimism has been proven to be a powerful construct that could effectively predict student achievement even after controlling for…
Achievements of schistosomiasis control in China.
Yuan, Hongchang; Jiang, Qingwu; Zhao, Genming; He, Na
2002-01-01
The control of schistosomiasis has been spectacularly successful in terms of controlling endemicity and severity of the disease during the last 50 years. It can be categorized into two stages. From 1955 through 1980, the transmission-control strategy had been widely and successfully carried out. By the end of 1980, the epidemic of schistosomiasis was successfully circumscribed in certain core regions including areas at the middle and low reaches of the Yangtze River and some mountainous areas in Sichuan and Yunnan provinces, where control of schistosomiasis had been demonstrated to be very difficult to be sustained. Therefore, since 1980, schistosomiasis control in China has been modified to employ a stepwise strategy, based on which morbidity control has been given priorities and if possible transmission control has been pursued. However, since snail-ridden areas remain unchanged so far, reinfections occur frequently. This necessitates a maintenance phase to consolidate the achievements in the control of schistosomiasis. In the mean time, we are challenged with some environmental, social and economical changes in terms of controlling schistosomiasis. Successfully controlling schistosomiasis in China is still a long-term task but will be achieved without doubt along with the economic development and the promotion of living and cultural standard of people. PMID:12426618
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.
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 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.
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.
Malaria control: achievements, problems and strategies.
Nájera, J A
2001-06-01
Even if history has not always been the Magistra vitae, Cicero expected it to be, it should provide, as Baas said, a mirror in which to observe and compare the past and present in order to draw therefrom well-grounded conclusions for the future. Based on this belief, this paper aims to provide an overview of the foundations and development of malaria control policies during the XX century. It presents an analysis of the conflicting tendencies which shaped the development of these policies and which appear to have oscillated between calls for frontal attack in an all-out campaign and calls for sustainable gains, even if slow. It discusses the various approaches to the control of malaria, their achievements and their limitations, not only to serve as a background to understand better the foundations of current policies, but also to prevent that simplistic generalisations may again lead to exaggerated expectations and disillusion. The first part of the paper is devoted to the development of malaria control during the first half of the century, characterised by the ups and downs in the reliance on mosquito control as the control measure applicable everywhere. The proliferation of "man-made-malaria", which accompanied the push for economic development in most of the endemic countries, spurred the need for control interventions and, while great successes were obtained in many specific projects, the general campaigns proposed by the enthusiasts of vector control faced increasing difficulties in their practical implementation in the field. Important events, which may be considered representative of this period are, on the campaign approach, the success of Gorgas in the Panama Canal, but also the failure of the Mian Mir project in India; while on the developmental approach, the Italian and Dutch schools of malariology, the Tennessee Valley and the development of malaria sanitation, included the so called species sanitation. The projection of these developments to a global
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.
Translational geroscience: emphasizing function to achieve optimal longevity.
Seals, Douglas R; Melov, Simon
2014-09-01
Among individuals, biological aging leads to cellular and organismal dysfunction and an increased risk of chronic degenerative diseases and disability. This sequence of events in combination with the projected increases in the number of older adults will result in a worldwide healthcare burden with dire consequences. Superimposed on this setting are the adults now reaching traditional retirement ages--the baby boomers--a group that wishes to remain active, productive and physically and cognitively fit as they grow older. Together, these conditions are producing an unprecedented demand for increased healthspan or what might be termed "optimal longevity"-to live long, but well. To meet this demand, investigators with interests in the biological aspects of aging from model organisms to human epidemiology (population aging) must work together within an interactive process that we describe astranslational geroscience. An essential goal of this new investigational platform should be the optimization and preservation of physiological function throughout the lifespan, including integrative physical and cognitive function, which would serve to increase healthspan, compress morbidity and disability into a shorter period of late-life, and help achieve optimal longevity. To most effectively utilize this new approach, we must rethink how investigators and administrators working at different levels of the translational research continuum communicate and collaborate with each other, how best to train the next generation of scientists in this new field, and how contemporary biological-biomedical aging research should be organized and funded. PMID:25324468
Translational Geroscience: Emphasizing function to achieve optimal longevity
Seals, Douglas R.; Melov, Simon
2014-01-01
Among individuals, biological aging leads to cellular and organismal dysfunction and an increased risk of chronic degenerative diseases and disability. This sequence of events in combination with the projected increases in the number of older adults will result in a worldwide healthcare burden with dire consequences. Superimposed on this setting are the adults now reaching traditional retirement ages--the baby boomers--a group that wishes to remain active, productive and physically and cognitively fit as they grow older. Together, these conditions are producing an unprecedented demand for increased healthspan or what might be termed “optimal longevity”—to live long, but well. To meet this demand, investigators with interests in the biological aspects of aging from model organisms to human epidemiology (population aging) must work together within an interactive process that we describe as translational geroscience. An essential goal of this new investigational platform should be the optimization and preservation of physiological function throughout the lifespan, including integrative physical and cognitive function, which would serve to increase healthspan, compress morbidity and disability into a shorter period of late-life, and help achieve optimal longevity. To most effectively utilize this new approach, we must rethink how investigators and administrators working at different levels of the translational research continuum communicate and collaborate with each other, how best to train the next generation of scientists in this new field, and how contemporary biological-biomedical aging research should be organized and funded. PMID:25324468
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.
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.
ERIC Educational Resources Information Center
Michou, Aikaterini; Vansteenkiste, Maarten; Mouratidis, Athanasios; Lens, Willy
2014-01-01
Background: The hierarchical model of achievement motivation presumes that achievement goals channel the achievement motives of need for achievement and fear of failure towards motivational outcomes. Yet, less is known whether autonomous and controlling reasons underlying the pursuit of achievement goals can serve as additional pathways between…
Optimized Delivery System Achieves Enhanced Endomyocardial Stem Cell Retention
Behfar, Atta; Latere, Jean-Pierre; Bartunek, Jozef; Homsy, Christian; Daro, Dorothee; Crespo-Diaz, Ruben J.; Stalboerger, Paul G.; Steenwinckel, Valerie; Seron, Aymeric; Redfield, Margaret M.; Terzic, Andre
2014-01-01
Background Regenerative cell-based therapies are associated with limited myocardial retention of delivered stem cells. The objective of this study is to develop an endocardial delivery system for enhanced cell retention. Methods and Results Stem cell retention was simulated in silico using one and three-dimensional models of tissue distortion and compliance associated with delivery. Needle designs, predicted to be optimal, were accordingly engineered using nitinol – a nickel and titanium alloy displaying shape memory and super-elasticity. Biocompatibility was tested with human mesenchymal stem cells. Experimental validation was performed with species-matched cells directly delivered into Langendorff-perfused porcine hearts or administered percutaneously into the endocardium of infarcted pigs. Cell retention was quantified by flow cytometry and real time quantitative polymerase chain reaction methodology. Models, computing optimal distribution of distortion calibrated to favor tissue compliance, predicted that a 75°-curved needle featuring small-to-large graded side holes would ensure the highest cell retention profile. In isolated hearts, the nitinol curved needle catheter (C-Cath) design ensured 3-fold superior stem cell retention compared to a standard needle. In the setting of chronic infarction, percutaneous delivery of stem cells with C-Cath yielded a 37.7±7.1% versus 10.0±2.8% retention achieved with a traditional needle, without impact on biocompatibility or safety. Conclusions Modeling guided development of a nitinol-based curved needle delivery system with incremental side holes achieved enhanced myocardial stem cell retention. PMID:24326777
Toward achieving optimal response: understanding and managing antidepressant side effects
Kelly, Karen; Posternak, Michael; Jonathan, E. Alpert
2008-01-01
The safety and tolerability of antidepressants have improved considerably over the past two decades, Nevertheless, antidepressant side effects are still common and problematic. The majority of patients treated with contemporary agents experience one or more bothersome side effects. These side effects often create barriers to achieving depressive remission, as well as to preventing relapse and recurrence. Clinicians tend to underestimate the prevalence of side effects, and as many as one quarter of patients discontinue their antidepressants because of difficult-to-tolerate side effects; others may continue on antidepressant therapy but experience diminished quality of life related to troublesome side effects. This article reviews the prevalence of side effects, the impact of side effects on treatment adherence, and methodological issues including the challenge of distinguishing side effects from residual depressive symptoms, discontinuation effects, and general medical problems. In addition, we address the most common side effects such as sexual dysfunction, gastrointestinal problems, sleep disturbance, apathy, and fatigue, and offer strategies for management that may help patients achieve optimal response to pharmacotherapy. PMID:19170398
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.
