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.
Cc Chow, Francis; Chan, Siew-Pheng; Hwu, Chii-Min; Suwanwalaikorn, Sompongse; Wu, Akira Yt; Gan, Susan Yu; Zacarias, Manuel B
2012-12-20
It is well recognised that Asia is at the epicenter of the global type 2 diabetes epidemic. Driven by socioeconomic changes involving industrialization, urbanization and adoption of Western lifestyles, the unprecedented increases in the prevalence of diabetes are particularly evident in Southeast Asia. The impact of diabetes is immense, and despite evidence of the benefit of optimal glucose control in reducing the risk of disease progression and development of macrovascular and microvascular complications, many individuals in this region remain poorly controlled. Chronic kidney disease (CKD) is an increasingly common diabetes-associated complication in Asian patients. Furthermore, Southeast Asia has one of the highest rates of end-stage renal disease (ESRD) in the world. Consequently, CKD in diabetes is associated with considerable morbidity and cardiovascular-related mortality, highlighting the need to screen and assess patients early in the course of the disease. The management of type 2 diabetes patients with declining renal function represents a significant challenge. Many of the older antidiabetic agents, such as metformin and sulfonylureas, are limited in their utility in CKD as a result of contraindications or hypoglycemic episodes. In contrast, dipeptidyl-peptidase IV inhibitors have provided a welcome addition to the therapeutic armamentarium for achieving glycemic control in these special populations. With comparable efficacy to and more favorable pharmacokinetic and side-effect profiles than traditional therapies, agents in this drug class, such as linagliptin, offer a more tailored approach to disease control in type 2 diabetes patients with declining renal function.
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.
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.
Smoking control: challenges and achievements
da Silva, Luiz Carlos Corrêa; de Araújo, Alberto José; de Queiroz, Ângela Maria Dias; Sales, Maria da Penha Uchoa; Castellano, Maria Vera Cruz de Oliveira
2016-01-01
ABSTRACT Smoking is the most preventable and controllable health risk. Therefore, all health care professionals should give their utmost attention to and be more focused on the problem of smoking. Tobacco is a highly profitable product, because of its large-scale production and great number of consumers. Smoking control policies and treatment resources for smoking cessation have advanced in recent years, showing highly satisfactory results, particularly in Brazil. However, there is yet a long way to go before smoking can be considered a controlled disease from a public health standpoint. We can already perceive that the behavior of our society regarding smoking is changing, albeit slowly. Therefore, pulmonologists have a very promising area in which to work with their patients and the general population. We must act with greater impetus in support of health care policies and social living standards that directly contribute to improving health and quality of life. In this respect, pulmonologists can play a greater role as they get more involved in treating smokers, strengthening anti-smoking laws, and demanding health care policies related to lung diseases.
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.…
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…
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.
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
Optimality principles in sensorimotor control.
Todorov, Emanuel
2004-09-01
The sensorimotor system is a product of evolution, development, learning and adaptation-which work on different time scales to improve behavioral performance. Consequently, many theories of motor function are based on 'optimal performance': they quantify task goals as cost functions, and apply the sophisticated tools of optimal control theory to obtain detailed behavioral predictions. The resulting models, although not without limitations, have explained more empirical phenomena than any other class. Traditional emphasis has been on optimizing desired movement trajectories while ignoring sensory feedback. Recent work has redefined optimality in terms of feedback control laws, and focused on the mechanisms that generate behavior online. This approach has allowed researchers to fit 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 real-time sensorimotor control strategies most suitable for accomplishing those goals.
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
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.
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…
Optimal performance of constrained control systems
NASA Astrophysics Data System (ADS)
Harvey, P. Scott, Jr.; Gavin, Henri P.; Scruggs, Jeffrey T.
2012-08-01
This paper presents a method to compute optimal open-loop trajectories for systems subject to state and control inequality constraints in which the cost function is quadratic and the state dynamics are linear. For the case in which inequality constraints are decentralized with respect to the controls, optimal Lagrange multipliers enforcing the inequality constraints may be found at any time through Pontryagin’s minimum principle. In so doing, the set of differential algebraic Euler-Lagrange equations is transformed into a nonlinear two-point boundary-value problem for states and costates whose solution meets the necessary conditions for optimality. The optimal performance of inequality constrained control systems is calculable, allowing for comparison to previous, sub-optimal solutions. The method is applied to the control of damping forces in a vibration isolation system subjected to constraints imposed by the physical implementation of a particular controllable damper. An outcome of this study is the best performance achievable given a particular objective, isolation system, and semi-active damper constraints.
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.
Ogita, Manabu; Miyauchi, Katsumi; Miyazaki, Tadashi; Naito, Ryo; Konishi, Hirokazu; Tsuboi, Shuta; Dohi, Tomotaka; Kasai, Takatoshi; Yokoyama, Takayuki; Okazaki, Shinya; Kurata, Takeshi; Daida, Hiroyuki
2014-01-01
Diabetes mellitus is recognized an independent risk factor for coronary artery disease (CAD) and mortality. Clinical trials have shown that statins significantly reduce cardiovascular events in diabetic patients. However, residual cardiovascular risk persists despite the achievement of target low-density lipoprotein cholesterol (LDL-C) levels with statin. High-density lipoprotein cholesterol (HDL-C) is an established coronary risk factor that is independent of LDL-C levels. We evaluated the impact of HDL-C on long-term mortality in diabetic patients with stable CAD who achieved optimal LDL-C. We enrolled 438 consecutive diabetic patients who were scheduled for percutaneous coronary intervention between 2004 and 2007 at our institution. We identified 165 patients who achieved target LDL-C <100 mg/dl. Patients were stratified into two groups according to HDL-C levels (low HDL-C group, baseline HDL-C <40 mg/dl; high HDL-C group, ≥40 mg/dl). Major adverse cardiac events (MACE) that included all-cause death, acute coronary syndrome, and target lesion revascularization were evaluated between the two groups. The median follow-up period was 946 days. The rate of MACE was significantly higher in diabetic patients with low-HDL-C who achieved optimal LDL-C (6.9 vs 17.9 %, log-rank P = 0.030). Multivariate Cox regression analysis showed that HDL-C is significantly associated with clinical outcomes (adjusted hazard ratio for MACE 1.33, 95 % confidence interval 1.01-1.75, P = 0.042). Low HDL-C is a residual risk factor that is significantly associated with long-term clinical outcomes among diabetic patients with stable CAD who achieve optimal LDL-C levels.
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.
Optimal control of complex atomic quantum systems
NASA Astrophysics Data System (ADS)
van Frank, S.; Bonneau, M.; Schmiedmayer, J.; Hild, S.; Gross, C.; Cheneau, M.; Bloch, I.; Pichler, T.; Negretti, A.; Calarco, T.; Montangero, S.
2016-10-01
Quantum technologies will ultimately require manipulating many-body quantum systems with high precision. Cold atom experiments represent a stepping stone in that direction: a high degree of control has been achieved on systems of increasing complexity. However, this control is still sub-optimal. In many scenarios, achieving a fast transformation is crucial to fight against decoherence and imperfection effects. Optimal control theory is believed to be the ideal candidate to bridge the gap between early stage proof-of-principle demonstrations and experimental protocols suitable for practical applications. Indeed, it can engineer protocols at the quantum speed limit – the fastest achievable timescale of the transformation. Here, we demonstrate such potential by computing theoretically and verifying experimentally the optimal transformations in two very different interacting systems: the coherent manipulation of motional states of an atomic Bose-Einstein condensate and the crossing of a quantum phase transition in small systems of cold atoms in optical lattices. We also show that such processes are robust with respect to perturbations, including temperature and atom number fluctuations.
Optimal control of complex atomic quantum systems
van Frank, S.; Bonneau, M.; Schmiedmayer, J.; Hild, S.; Gross, C.; Cheneau, M.; Bloch, I.; Pichler, T.; Negretti, A.; Calarco, T.; Montangero, S.
2016-01-01
Quantum technologies will ultimately require manipulating many-body quantum systems with high precision. Cold atom experiments represent a stepping stone in that direction: a high degree of control has been achieved on systems of increasing complexity. However, this control is still sub-optimal. In many scenarios, achieving a fast transformation is crucial to fight against decoherence and imperfection effects. Optimal control theory is believed to be the ideal candidate to bridge the gap between early stage proof-of-principle demonstrations and experimental protocols suitable for practical applications. Indeed, it can engineer protocols at the quantum speed limit – the fastest achievable timescale of the transformation. Here, we demonstrate such potential by computing theoretically and verifying experimentally the optimal transformations in two very different interacting systems: the coherent manipulation of motional states of an atomic Bose-Einstein condensate and the crossing of a quantum phase transition in small systems of cold atoms in optical lattices. We also show that such processes are robust with respect to perturbations, including temperature and atom number fluctuations. PMID:27725688
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…
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.