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.
ERIC Educational Resources Information Center
Daniels, Lia M.; Perry, Raymond P.; Stupnisky, Robert H.; Stewart, Tara L.; Newall, Nancy E. G.; Clifton, Rodney A.
2014-01-01
In the area of achievement motivation, students' beliefs pertaining to achievement goals and perceived control have separately guided a large amount theoretical and empirical research. However, limited research has considered the simultaneous effects of goals and control on achievement. The purpose of this study was to examine primary and…
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.
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
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
WFH: closing the global gap--achieving optimal care.
Skinner, Mark W
2012-07-01
For 50 years, the World Federation of Hemophilia (WFH) has been working globally to close the gap in care and to achieve Treatment for All patients, men and women, with haemophilia and other inherited bleeding disorders, regardless of where they might live. The WFH estimates that more than one in 1000 men and women has a bleeding disorder equating to 6,900,000 worldwide. To close the gap in care between developed and developing nations a continued focus on the successful strategies deployed heretofore will be required. However, in response to the rapid advances in treatment and emerging therapeutic advances on the horizon it will also require fresh approaches and renewed strategic thinking. It is difficult to predict what each therapeutic advance on the horizon will mean for the future, but there is no doubt that we are in a golden age of research and development, which has the prospect of revolutionizing treatment once again. An improved understanding of "optimal" treatment is fundamental to the continued evolution of global care. The challenges of answering government and payer demands for evidence-based medicine, and cost justification for the introduction and enhancement of treatment, are ever-present and growing. To sustain and improve care it is critical to build the body of outcome data for individual patients, within haemophilia treatment centers (HTCs), nationally, regionally and globally. Emerging therapeutic advances (longer half-life therapies and gene transfer) should not be justified or brought to market based only on the notion that they will be economically more affordable, although that may be the case, but rather more importantly that they will be therapeutically more advantageous. Improvements in treatment adherence, reductions in bleeding frequency (including microhemorrhages), better management of trough levels, and improved health outcomes (including quality of life) should be the foremost considerations. As part of a new WFH strategic plan
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.
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
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.
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.
On the Achievable Efficiency-Fairness Tradeoff in Utility-Optimal MAC Protocols
NASA Astrophysics Data System (ADS)
Lee, Jang-Won; Chiang, Mung; Calderbank, A. Robert
We use the network utility maximization (NUM) framework to create an efficient and fair medium access control (MAC) protocol for wireless networks. By adjusting the parameters in the utility objective functions of NUM problems, we control the tradeoff between efficiency and fairness of radio resource allocation through a rigorous and systematic design. In this paper, we propose a scheduling-based MAC protocol. Since it provides an upper-bound on the achievable performance, it establishes the optimality benchmarks for comparison with other algorithms in related work.
Estimates of Savings Achievable from Irrigation Controller
Williams, Alison; Fuchs, Heidi; Whitehead, Camilla Dunham
2014-03-28
This paper performs a literature review and meta-analysis of water savings from several types of advanced irrigation controllers: rain sensors (RS), weather-based irrigation controllers (WBIC), and soil moisture sensors (SMS).The purpose of this work is to derive average water savings per controller type, based to the extent possible on all available data. After a preliminary data scrubbing, we utilized a series of analytical filters to develop our best estimate of average savings. We applied filters to remove data that might bias the sample such as data self-reported by manufacturers, data resulting from studies focusing on high-water users, or data presented in a non-comparable format such as based on total household water use instead of outdoor water use. Because the resulting number of studies was too small to be statistically significant when broken down by controller type, this paper represents a survey and synthesis of available data rather than a definitive statement regarding whether the estimated water savings are representative.
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.
The optimal polarizations for achieving maximum contrast in radar images
NASA Technical Reports Server (NTRS)
Swartz, A. A.; Yueh, H. A.; Kong, J. A.; Novak, L. M.; Shin, R. T.
1988-01-01
There is considerable interest in determining the optimal polarizations that maximize contrast between two scattering classes in polarimetric radar images. A systematic approach is presented for obtaining the optimal polarimetric matched filter, i.e., that filter which produces maximum contrast between two scattering classes. The maximization procedure involves solving an eigenvalue problem where the eigenvector corresponding to the maximum contrast ratio is an optimal polarimetric matched filter. To exhibit the physical significance of this filter, it is transformed into its associated transmitting and receiving polarization states, written in terms of horizontal and vertical vector components. For the special case where the transmitting polarization is fixed, the receiving polarization which maximizes the contrast ratio is also obtained. Polarimetric filtering is then applies to synthetic aperture radar images obtained from the Jet Propulsion Laboratory. It is shown, both numerically and through the use of radar imagery, that maximum image contrast can be realized when data is processed with the optimal polarimeter matched filter.
ERIC Educational Resources Information Center
Kim, Kyoungho; Rohner, Ronald P.
2002-01-01
Explored the relationship between parenting style and academic achievement of Korean American adolescents, investigating the influence of perceived parental warmth and control and improvement in schooling. Survey data indicated that authoritative paternal parenting related to optimal academic achievement. Differences in maternal parenting styles…
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.
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.
Controlling open quantum systems: tools, achievements, and limitations
NASA Astrophysics Data System (ADS)
Koch, Christiane P.
2016-06-01
The advent of quantum devices, which exploit the two essential elements of quantum physics, coherence and entanglement, has sparked renewed interest in the control of open quantum systems. Successful implementations face the challenge of preserving relevant nonclassical features at the level of device operation. A major obstacle is decoherence, which is caused by interaction with the environment. Optimal control theory is a tool that can be used to identify control strategies in the presence of decoherence. Here we review recent advances in optimal control methodology that allow typical tasks in device operation for open quantum systems to be tackled and discuss examples of relaxation-optimized dynamics. Optimal control theory is also a useful tool to exploit the environment for control. We discuss examples and point out possible future extensions.
Controlling open quantum systems: tools, achievements, and limitations.