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
Reentry trajectory optimization and control
NASA Astrophysics Data System (ADS)
Strohmaier, P.; Kiefer, A.; Burkhardt, D.; Horn, K.
1990-06-01
There are several possible methods to increase the cross range capability of a winged reentry vehicle, for instance, skip trajectories, a powered cruise phase, or high lift/drag ratio flight. However, most of these alternative descent strategies have not yet been investigated sufficiently with respect to aero-thermodynamic effects and the design of the thermal protection system. This problem is treated by two different means. First, a nominal reentry trajectory is generated based on a phase concept, and then the same problem is again solved using a numerical optimization code to determine the control functions. The nominal reentry trajectory design presented first subdivides the total reentry trajectory into several segments with partially constant control/state parameters such as maximum heat flux and deceleration. The optimal conditions for a given segment can then be selected. In contrast, the parameterized optimization code selects the control functions freely. Both approaches consider a mass point simulation which uses realistic model assumptions for atmosphere, earth and gravity. Likewise, both approaches satisfy all flight regime limitations and boundary conditions such as thermal constraints throughout the flight path and specified speed and altitude at the final time. For the optimization of high cross reentry trajectories the cross range per total absorbed heat represents an appropriate cost function. The optimization code delivers quite a different flight strategy than that usually generated by the nominal reentry design program, first flying longer along the temperature boundary at highest possible angle of attack (AOAs) (utilizing higher average turn rates), and afterwards performing flare-dive segments to reduce heat flux and to increase range. Finally, the aspect of guiding the nominal or optimized reentry trajectory during a cross range flight is considered. The vertical guidance is performed with both angles of attack and roll angle control. 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.
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
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
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
Optimization of EB plant by constraint control
Hummel, H.K.; de Wit, G.B.C.; Maarleveld, A. )
1991-03-01
Optimum plant operation can often be achieved by means of constraint control instead of model- based on-line optimization. This is because optimum operation is seldom at the top of the hill but usually at the intersection of constraints. This article describes the development of a constraint control system for a plant producing ethylbenzene (EB) by the Mobil/Badger Ethylbenzene Process. Plant optimization can be defined as the maximization of a profit function describing the economics of the plant. This function contains terms with product values, feedstock prices and operational costs. Maximization of the profit function can be obtained by varying relevant degrees of freedom in the plant, such as a column operating pressure or a reactor temperature. These degrees of freedom can be varied within the available operating margins of the plant.
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.
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.
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.
Optimizing density patterns to achieve desired light extraction for displays
NASA Astrophysics Data System (ADS)
Davenport, T. L. R.; Cassarly, W. J.
2007-01-01
In displays such as backlights and signage, it is often desirable to produce a particular spatial luminance distribution of light. This work demonstrates an iterative optimization technique for determining the density of light extractors required to produce desired luminance distributions.
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.
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.
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…
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.
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.
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.
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.
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
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)…
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…
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.
Optimal control design that accounts for model mismatch errors
Kim, T.J.; Hull, D.G.
1995-02-01
A new technique is presented in this paper that reduces the complexity of state differential equations while accounting for modeling assumptions. The mismatch controls are defined as the differences between the model equations and the true state equations. The performance index of the optimal control problem is formulated with a set of tuning parameters that are user-selected to tune the control solution in order to achieve the best results. Computer simulations demonstrate that the tuned control law outperforms the untuned controller and produces results that are comparable to a numerically-determined, piecewise-linear optimal controller.
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
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.
Regulatory schemes to achieve optimal flux partitioning in bacterial metabolism
NASA Astrophysics Data System (ADS)
Tang, Lei-Han; Yang, Zhu; Hui, Sheng; Kim, Pan-Jun; Li, Xue-Fei; Hwa, Terence
2012-02-01
The flux balance analysis (FBA) offers a way to compute the optimal performance of a given metabolic network when the maximum incoming flux of nutrient molecules and other essential ingredients for biosynthesis are specified. Here we report a theoretical and computational analysis of the network structure and regulatory interactions in an E. coli cell. An automated scheme is devised to simplify the network topology and to enumerate the independent flux degrees of freedom. The network organization revealed by the scheme enables a detailed interpretation of the three layers of metabolic regulation known in the literature: i) independent transcriptional regulation of biosynthesis and salvage pathways to render the network tree-like under a given nutrient condition; ii) allosteric end-product inhibition of enzyme activity at entry points of synthesis pathways for metabolic flux partitioning according to consumption; iii) homeostasis of currency and carrier compounds to maintain sufficient supply of global commodities. Using the amino-acid synthesis pathways as an example, we show that the FBA result can be reproduced with suitable implementation of the three classes of regulatory interactions with literature evidence.