Koch, Christiane P
2016-06-01
The advent of quantum devices, which exploit the two essential elements of quantum physics, coherence and entanglement, has sparked renewed interest in the control of open quantum systems. Successful implementations face the challenge of preserving relevant nonclassical features at the level of device operation. A major obstacle is decoherence, which is caused by interaction with the environment. Optimal control theory is a tool that can be used to identify control strategies in the presence of decoherence. Here we review recent advances in optimal control methodology that allow typical tasks in device operation for open quantum systems to be tackled and discuss examples of relaxation-optimized dynamics. Optimal control theory is also a useful tool to exploit the environment for control. We discuss examples and point out possible future extensions. PMID:27143501
Aircraft optimization by a system approach: Achievements and trends
NASA Technical Reports Server (NTRS)
Sobieszczanski-Sobieski, Jaroslaw
1992-01-01
Recently emerging methodology for optimal design of aircraft treated as a system of interacting physical phenomena and parts is examined. The methodology is found to coalesce into methods for hierarchic, non-hierarchic, and hybrid systems all dependent on sensitivity analysis. A separate category of methods has also evolved independent of sensitivity analysis, hence suitable for discrete problems. References and numerical applications are cited. Massively parallel computer processing is seen as enabling technology for practical implementation of the methodology.
Multidisciplinary optimization for engineering systems: Achievements and potential
NASA Technical Reports Server (NTRS)
Sobieszczanski-Sobieski, Jaroslaw
1989-01-01
The currently common sequential design process for engineering systems is likely to lead to suboptimal designs. Recently developed decomposition methods offer an alternative for coming closer to optimum by breaking the large task of system optimization into smaller, concurrently executed and, yet, coupled tasks, identified with engineering disciplines or subsystems. The hierarchic and non-hierarchic decompositions are discussed and illustrated by examples. An organization of a design process centered on the non-hierarchic decomposition is proposed.
Achieving Optimal Privacy in Trust-Aware Social Recommender Systems
NASA Astrophysics Data System (ADS)
Dokoohaki, Nima; Kaleli, Cihan; Polat, Huseyin; Matskin, Mihhail
Collaborative filtering (CF) recommenders are subject to numerous shortcomings such as centralized processing, vulnerability to shilling attacks, and most important of all privacy. To overcome these obstacles, researchers proposed for utilization of interpersonal trust between users, to alleviate many of these crucial shortcomings. Till now, attention has been mainly paid to strong points about trust-aware recommenders such as alleviating profile sparsity or calculation cost efficiency, while least attention has been paid on investigating the notion of privacy surrounding the disclosure of individual ratings and most importantly protection of trust computation across social networks forming the backbone of these systems. To contribute to addressing problem of privacy in trust-aware recommenders, within this paper, first we introduce a framework for enabling privacy-preserving trust-aware recommendation generation. While trust mechanism aims at elevating recommender's accuracy, to preserve privacy, accuracy of the system needs to be decreased. Since within this context, privacy and accuracy are conflicting goals we show that a Pareto set can be found as an optimal setting for both privacy-preserving and trust-enabling mechanisms. We show that this Pareto set, when used as the configuration for measuring the accuracy of base collaborative filtering engine, yields an optimized tradeoff between conflicting goals of privacy and accuracy. We prove this concept along with applicability of our framework by experimenting with accuracy and privacy factors, and we show through experiment how such optimal set can be inferred.
Residential Mobility, Inhibitory Control, and Academic Achievement in Preschool
ERIC Educational Resources Information Center
Schmitt, Sara A.; Finders, Jennifer K.; McClelland, Megan M.
2015-01-01
Research Findings: The present study investigated the direct effects of residential mobility on children's inhibitory control and academic achievement during the preschool year. It also explored fall inhibitory control and academic skills as mediators linking residential mobility and spring achievement. Participants included 359 preschool…
Residential Mobility, Inhibitory Control, and Academic Achievement in Preschool
ERIC Educational Resources Information Center
Schmitt, Sara A.; Finders, Jennifer K.; McClelland, Megan M.
2015-01-01
The present study investigated the direct effects of residential mobility on children's inhibitory control and academic achievement during the preschool year. It also explored fall inhibitory control and academic skills as mediators linking residential mobility and spring achievement. Participants included 359 preschool children (49% female)…
Longitudinal Effects of Perceived Control on Academic Achievement
ERIC Educational Resources Information Center
You, Sukkyung; Hong, Sehee; Ho, Hsiu-Zu
2011-01-01
It is well established that perceived control plays an important role in student academic achievement, but little is known about its longitudinal stability, ethnic variation, and developmental effects on subsequent achievement during adolescence. Findings from this study indicated (a) perceived control remains stable during adolescence for each of…
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.
Gout: optimizing treatment to achieve a disease cure
Bernal, José Antonio; Quilis, Neus; Andrés, Mariano; Sivera, Francisca; Pascual, Eliseo
2016-01-01
Gout is one of the most common inflammatory arthritides. The disease is due to the deposition of monosodium urate crystals. These deposits are reversible with proper treatment, suggesting that gout is a curable disease. The main aim in gout is to lower serum uric acid levels to a pre-established target; there are different urate-lowering drugs (xanthine oxidase inhibitors, uricosurics and uricases) through which this can be achieved. Proper treatment of gout also involves correct management of acute flares and their prevention. To ensure treatment adherence it is necessary to explain to the patient what the objectives are. PMID:26977282
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.
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.
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
Multiphase Nano-Composite Coatings for Achieving Energy Optimization
Nainaparampil, Jose
2012-03-26
UES Inc. and ANL teamed in this work to develop novel coating systems for the protection of surfaces from thermal degradation mainly in two applications; Machining and Die casting. These coatings were specifically designed for the purpose by incorporating required material phases and the overall architecture, which led to reduce the energy usage and increase efficiency of the operations. Following the UES/ANL's feasibility work, the coatings were developed utilizing High power impulse magnetron sputtering (HiPMS) and Large area filtered arc deposition (LAFAD) techniques. Toughness, hardness and oxidation resistance: contrasting qualities have been mixed in the right proportion to attain the suitable material characteristic for the cause. Hafnium diboride (HfB2) based materials provided such a system and its properties were tamed to attain the right combination of toughness and hardness by working on the microstructure and architecture of coatings. An effective interfacing material (graded concentrations of topcoat) was also achieved in this work to provide the required adhesion between the substrate and the coating. Combination of an appropriate bond coat and a functional top coat provided the present thermal degradation resistant coating for cutting tools and die-casting applications. Laboratory level performance tests and industrial level application tests by partner companies (Beta Site Testing) were used for the development of these coatings.
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.
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.
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.
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.
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.
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
ERIC Educational Resources Information Center
Gadzella, Bernadette M.; And Others
The study investigated (a) relationships between measures on study habits and attitudes, locus of control, achieving tendency, and semester grade-point averages (SGPA), (b) differences between the sexes on the above mentioned variables, and (c) best predictor of SGPA. The subjects were 39 males and 81 females. There were a number of significant…
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.
The Impact of Locus of Control on Language Achievement
ERIC Educational Resources Information Center
Nodoushan, Mohammad Ali Salmani
2012-01-01
This study hypothesized that students' loci of control affected their language achievement. 198 (N = 198) EFL students took the Rotter's (1966) locus of control test and were classified as locus-internal (ni = 78), and locus-external (ne = 120). They then took their ordinary courses and at the end of the semester, they were given their exams.…
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.
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.
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.
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.
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.
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.
Purpose plus: supporting youth purpose, control, and academic achievement.
Pizzolato, Jane Elizabeth; Brown, Elizabeth Levine; Kanny, Mary Allison
2011-01-01
Research in the past decade suggests that a persistent achievement gap between students from low-income minority backgrounds and higher-income white backgrounds may be rooted in theories of student motivation and youth purpose. Yet limited research exists regarding the role of purpose on positive youth development as it pertains to academic achievement. Using a sample of 209 high school students, this study examines the effectiveness of an intervention designed to promote purpose development and internal control over academic success in high school students from a low-socioeconomic-status community. Findings reveal that a short-term intervention was effective in significantly increasing internal control over academic success and purpose in life for students participating in the intervention group. In addition, analysis of academic achievement for students who experienced positive gains in internal control and purpose demonstrates significant gains in academic achievement as measured by grade point average. Implications are made for further study of internal control and life purpose as a means of academic intervention in the effort to address the achievement gap. PMID:22275280
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
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.
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.
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.
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 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.
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.
Children's Effortful Control and Academic Achievement: Mediation through Social Functioning
ERIC Educational Resources Information Center
Valiente, Carlos; Eisenberg, Nancy; Haugen, Rg; Spinrad, Tracy L.; Hofer, Claire; Liew, Jeffrey; Kupfer, Anne
2011-01-01
Research Findings: The purpose of this study was to test the premise that children's effortful control (EC) is prospectively related to their academic achievement and to specify mechanisms through which EC is related to academic success. We used data from 214 children (M age at Time 1 [T1] = 73 months) to test whether social functioning (e.g.,…
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
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.
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.
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.
The purposes, achievements, and priorities of arms control
Brown, P.S.
1987-09-01
Arms control purposes include strengthening the framework of deterrence and reducing the threat of the use of nuclear weapons, reducing the dangers of attack and accidental nuclear war, and allowing more resources for the civilian economy. The paper briefly describes achievements in arms control since World War II. These include the Limited Test Ban Treaty (LTBT), Nonproliferation Treaty (NPT), Anti-Ballistic Missile Treaty (ABMT)-SALT I, SALT II, Threshold Test Ban Treaty (TTBT), Peaceful Nuclear Explosions Treaty (PNET), and Nuclear-Free Zones treaties. The author also discusses his views on what the priorities of arms control activities should be. (ACR)
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.
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.
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.
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.
Role of well-being therapy in achieving a balanced and individualized path to optimal functioning.
Ruini, Chiara; Fava, Giovanni A
2012-01-01
A specific psychotherapeutic strategy for increasing psychological well-being and resilience, well-being therapy (WBT), based on Ryff's conceptual model, has been developed and tested in a number of randomized controlled trials. The findings indicate that flourishing and resilience can be promoted by specific interventions leading to a positive evaluation of one's self, a sense of continued growth and development, the belief that life is purposeful and meaningful, the possession of quality relations with others, the capacity to manage effectively one's life and a sense of self-determination. A decreased vulnerability to depression, mood swings and anxiety has been demonstrated after WBT in high-risk populations. School interventions based on the principles of WBT have been found to yield both promotion of well-being and decrease of distress compared with control groups. The differential technical characteristics and indications of WBT are described, with a special reference to the promotion of an individualized and balanced path to achieve optimal human functioning, avoiding the polarities in positive psychological dimensions. PMID:22570318
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.
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 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 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
Achieving optimal aesthetics for direct and indirect restorations with microhybrid composite resins.
Okuda, Wynn H
2005-04-01
In aesthetic dentistry, material science has played a key role in the development of natural-appearing restorations. Despite the progress, there have been challenges in achieving a harmonious integration of direct and indirect posterior restorations. Although porcelain restorations provide natural aesthetics, ceramics cannot be applied via direct techniques. Consequently, composite resins are valuable alternatives for conservative posterior restorations. In addition, because of their differing physical and optical properties, optimal aesthetic blending with porcelain and resin cannot be routinely achieved. This article explores the potential of composite resins as a direct and indirect restorative option in achieving the most favorable natural blend in the posterior region. PMID:15974036
An active control strategy for achieving weak radiator structures
Naghshineh, K. . Acoustics and Radar Technology Lab.); Koopmann, G.H. . Center for Acoustics and Vibration)
1994-01-01
A general control strategy is presented for active suppression of total radiated sound power from harmonically excited structures based on the measurement of their response. Using the measured response of the structure together with knowledge of its structural mobility, and equivalent primary excitation force is found at discrete points along the structure. Using this equivalent primary force and performing a quadratic optimization of the power radiated form the structure, a set of control forces is found at selected points on the structure that results in minimum radiated sound power. A numerical example of this strategy is presented for a simply supported beam in a rigid baffle excited by a harmonic plane wave incident at an oblique angle. A comparison of the response of the beam with and without control forces shows a large reduction in the controlled response displacement magnitude. In addition, as the result of the action of the control forces, the magnitude of the wave number spectrum of the beam's response in the supersonic region is decreased substantially. The effect of the number and location of the actuators on reductions in sound power level is also studied. The actuators located at the anti-nodes of structural modes within the supersonic region together with those located near boundaries are found to be the most effective in controlling the radiation of sound from a structure.
ERIC Educational Resources Information Center
Wagner, Charles A.; DiPaola, Michael F.
2011-01-01
The purpose of this study is to build on an emergent research base for academic optimism by testing the construct and its relationship to student achievement and organizational citizenship behaviors in schools in a sample of public high schools. All participants in this study were full-time teachers, guidance counselors, and other full-time…
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.
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.
Optimally Scaled H(sub infinity) Full Information Control Synthesis with Real Uncertainty
NASA Technical Reports Server (NTRS)
Balas, Gary J.; Lind, Rick; Packard, Andy
1996-01-01
This paper presents an algorithm to synthesize optimal controllers for the scaled H(sub infinity). full information problem with real and complex uncertainty. The control problem is reduced to a linear matrix inequality which can be solved via a finite dimensional convex optimization. This technique is compared with the optimal scaled H(sub infinity). full information with only complex uncertainty and D - K iteration control design to synthesize controllers for a missile autopilot. Directly including real parametric uncertainty into the control design results in improved robust performance of the missile autopilot. The controller synthesized via D - K iteration achieves results similar to the optimal designs.
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.
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
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.
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.
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.
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.
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.
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.
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.
ERIC Educational Resources Information Center
Nikelshpur, Dmitry O.
2014-01-01
Similar to mammalian brains, Artificial Neural Networks (ANN) are universal approximators, capable of yielding near-optimal solutions to a wide assortment of problems. ANNs are used in many fields including medicine, internet security, engineering, retail, robotics, warfare, intelligence control, and finance. "ANNs have a tendency to get…
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.
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.
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).
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.
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.
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.
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.
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.
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.
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.
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
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.
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
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.
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.
ERIC Educational Resources Information Center
Kramer, Karen Z.