Optimal control, geometry, and quantum computing
NASA Astrophysics Data System (ADS)
Nielsen, Michael A.; Dowling, Mark R.; Gu, Mile; Doherty, Andrew C.
2006-06-01
We prove upper and lower bounds relating the quantum gate complexity of a unitary operation, U , to the optimal control cost associated to the synthesis of U . These bounds apply for any optimal control problem, and can be used to show that the quantum gate complexity is essentially equivalent to the optimal control cost for a wide range of problems, including time-optimal control and finding minimal distances on certain Riemannian, sub-Riemannian, and Finslerian manifolds. These results generalize the results of [Nielsen, Dowling, Gu, and Doherty, Science 311, 1133 (2006)], which showed that the gate complexity can be related to distances on a Riemannian manifold.
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.
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.
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.
Optimizing Dynamical Network Structure for Pinning Control.
Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo
2016-04-12
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.
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.
Dynamics systems vs. optimal control--a unifying view.
Schaal, Stefan; Mohajerian, Peyman; Ijspeert, Auke
2007-01-01
In the past, computational motor control has been approached from at least two major frameworks: the dynamic systems approach and the viewpoint of optimal control. The dynamic system approach emphasizes motor control as a process of self-organization between an animal and its environment. Nonlinear differential equations that can model entrainment and synchronization behavior are among the most favorable tools of dynamic systems modelers. In contrast, optimal control approaches view motor control as the evolutionary or development result of a nervous system that tries to optimize rather general organizational principles, e.g., energy consumption or accurate task achievement. Optimal control theory is usually employed to develop appropriate theories. Interestingly, there is rather little interaction between dynamic systems and optimal control modelers as the two approaches follow rather different philosophies and are often viewed as diametrically opposing. In this paper, we develop a computational approach to motor control that offers a unifying modeling framework for both dynamic systems and optimal control approaches. In discussions of several behavioral experiments and some theoretical and robotics studies, we demonstrate how our computational ideas allow both the representation of self-organizing processes and the optimization of movement based on reward criteria. Our modeling framework is rather simple and general, and opens opportunities to revisit many previous modeling results from this novel unifying view.
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
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.
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.
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…
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.
Lie algebroids and optimal control: abnormality
NASA Astrophysics Data System (ADS)
Barbero-Liñán, M.; de Diego, D. Martín; Muñoz-Lecanda, M. C.
2009-05-01
Candidates to be solutions to optimal control problems, called extremals, are found using Pontryagin's Maximum Principle [9]. This Principle gives necessary conditions for optimality and, under suitable assumptions, starts a presymplectic constraint algorithm in the sense given in [3]. This procedure, first considered in optimal control theory in [6], can be adapted to characterize the different kinds of extremals [1]. In this paper, we describe the constraints given by the algorithm for the so-called abnormal extremals for optimal control problems defined on Lie algebroids [4, 7, 8]. The peculiarity of the abnormal extremals is their independence on the cost function to characterize them. In particular, we are interested in how useful the geometry provided by the Lie algebroid is to study the constraints obtained in the optimal control problems for affine connection control systems. These systems model the motion of different types of mechanical systems such as rigid bodies, nonholonomic systems and robotic arms [2].
Locus of Control in Underachieving and Achieving Gifted Students.
ERIC Educational Resources Information Center
McClelland, Robert; And Others
1991-01-01
This study, with 87 underachieving and 77 achieving gifted students in grades 6-9, found that general locus of control measures did not differentiate between the 2 groups, that both scored significantly higher on positive internal than on negative internal locus of control, and that there were no gender or grade effects. (Author/DB)
Optimal second order sliding mode control for linear uncertain systems.
Das, Madhulika; Mahanta, Chitralekha
2014-11-01
In this paper an optimal second order sliding mode controller (OSOSMC) is proposed to track a linear uncertain system. The optimal controller based on the linear quadratic regulator method is designed for the nominal system. An integral sliding mode controller is combined with the optimal controller to ensure robustness of the linear system which is affected by parametric uncertainties and external disturbances. To achieve finite time convergence of the sliding mode, a nonsingular terminal sliding surface is added with the integral sliding surface giving rise to a second order sliding mode controller. The main advantage of the proposed OSOSMC is that the control input is substantially reduced and it becomes chattering free. Simulation results confirm superiority of the proposed OSOSMC over some existing.
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
Optimal birth control of population dynamics.