2012-01-01
Using a longitudinal US dataset (N = 6,134) we examine the relationship between parental behavioural control and academic achievement and explore the moderating role of parental involvement and parental warmth. Analyses using multiple hierarchical regression with clustering controls shows that parental behavioural control is negatively associated…
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.
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.
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
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.
Kudchadker, Rajat J.; Pugh, Thomas J.; Swanson, David A.; Bruno, Teresa L.; Bolukbasi, Yasemin; Frank, Steven J.
2012-01-01
Advances in brachytherapy treatment planning systems have allowed the opportunity for brachytherapy to be planned intraoperatively as well as preoperatively. The relative advantages and disadvantages of each approach have been the subject of extensive debate, and some contend that the intraoperative approach is vital to the delivery of optimal therapy. The purpose of this study was to determine whether high-quality permanent prostate implants can be achieved consistently using a preoperative planning approach that allows for, but does not necessitate, intraoperative optimization. To achieve this purpose, we reviewed the records of 100 men with intermediate-risk prostate cancer who had been prospectively treated with brachytherapy monotherapy between 2006 and 2009 at our institution. All patients were treated with iodine-125 stranded seeds; the planned target dose was 145 Gy. Only 8 patients required adjustments to the plan on the basis of intraoperative findings. Consistency and quality were assessed by calculating the correlation coefficient between the planned and implanted amounts of radioactivity and by examining the mean values of the dosimetric parameters obtained on preoperative and 30 days postoperative treatment planning. The amount of radioactivity implanted was essentially identical to that planned (mean planned radioactivity, 41.27 U vs. mean delivered radioactivity, 41.36 U; R{sup 2} = 0.99). The mean planned and day 30 prostate V100 values were 99.9% and 98.6%, respectively. The mean planned and day 30 prostate D90 values were 186.3 and 185.1 Gy, respectively. Consistent, high-quality prostate brachytherapy treatment plans can be achieved using a preoperative planning approach, mostly without the need for intraoperative optimization. Good quality assurance measures during simulation, treatment planning, implantation, and postimplant evaluation are paramount for achieving a high level of quality and consistency.
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.
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
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.
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.
One shot methods for optimal control of distributed parameter systems 1: Finite dimensional control
NASA Technical Reports Server (NTRS)
Taasan, Shlomo
1991-01-01
The efficient numerical treatment of optimal control problems governed by elliptic partial differential equations (PDEs) and systems of elliptic PDEs, where the control is finite dimensional is discussed. Distributed control as well as boundary control cases are discussed. The main characteristic of the new methods is that they are designed to solve the full optimization problem directly, rather than accelerating a descent method by an efficient multigrid solver for the equations involved. The methods use the adjoint state in order to achieve efficient smoother and a robust coarsening strategy. The main idea is the treatment of the control variables on appropriate scales, i.e., control variables that correspond to smooth functions are solved for on coarse grids depending on the smoothness of these functions. Solution of the control problems is achieved with the cost of solving the constraint equations about two to three times (by a multigrid solver). Numerical examples demonstrate the effectiveness of the method proposed in distributed control case, pointwise control and boundary control problems.
ERIC Educational Resources Information Center
Cromartie, Michael Tyrone
2013-01-01
The aim of this study was to determine the organizational characteristics and behaviors that contribute to sustaining a culture of academic optimism as a mechanism of student achievement. While there is a developing research base identifying both the individual elements of academic optimism as well as the academic optimism construct itself as…
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.
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.
An integrated control/structure design method using multi-objective optimization
NASA Technical Reports Server (NTRS)
Gupta, Sandeep; Joshi, Suresh M.
1991-01-01
The benefits are demonstrated of a multiobjective optimization based control structure integrated design methodology. An application of the proposed CSI methodology to the integrated design of the Spacecraft COntrol Lab Experiment (SCOLE) configuration is presented. Integrated design resulted in reducing both the control performance measure and the mass. Thus, better overall performance is achieved through integrated design optimization. The mutliobjective optimization approach used provides Pareto optimal solutions by unconstrained minimization of a differentiable KS function. Furthermore, adjusting the parameters gives insight into the trade-offs involved between different objectives.
Method of achieving the controlled release of thermonuclear energy
Brueckner, Keith A.
1986-01-01
A method of achieving the controlled release of thermonuclear energy by illuminating a minute, solid density, hollow shell of a mixture of material such as deuterium and tritium with a high intensity, uniformly converging laser wave to effect an extremely rapid build-up of energy in inwardly traveling shock waves to implode the shell creating thermonuclear conditions causing a reaction of deuterons and tritons and a resultant high energy thermonuclear burn. Utilizing the resulting energy as a thermal source and to breed tritium or plutonium. The invention also contemplates a laser source wherein the flux level is increased with time to reduce the initial shock heating of fuel and provide maximum compression after implosion; and, in addition, computations and an equation are provided to enable the selection of a design having a high degree of stability and a dependable fusion performance by establishing a proper relationship between the laser energy input and the size and character of the selected material for the fusion capsule.
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.
Bichacho, N
1998-10-01
The role of prosthetic restorations in the final appearance of the surrounding soft tissues has long been recognized. Innovative prosthodontic concepts as described should be used to enhance the biologic as well as the esthetic data of the supporting tissues, in natural teeth and implants alike. Combined dental treatment modalities of different kinds (i.e., orthodontics, periodontal treatment) are often required for optimal results. Meticulous care and attention to the delicate soft tissues should be given throughout all phases of the treatment, with a view to achieving a functional, healthy, and esthetic oral environment. PMID:9891656
NASA Astrophysics Data System (ADS)
Deng, Lujuan; Xie, Songhe; Cui, Jiantao; Liu, Tao
2006-11-01
It is the essential goal of intelligent greenhouse environment optimal control to enhance income of cropper and energy save. There were some characteristics such as uncertainty, imprecision, nonlinear, strong coupling, bigger inertia and different time scale in greenhouse environment control system. So greenhouse environment optimal control was not easy and especially model-based optimal control method was more difficult. So the optimal control problem of plant environment in intelligent greenhouse was researched. Hierarchical greenhouse environment control system was constructed. In the first level data measuring was carried out and executive machine was controlled. Optimal setting points of climate controlled variable in greenhouse was calculated and chosen in the second level. Market analysis and planning were completed in third level. The problem of the optimal setting point was discussed in this paper. Firstly the model of plant canopy photosynthesis responses and the model of greenhouse climate model were constructed. Afterwards according to experience of the planting expert, in daytime the optimal goals were decided according to the most maximal photosynthesis rate principle. In nighttime on plant better growth conditions the optimal goals were decided by energy saving principle. Whereafter environment optimal control setting points were computed by GA. Compared the optimal result and recording data in real system, the method is reasonable and can achieve energy saving and the maximal photosynthesis rate in intelligent greenhouse
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.
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.
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
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.
Malaria in Turkey: successful control and strategies for achieving elimination.
Özbilgina, Ahmet; Topluoglu, Seher; Es, Saffet; Islek, Elif; Mollahaliloglu, Salih; Erkoc, Yasin
2011-01-01
Turkey is located in the middle of Asia, Africa and Europe, close to Caucasia, Balkans and Middle East in subtropical climate zone. Malaria has been known since the early ages of human history and it was one of the leading diseases in Anatolian history, as well. Today, chloroquine-sensitive Plasmodium vivax is the only agent of autochthonous malaria cases in Turkey. The other Plasmodium species identified are isolated from imported cases of malaria. The most common vector of malaria in Turkey is Anopheles sacharovi followed by An. superpictus, An. maculipennis and An. subalpinus. In 2009, pre-elimination stage of Malaria Program was started due to dramatic decline in the number of malaria cases in Turkey (Total, 84; 38 autochthonous cases only in 26 foci in south-eastern Anatolia, and 46 imported cases; incidence: 0.1/100,000). As there were no detected cases of new autochthonous malaria in the first 8 months of 2010, elimination stage was started. The role of the persistent policies and successful applications of the Ministry of Health, such as the strict control of the patients using anti-malarial drugs especially chloroquine, avoidance of resistant insecticides, facilitation of access to patients via Health Transformation Program (HTP), establishment of close contact with the patients' families, and improvement of reporting and surveillance system, was essential. In addition, improvement maintained in the motivations and professional rights of malaria workers, as well in the coordination of field studies and maintenance of a decline or termination in vector-to-person transmission were all achieved with the insistent policies of the Ministry of Health. Other factors that probably contributed to elimination studies include lessening of military operations in south-eastern Anatolia and the lowering of malaria cases in neighbouring countries in recent years. Free access to health services concerning malaria is still successfully conducted throughout the country
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.
Selection of optimal composition-control parameters for friable materials
Pak, Yu.N.; Vdovkin, A.V.
1988-05-01
A method for composition analysis of coal and minerals is proposed which uses scattered gamma radiation and does away with preliminary sample preparation to ensure homogeneous particle density, surface area, and size. Reduction of the error induced by material heterogeneity has previously been achieved by rotation of the control object during analysis. A further refinement is proposed which addresses the necessity that the contribution of the radiation scattered from each individual surface to the total intensity be the same. This is achieved by providing a constant linear rate of travel for the irradiated spot through back-and-forth motion of the sensor. An analytical expression is given for the laws of motion for the sensor and test tube which provides for uniform irradiated area movement along a path analogous to the Archimedes spiral. The relationships obtained permit optimization of measurement parameters in analyzing friable materials which are not uniform in grain size.
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.
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.
Design and Validation of Optimized Feedforward with Robust Feedback Control of a Nuclear Reactor
Shaffer, Roman; He Weidong; Edwards, Robert M.
2004-08-15
Design applications for robust feedback and optimized feedforward control, with confirming results from experiments conducted on the Pennsylvania State University TRIGA reactor, are presented. The combination of feedforward and feedback control techniques complement each other in that robust control offers guaranteed closed-loop stability in the presence of uncertainties, and optimized feedforward offers an approach to achieving performance that is sometimes limited by overly conservative robust feedback control. The design approach taken in this work combines these techniques by first designing robust feedback control. Alternative methods for specifying a low-order linear model and uncertainty specifications, while seeking as much performance as possible, are discussed and evaluated. To achieve desired performance characteristics, the optimized feedforward control is then computed by using the nominal nonlinear plant model that incorporates the robust feedback control.
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.
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).
NASA Technical Reports Server (NTRS)
Ostroff, Aaron J.
1998-01-01
This paper contains a study of two methods for use in a generic nonlinear simulation tool that could be used to determine achievable control dynamics and control power requirements while performing perfect tracking maneuvers over the entire flight envelope. The two methods are NDI (nonlinear dynamic inversion) and the SOFFT(Stochastic Optimal Feedforward and Feedback Technology) feedforward control structure. Equivalent discrete and continuous SOFFT feedforward controllers have been developed. These equivalent forms clearly show that the closed-loop plant model loop is a plant inversion and is the same as the NDI formulation. The main difference is that the NDI formulation has a closed-loop controller structure whereas SOFFT uses an open-loop command model. Continuous, discrete, and hybrid controller structures have been developed and integrated into the formulation. Linear simulation results show that seven different configurations all give essentially the same response, with the NDI hybrid being slightly different. The SOFFT controller gave better tracking performance compared to the NDI controller when a nonlinear saturation element was added. Future plans include evaluation using a nonlinear simulation.
Numerical optimization of laser fields to control molecular orientation
Ben Haj-Yedder, A.; Auger, A.; Dion, C.M.; Cances, E.; Le Bris, C.; Keller, A.; Atabek, O.
2002-12-01
A thorough numerical illustration of an optimal control scenario dealing with the laser-induced orientation of a diatomic molecule (LiF) is presented. Special emphasis is laid on the definition of the various targets dealing with different orientation characteristics, identified in terms of maximum efficiency (i.e., molecular axis direction closest to the direction of the laser polarization vector), maximum duration (i.e., the time interval during which this orientation is maintained), or of a compromise between efficiency and duration. Excellent postpulse orientation is achieved by sudden, intense pulses. Thermal effects are also studied with an extension of the control scenarios to Boltzmann averaged orientation dynamics at T=5 K.
Optimize the OPC control recipe with cost function
NASA Astrophysics Data System (ADS)
Liu, Qingwei; Zhang, Liguo
2010-09-01
With the design rule shrinks rapidly, full chip robust Optical Proximity Correction (OPC) will definitely need longer time due to the increasing pattern density. Furthermore, to achieve a perfect OPC control recipe becomes more difficult. For, the critical dimension of the design features is deeply sub exposure wavelength, and there is only limited room for the OPC correction. Usually very complicated scripts need to be developed to handle the shrinking designs, which can be infinitely complicated. So when you are defining a parameter value in your OPC control recipe, one problem is how to find the optimum setting. And usually there are a bund of parameters in the script, some of which may have impact on others performance. We here demonstrate an approach of how to find the optimized setting of the critical parameters with cost function. And this will be helpful to reduce the difficulty for OPC recipe development.
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.
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.
Self-Esteem, Locus of Control, and Student Achievement.
ERIC Educational Resources Information Center
Sterbin, Allan; Rakow, Ernest
The direct effects of locus of control and self-esteem on standardized test scores were studied. The relationships among the standardized test scores and measures of locus of control and self-esteem for 12,260 students from the National Education Longitudinal Study 1994 database were examined, using the same definition of locus of control and…
Reversible Masking Using Low-Molecular-Weight Neutral Lipids to Achieve Optimal-Targeted Delivery
Templeton, Nancy Smyth; Senzer, Neil
2012-01-01
Intravenous injection of therapeutics is required to effectively treat or cure metastatic cancer, certain cardiovascular diseases, and other acquired or inherited diseases. Using this route of delivery allows potential uptake in all disease targets that are accessed by the bloodstream. However, normal tissues and organs also have the potential for uptake of therapeutic agents. Therefore, investigators have used targeted delivery to attempt delivery solely to the target cells; however, use of ligands on the surface of delivery vehicles to target specific cell surface receptors is not sufficient to avoid nonspecific uptake. PEGylation has been used for decades to try to avoid nonspecific uptake but suffers from many problems known as “The PEGylation Dilemma.” We have solved this dilemma by replacing PEGylation with reversible masking using low-molecular-weight neutral lipids in order to achieve optimal-targeted delivery solely to target cells. Our paper will focus on this topic. PMID:22655199
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
Purpose Plus: Supporting Youth Purpose, Control, and Academic Achievement
ERIC Educational Resources Information Center
Pizzolato, Jane Elizabeth; Brown, Elizabeth Levine; Kanny, Mary Allison
2011-01-01
Research in the past decade suggests that a persistent achievement gap between students from low-income minority backgrounds and higher-income white backgrounds may be rooted in theories of student motivation and youth purpose. Yet limited research exists regarding the role of purpose on positive youth development as it pertains to academic…
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.