Chan, W L; Guo, B Z
1989-11-01
The authors studied optimal birth control policies for an age-structured population of McKendrick type which is a distributed parameter system involving 1st order partial differential equations with nonlocal bilinear boundary control. The functional analytic approach of Dubovitskii and Milyutin is adopted in the investigation. Maximum principles for problems with a free end condition and fixed final horizon are developed, and the time optimal control problems, the problem with target sets, and infinite planning horizon case are investigated.
Dynamic optimization and adaptive controller design
NASA Astrophysics Data System (ADS)
Inamdar, S. R.
2010-10-01
In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.
Role of controllability in optimizing quantum dynamics
Wu Rebing; Hsieh, Michael A.; Rabitz, Herschel
2011-06-15
This paper reveals an important role that controllability plays in the complexity of optimizing quantum control dynamics. We show that the loss of controllability generally leads to multiple locally suboptimal controls when gate fidelity in a quantum control system is maximized, which does not happen if the system is controllable. Such local suboptimal controls may attract an optimization algorithm into a local trap when a global optimal solution is sought, even if the target gate can be perfectly realized. This conclusion results from an analysis of the critical topology of the corresponding quantum control landscape, which refers to the gate fidelity objective as a functional of the control fields. For uncontrollable systems, due to SU(2) and SU(3) dynamical symmetries, the control landscape corresponding to an implementable target gate is proven to possess multiple locally optimal critical points, and its ruggedness can be further increased if the target gate is not realizable. These results imply that the optimization of quantum dynamics can be seriously impeded when operating with local search algorithms under these conditions, and thus full controllability is demanded.
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.
ERIC Educational Resources Information Center
McGuigan, Leigh; Hoy, Wayne K.
2006-01-01
Since the Coleman Report (1966), educational researchers have tried to identify school properties that make a difference in student achievement and overcome the negative influence of low socioeconomic status. We theorized that academic optimism was a latent construct that enhanced student achievement and that enabling school structure provided a…
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.
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.
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.
Neuro-optimal control of helicopter UAVs
NASA Astrophysics Data System (ADS)
Nodland, David; Ghosh, Arpita; Zargarzadeh, H.; Jagannathan, S.
2011-05-01
Helicopter UAVs can be extensively used for military missions as well as in civil operations, ranging from multirole combat support and search and rescue, to border surveillance and forest fire monitoring. Helicopter UAVs are underactuated nonlinear mechanical systems with correspondingly challenging controller designs. This paper presents an optimal controller design for the regulation and vertical tracking of an underactuated helicopter using an adaptive critic neural network framework. The online approximator-based controller learns the infinite-horizon continuous-time Hamilton-Jacobi-Bellman (HJB) equation and then calculates the corresponding optimal control input that minimizes the HJB equation forward-in-time. In the proposed technique, optimal regulation and vertical tracking is accomplished by a single neural network (NN) with a second NN necessary for the virtual controller. Both of the NNs are tuned online using novel weight update laws. Simulation results are included to demonstrate the effectiveness of the proposed control design in hovering applications.
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.
Automated beam steering using optimal control
Allen, C. K.
2004-01-01
We present a steering algorithm which, with the aid of a model, allows the user to specify beam behavior throughout a beamline, rather than just at specified beam position monitor (BPM) locations. The model is used primarily to compute the values of the beam phase vectors from BPM measurements, and to define cost functions that describe the steering objectives. The steering problem is formulated as constrained optimization problem; however, by applying optimal control theory we can reduce it to an unconstrained optimization whose dimension is the number of control signals.
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.
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)
Multi-objective optimization for model predictive control.
Wojsznis, Willy; Mehta, Ashish; Wojsznis, Peter; Thiele, Dirk; Blevins, Terry
2007-06-01
This paper presents a technique of multi-objective optimization for Model Predictive Control (MPC) where the optimization has three levels of the objective function, in order of priority: handling constraints, maximizing economics, and maintaining control. The greatest weights are assigned dynamically to control or constraint variables that are predicted to be out of their limits. The weights assigned for economics have to out-weigh those assigned for control objectives. Control variables (CV) can be controlled at fixed targets or within one- or two-sided ranges around the targets. Manipulated Variables (MV) can have assigned targets too, which may be predefined values or current actual values. This MV functionality is extremely useful when economic objectives are not defined for some or all the MVs. To achieve this complex operation, handle process outputs predicted to go out of limits, and have a guaranteed solution for any condition, the technique makes use of the priority structure, penalties on slack variables, and redefinition of the constraint and control model. An engineering implementation of this approach is shown in the MPC embedded in an industrial control system. The optimization and control of a distillation column, the standard Shell heavy oil fractionator (HOF) problem, is adequately achieved with this MPC. PMID:17382946
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)
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.
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.
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.
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.
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.
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.
Near-time-optimal control for quantum systems
NASA Astrophysics Data System (ADS)
Chen, Qi-Ming; Wu, Re-Bing; Zhang, Tian-Ming; Rabitz, Herschel
2015-12-01
For a quantum system controlled by an external field, time-optimal control is referred to as the shortest-time-duration control that can still permit maximizing an objective function J , which is especially a desirable goal for engineering quantum dynamics against decoherence effects. However, since rigorously finding a time-optimal control is usually very difficult and in many circumstances the control is only required to be sufficiently short and precise, one can design algorithms seeking such suboptimal control solutions for much reduced computational effort. In this paper, we propose an iterative algorithm for finding near-time-optimal control in a high level set (i.e., the set of controls that achieves the same value of J ) that can be arbitrarily close to the global optima. The algorithm proceeds seeking to decrease the time duration T while the value of J remains invariant, until J leaves the level-set value; the deviation of J due to numerical errors is corrected by gradient climbing that brings the search back to the level-set J value. Since the level set is very close to the maximum value of J , the resulting control solution is nearly time optimal with manageable precision. Numerical examples demonstrate the effectiveness and general applicability of the algorithm.
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.
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...
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.
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.
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
Optimal Control for Coupled Near-Field/Far-Field Domains
NASA Astrophysics Data System (ADS)
Chen, Guoquan; Collis, S. Scott; Ghayour, Kaveh; Heinkenschloss, Matthias
2002-11-01
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 wave equation using a discontinuous Galerkin formulation. In this approach, the coupling of near-field and far-field domains is achieved by weakly enforcing continuity of normal fluxes across a coupling surface that encloses all nonlinear flow effects and noise sources. For optimal control, gradient formation 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. The formulation and implementation of the state and adjoint problems will be presented along with preliminary results. This computational framework will be applied in the future to study optimal boundary control of blade-vortex interaction, which is a significant noise source for helicopters on approach to landing.
Conjunctive Multibasin Management: An Optimal Control Approach
NASA Astrophysics Data System (ADS)
Noel, Jay E.; Howitt, Richard E.
1982-08-01
The economic effects of conjunctive management of ground and surface water supplies for irrigation are formulated as an optimal control model. An empirical hydroeconomic model is estimated for the Yolo County district in California. Two alternative solution methodologies (analytic Riccatti and mathematical programing) are applied and compared. Results show the economic potential for interbasin transfers and the impact of increased electricity prices on optimal groundwater management.
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.
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.
Optimal control of a quantum measurement
NASA Astrophysics Data System (ADS)
Egger, D. J.; Wilhelm, F. K.
2014-11-01
Pulses to steer the time evolution of quantum systems can be designed with optimal control theory. In most cases it is the coherent processes that can be controlled and one optimizes the time evolution toward a target unitary process, sometimes also in the presence of noncontrollable incoherent processes. Here we show how to extend the gradient ascent pulse engineering (GRAPE) algorithm in the case where the incoherent processes are controllable and the target time evolution is a nonunitary quantum channel. We perform a gradient search on a fidelity measure based on Choi matrices. We illustrate our algorithm by optimizing a phase qubit measurement pulse. We show how this technique can lead to a large measurement contrast close to 99 % . We also show, within the validity of our model, that this algorithm can produce short 1.4 -ns pulses with 98.2 % contrast.
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.
Soft commitment: self-control achieved by response persistence.
Siegel, E; Rachlin, H
1995-01-01
With reinforcement contingent on a single peck on either of two available keys (concurrent continuous reinforcement schedules) 4 pigeons, at 80% of free-feeding weights, preferred a smaller-sooner reinforcer (2.5 s of mixed grain preceded by a 0.5-s delay) to a larger-later reinforcer (4.5 s of mixed grain preceded by a 3.5-s delay). However, when the smaller-sooner and larger-later reinforcers were contingent on a concurrent fixed-ratio 31 schedule (the first 30 pecks distributed in any way on the two keys), all pigeons obtained the larger-later reinforcer much more often than they did when only a single peck was required. This "self-control" was achieved by beginning to peck the key leading to the larger-later reinforcer and persisting on that key until reinforcement occurred. We call this persistence "soft commitment" to distinguish it from strict commitment, in which self-control is achieved by preventing changeovers. Soft commitment also effectively achieved self-control when a brief (1-s) signal was inserted between the 30th and 31st response of the ratio and with concurrent fixed-interval 30-s schedules (rather than ratio schedules) of reinforcement. In a second experiment with the same subjects, the fixed ratio was interrupted by darkening both keys and lighting a third (center) key on which pecking was required for various fractions of the fixed-ratio count. The interruption significantly reduced self-control. When interruption was complete (30 responses on the center key followed by a single choice response), pigeons chose the smaller-sooner reinforcer as frequently as they did when only a single choice response was required. PMID:7561671
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.