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.
NASA Technical Reports Server (NTRS)
Garg, Sanjay; Schmidt, Phillip H.
1993-01-01
A parameter optimization framework has earlier been developed to solve the problem of partitioning a centralized controller into a decentralized, hierarchical structure suitable for integrated flight/propulsion control implementation. This paper presents results from the application of the controller partitioning optimization procedure to IFPC design for a Short Take-Off and Vertical Landing (STOVL) aircraft in transition flight. The controller partitioning problem and the parameter optimization algorithm are briefly described. Insight is provided into choosing various 'user' selected parameters in the optimization cost function such that the resulting optimized subcontrollers will meet the characteristics of the centralized controller that are crucial to achieving the desired closed-loop performance and robustness, while maintaining the desired subcontroller structure constraints that are crucial for IFPC implementation. The optimization procedure is shown to improve upon the initial partitioned subcontrollers and lead to performance comparable to that achieved with the centralized controller. This application also provides insight into the issues that should be addressed at the centralized control design level in order to obtain implementable partitioned subcontrollers.
Automatic optimization of metrology sampling scheme for advanced process control
NASA Astrophysics Data System (ADS)
Chue, Chuei-Fu; Huang, Chun-Yen; Shih, Chiang-Lin
2011-03-01
In order to ensure long-term profitability, driving the operational costs down and improving the yield of a DRAM manufacturing process are continuous efforts. This includes optimal utilization of the capital equipment. The costs of metrology needed to ensure yield are contributing to the overall costs. As the shrinking of device dimensions continues, the costs of metrology are increasing because of the associated tightening of the on-product specifications requiring more metrology effort. The cost-of-ownership reduction is tackled by increasing the throughput and availability of metrology systems. However, this is not the only way to reduce metrology effort. In this paper, we discuss how the costs of metrology can be improved by optimizing the recipes in terms of the sampling layout, thereby eliminating metrology that does not contribute to yield. We discuss results of sampling scheme optimization for on-product overlay control of two DRAM manufacturing processes at Nanya Technology Corporation. For a 6x DRAM production process, we show that the reduction of metrology waste can be as high as 27% and overlay can be improved by 36%, comparing with a baseline sampling scheme. For a 4x DRAM process, having tighter overlay specs, a gain of ca. 0.5nm on-product overlay could be achieved, without increasing the metrology effort relative to the original sampling plan.
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.
A 'cheap' optimal control approach to estimate muscle forces in musculoskeletal systems.
Menegaldo, Luciano Luporini; de Toledo Fleury, Agenor; Weber, Hans Ingo
2006-01-01
This paper shows a new method to estimate the muscle forces in musculoskeletal systems based on the inverse dynamics of a multi-body system associated optimal control. The redundant actuator problem is solved by minimizing a time-integral cost function, augmented with a torque-tracking error function, and muscle dynamics is considered through differential constraints. The method is compared to a previously implemented human posture control problem, solved using a Forward Dynamics Optimal Control approach and to classical static optimization, with two different objective functions. The new method provides very similar muscle force patterns when compared to the forward dynamics solution, but the computational cost is much smaller and the numerical robustness is increased. The results achieved suggest that this method is more accurate for the muscle force predictions when compared to static optimization, and can be used as a numerically 'cheap' alternative to the forward dynamics and optimal control in some applications. PMID:16033695
Achieving process control through improved grinding techniques for ferrite materials
Bruce, J.
1995-09-01
In manufacturing soft ferrite materials the particle size of the raw material has a significant impact on the reactivity of calcination. The control of particle size distribution and final formulation at wet milling after calcining impacts the reactivity during sintering and the magnetic properties of the final product. This paper will deal with steps taken to improve process control during the grinding operations of raw material and calcine in soft ferrite production. Equipment modifications as well as changes to the grinding and material handling techniques will be included. All examples of process control and improvements will be supported by data.
Debris control design achievements of the booster separation motors
NASA Technical Reports Server (NTRS)
Smith, G. W.; Chase, C. A.
1985-01-01
The stringent debris control requirements imposed on the design of the Space Shuttle booster separation motor are described along with the verification program implemented to ensure compliance with debris control objectives. The principal areas emphasized in the design and development of the Booster Separation Motor (BSM) relative to debris control were the propellant formulation and nozzle closures which protect the motors from aerodynamic heating and moisture. A description of the motor design requirements, the propellant formulation and verification program, and the nozzle closures design and verification are presented.
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.
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.
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
Achievement Goals and Emotions: The Mediational Roles of Perceived Progress, Control, and Value
ERIC Educational Resources Information Center
Hall, Nathan C.; Sampasivam, Lavanya; Muis, Krista R.; Ranellucci, John
2016-01-01
Background: The link between achievement goals and achievement emotions is well established; however, research exploring potential mediators of this relationship is lacking. The control-value theory of achievement emotions (Pekrun, 2006, "Educational Psychology Review," 18, 315) posits that perceptions of control and value mediate the…
Achieving Acceptable Air Quality: Some Reflections on Controlling Vehicle Emissions
NASA Astrophysics Data System (ADS)
Calvert, J. G.; Heywood, J. B.; Sawyer, R. F.; Seinfeld, J. H.
1993-07-01
Motor vehicle emissions have been and are being controlled in an effort to abate urban air pollution. This article addresses the question: Will the vehicle exhaust emission control and fuel requirements in the 1990 Clean Air Act Amendments and the California Air Resources Board regulations on vehicles and fuels have a significant impact? The effective control of in-use vehicle emissions is the key to a solution to the motor vehicle part of the urban air pollution problem for the next decade or so. It is not necessary, except perhaps in Southern California, to implement extremely low new car emission standards before the end of the 20th century. Some of the proposed gasoline volatility and composition changes in reformulated gasoline will produce significant reductions in vehicle emissions (for example, reduced vapor pressure, sulfur, and light olefin and improved high end volatility), whereas others (such as substantial oxygenate addition and aromatics reduction) will not.
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.
Cognitive Control Predicts Academic Achievement in Kindergarten Children
ERIC Educational Resources Information Center
Coldren, Jeffrey T.
2013-01-01
Children's ability to shift behavior in response to changing environmental demands is critical for successful intellectual functioning. While the processes underlying the development of cognitive control have been thoroughly investigated, its functioning in an ecologically relevant setting such as school is less well understood. Given the alarming…
ACHIEVING IRRIGATION RETURN FLOW QUALITY CONTROL THROUGH IMPROVED LEGAL SYSTEMS
The key to irrigated agricultural return flow quality control is proper utilization and management of the resource itself, and an accepted tool in out society is the law. This project is designed to develop legal alternatives that will facilitate the implementation of improved wa...
Executive functioning in individuals with a history of ASDs who have achieved optimal outcomes.