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 of the Starfire Beam Director
NASA Astrophysics Data System (ADS)
Lanier, Troy V.
1992-12-01
The Starfire Beam Director (SBD) is located at the Starfire Optical Range at Kirtland Air Force Base in Albuquerque, New Mexico. The SBD capabilities include tracking celestial objects and active or passive tracking of artificial satellites to support the Phillips Laboratory Ground Based Laser Acquisition, Tracking, and Pointing (GBL ATP) program. The pointing and tracking accuracy needed to support such experiments is micron rad to sub-grad level. To accomplish this goal requires precise pointing of the massive 6 ton 1-meter clear aperture coelostat. Optimal control design techniques are used to develop a controller to meet the stringent pointing requirements. A nominal linear state-space model was built which included gimbal dynamics, plant disturbances, and sensor noise. Then optimal control design techniques were used to develop unity feedback and two degree of freedom controllers. The various controllers were simulated with the coelostat truth model, which incorporated the higher frequency control loop and motor dynamics, nonlinearities, plant disturbances, sensor noise, and discrete control effects. The best of the designs, the H2 unity feedback controller, was compared and contrasted with the performance of the controller currently being used, which was obtained by classical control design. The H2 controller exceeded tracking requirements and in most areas performed better than the current controller.
Academic Optimism, Organizational Citizenship Behaviors, and Student Achievement at Charter Schools
ERIC Educational Resources Information Center
Guvercin, Mustafa
2013-01-01
The purpose of this study was to examine the relationship among academic optimism, Organizational Citizenship Behaviors (OCBs), and student achievement in college preparatory charter schools. A purposeful sample of elementary school teachers from college preparatory charter schools (N = 226) in southeast Texas was solicited to complete the…
Injecting nation: achieving control of hepatitis C in Australia.
Wodak, A
1997-09-01
Since Australia banned heroin in 1953 consumption of illicit drugs, deaths, crime and corruption related to drugs have steadily increased. Injecting drug use (IDU) in Australia is now a significant public health problem linked each year to approximately 500 overdose deaths and more than 6000 hepatitis C infections. At least 85% of prevalent and incident hepatitis C cases in Australia are injecting drug users (IDUs) with annual incidence estimated at 15%. Although poorly documented, increasing numbers of patients with end-stage liver disease from hepatitis C now appear to present in Australia. This reflects a heroin-injecting epidemic commencing a quarter of a century ago, the close association between drug injecting and hepatitis C and the long delay between hepatitis C infection and complications. The overall health and economic burden of hepatitis C may soon exceed HIV. Control is far more difficult to achieve for hepatitis C than HIV because of much higher baseline prevalence levels and far greater infectiousness by blood to blood spread. Transmission appears to follow minimal breaches of infection control guidelines. Hepatitis C has not yet become a priority public health issue in Australia. No national prevention strategy has been proposed. Prevention strategies (such as needle exchange or methadone) which controlled HIV among IDUs should be expanded, with the expectation of some useful reduction of spread but without achieving control of hepatitis C. Other options for control must be considered. Eradicating illicit drug use in Australia is unachievable. Virtually eradicating injecting drug use by facilitating a switch to non-injecting routes of administration (NIROA) is achievable (although difficult) and this could control hepatitis C. NIROA will have the probable additional benefit of reducing drug overdose deaths. NIROA has begun recently to replace injecting in several countries without government intervention. Powerful cultural, pharmacological and
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.
Finite set control transcription for optimal control applications
NASA Astrophysics Data System (ADS)
Stanton, Stuart Andrew
An enhanced method in optimization rooted in direct collocation is formulated to treat the finite set optimal control problem. This is motivated by applications in which a hybrid dynamical system is subject to ordinary differential continuity constraints, but control variables are contained within finite spaces. Resulting solutions display control discontinuities as variables switch between one feasible value to another. Solutions derived are characterized as optimal switching schedules between feasible control values. The methodology allows control switches to be determined over a continuous spectrum, overcoming many of the limitations associated with discretized solutions. Implementation details are presented and several applications demonstrate the method's utility and capability. Simple applications highlight the effectiveness of the methodology, while complicated dynamic systems showcase its relevance. A key example considers the challenges associated with libration point formations. Extensions are proposed for broader classes of hybrid systems.