Troyb, Eva; Rosenthal, Michael; Eigsti, Inge-Marie; Kelley, Elizabeth; Tyson, Katherine; Orinstein, Alyssa; Barton, Marianne; Fein, Deborah
2014-01-01
Executive functioning (EF) is examined among children and adolescents once diagnosed with an autism spectrum disorder (ASD), but who no longer meet diagnostic criteria. These individuals have average social and language skills, receive minimal school support and are considered to have achieved "optimal outcomes" (OOs). Since residual impairments in these individuals might be expected in deficits central to autism, and in developmentally advanced skills, EF was examined in 34 individuals who achieved OOs, 43 individuals with high-functioning autism (HFA), and 34 typically developing (TD) peers. Groups were matched on age (M = 13.49), gender, and nonverbal IQ (NVIQ) but differed on verbal IQ (VIQ; HFA < TD, OO). On direct assessment, all three groups demonstrated average EF; however, the OO and HFA groups exhibited more impulsivity and less efficient planning and problem-solving than the TD group, and more HFA participants exhibited below average inhibition than did OO and TD participants. Parent-report measures revealed average EF among the OO and TD groups; however, the OO group exhibited more difficulty than the TD group on set-shifting and working memory. HFA participants demonstrated more difficulty on all parent-reported EF domains, with a clinical impairment in attention-shifting. Results suggest that EF in OO appears to be within the average range, even for functions that were impaired among individuals with HFA. Despite their average performance, however, the OO and TD groups differed on measures of impulsivity, set-shifting, problem-solving, working memory, and planning, suggesting that the OO group does not have the above-average EF scores of the TD group despite their high-average IQs. PMID:23731181
NASA Technical Reports Server (NTRS)
Becus, G. A.; Lui, C. Y.; Venkayya, V. B.; Tischler, V. A.
1987-01-01
A method for simultaneous structural and control design of large flexible space structures (LFSS) to reduce vibration generated by disturbances is presented. Desired natural frequencies and damping ratios for the closed loop system are achieved by using a combination of linear quadratic regulator (LQR) synthesis and numerical optimization techniques. The state and control weighing matrices (Q and R) are expressed in terms of structural parameters such as mass and stiffness. The design parameters are selected by numerical optimization so as to minimize the weight of the structure and to achieve the desired closed-loop eigenvalues. An illustrative example of the design of a two bar truss is presented.
Physiological geroscience: targeting function to increase healthspan and achieve optimal longevity.
Seals, Douglas R; Justice, Jamie N; LaRocca, Thomas J
2016-04-15
Most nations of the world are undergoing rapid and dramatic population ageing, which presents great socio-economic challenges, as well as opportunities, for individuals, families, governments and societies. The prevailing biomedical strategy for reducing the healthcare impact of population ageing has been 'compression of morbidity' and, more recently, to increase healthspan, both of which seek to extend the healthy period of life and delay the development of chronic diseases and disability until a brief period at the end of life. Indeed, a recently established field within biological ageing research, 'geroscience', is focused on healthspan extension. Superimposed on this background are new attitudes and demand for 'optimal longevity' - living long, but with good health and quality of life. A key obstacle to achieving optimal longevity is the progressive decline in physiological function that occurs with ageing, which causes functional limitations (e.g. reduced mobility) and increases the risk of chronic diseases, disability and mortality. Current efforts to increase healthspan centre on slowing the fundamental biological processes of ageing such as inflammation/oxidative stress, increased senescence, mitochondrial dysfunction, impaired proteostasis and reduced stress resistance. We propose that optimization of physiological function throughout the lifespan should be a major emphasis of any contemporary biomedical policy addressing global ageing. Effective strategies should delay, reduce in magnitude or abolish reductions in function with ageing (primary prevention) and/or improve function or slow further declines in older adults with already impaired function (secondary prevention). Healthy lifestyle practices featuring regular physical activity and ideal energy intake/diet composition represent first-line function-preserving strategies, with pharmacological agents, including existing and new pharmaceuticals and novel 'nutraceutical' compounds, serving as potential
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.
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.
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.
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.
Achievements in and Challenges of Tuberculosis Control in South Korea.
Kim, Ji Han; Yim, Jae-Joon
2015-11-01
After the Korean War (1950-1953), nearly 6.5% of South Korea's population had active tuberculosis (TB). In response, South Korea implemented the National Tuberculosis Program in 1962. From 1965 to 1995, the prevalence of bacteriologically confirmed pulmonary TB in South Korea decreased from 940 to 219 cases per 100,000 population. Astounding economic growth might have contributed to this result; however, TB incidence in South Korea remains the highest among high-income countries. The rate of decrease in TB incidence seems to have slowed over the past 15 years. A demographic shift toward an older population, many of whom have latent TB and various concurrent conditions, is challenging TB control efforts in South Korea. The increasing number of immigrants also plays a part in the prolonged battle against TB. A historical review of TB in South Korea provides an opportunity to understand national TB control efforts that are applicable to other parts of the world. PMID:26485188
Troyb, Eva; Orinstein, Alyssa; Tyson, Katherine; Helt, Molly; Eigsti, Inge-Marie; Stevens, Michael; Fein, Deborah
2014-04-01
This study examines the academic abilities of children and adolescents who were once diagnosed with an autism spectrum disorder, but who no longer meet diagnostic criteria for this disorder. These individuals have achieved social and language skills within the average range for their ages, receive little or no school support, and are referred to as having achieved "optimal outcomes." Performance of 32 individuals who achieved optimal outcomes, 41 high-functioning individuals with a current autism spectrum disorder diagnosis (high-functioning autism), and 34 typically developing peers was compared on measures of decoding, reading comprehension, mathematical problem solving, and written expression. Groups were matched on age, sex, and nonverbal IQ; however, the high-functioning autism group scored significantly lower than the optimal outcome and typically developing groups on verbal IQ. All three groups performed in the average range on all subtests measured, and no significant differences were found in performance of the optimal outcome and typically developing groups. The high-functioning autism group scored significantly lower on subtests of reading comprehension and mathematical problem solving than the optimal outcome group. These findings suggest that the academic abilities of individuals who achieved optimal outcomes are similar to those of their typically developing peers, even in areas where individuals who have retained their autism spectrum disorder diagnoses exhibit some ongoing difficulty. PMID:24096312
Control and optimization of a staged laser-wakefield accelerator
NASA Astrophysics Data System (ADS)
Golovin, G.; Banerjee, S.; Chen, S.; Powers, N.; Liu, C.; Yan, W.; Zhang, J.; Zhang, P.; Zhao, B.; Umstadter, D.
2016-09-01
We report results of an experimental study of laser-wakefield acceleration of electrons, using a staged device based on a double-jet gas target that enables independent injection and acceleration stages. This novel scheme is shown to produce stable, quasi-monoenergetic, and tunable electron beams. We show that optimal accelerator performance is achieved by systematic variation of five critical parameters. For the injection stage, we show that the amount of trapped charge is controlled by the gas density, composition, and laser power. For the acceleration stage, the gas density and the length of the jet are found to determine the final electron energy. This independent control over both the injection and acceleration processes enabled independent control over the charge and energy of the accelerated electron beam while preserving the quasi-monoenergetic character of the beam. We show that the charge and energy can be varied in the ranges of 2-45 pC, and 50-450 MeV, respectively. This robust and versatile electron accelerator will find application in the generation of high-brightness and controllable x-rays, and as the injector stage for more conventional devices.