Optimal control of gypsy moth populations.
Whittle, Andrew; Lenhart, Suzanne; White, K A J
2008-02-01
This study investigates an optimal strategy for the cost effective control of gypsy moth populations. Gypsy moth populations cycle between low sparse numbers to high outbreak levels and it is during the outbreak levels that the moths cause extensive damage to plant foliage which can lead to deforestation. Deforestation can result in significant economic damage to infested areas, and consequently, there have been many efforts to control moth populations. One effective method of control is the use of the biocontrol agent, Gypchek, but its production is costly. We develop a mathematical model which combines population dynamics and optimal control of the moth population to explore strategies by which the total cost of the gypsy moth problem (economic damage and cost of Gypchek) can be minimized.
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.
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.
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.
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
Determination of optimal gains for constrained controllers
Kwan, C.M.; Mestha, L.K.
1993-08-01
In this report, we consider the determination of optimal gains, with respect to a certain performance index, for state feedback controllers where some elements in the gain matrix are constrained to be zero. Two iterative schemes for systematically finding the constrained gain matrix are presented. An example is included to demonstrate the procedures.
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.
NASA Astrophysics Data System (ADS)
Konakom, Kwantip; Saengchan, Aritsara; Kittisupakorn, Paisan; Mujtaba, Iqbal M.
2011-08-01
Industrial grade ethyl acetate is available with minimum purity of 85.0%. It is mostly produced by an ethanol esterification in a distillation process on both batch and continuous modes. However, researches on high purity production with short operating time are rarely achieved. Therefore, the objective in this work is to study an approach to produce ethyl acetate of 90.0% by 8 hours using a batch reactive distillation column. Based on open-loop simulations, the distillation with constant reflux ratio cannot achieve the product specification. Thus, the dynamic optimization strategy is proposed to handle this problem. For the process safety—preventing the dried column and fractured, a minimum reflux ratio must be determined in advance and then an optimal reflux profile is calculated to achieve optimal product yield. Simulation results show that the industrial grade ethyl acetate can be produced by the dynamic optimization programming with two or more time intervals. Besides, the increasing of time intervals can produce more distillate product.
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.
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.
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…
Distributed optimization and flight control using collectives
NASA Astrophysics Data System (ADS)
Bieniawski, Stefan Richard
The increasing complexity of aerospace systems demands new approaches for their design and control. Approaches are required to address the trend towards aerospace systems comprised of a large number of inherently distributed and highly nonlinear components with complex and sometimes competing interactions. This work introduces collectives to address these challenges. Although collectives have been used for distributed optimization problems in computer science, recent developments based upon Probability Collectives (PC) theory enhance their applicability to discrete, continuous, mixed, and constrained optimization problems. Further, they are naturally applied to distributed systems and those involving uncertainty, such as control in the presence of noise and disturbances. This work describes collectives theory and its implementation, including its connections to multi-agent systems, machine learning, statistics, and gradient-based optimization. To demonstrate the approach, two experiments were developed. These experiments built upon recent advances in actuator technology that resulted in small, simple flow control devices. Miniature-Trailing Edge Effectors (MiTE), consisting of a small, 1-5% chord, moveable surface mounted at the wing trailing edge, are used for the experiments. The high bandwidth, distributed placement, and good control authority make these ideal candidates for rigid and flexible mode control of flight vehicles. This is demonstrated in two experiments: flutter suppression of a flexible wing, and flight control of a remotely piloted aircraft. The first experiment successfully increased the flutter speed by over 25%. The second experiment included a novel distributed flight control system based upon the MiTEs that includes distributed sensing, logic, and actuation. Flight tests validated the control capability of the MiTEs and the associated flight control architecture. The collectives approach was used to design controllers for the distributed
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.
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.
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.
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.
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.
Necessary Conditions for Optimal Control of Stochastic Evolution Equations in Hilbert Spaces
Al-Hussein, Abdul Rahman
2011-06-15
We consider a nonlinear stochastic optimal control problem associated with a stochastic evolution equation. This equation is driven by a continuous martingale in a separable Hilbert space and an unbounded time-dependent linear operator.We derive a stochastic maximum principle for this optimal control problem. Our results are achieved by using the adjoint backward stochastic partial differential equation.
Aerodynamic shape optimization using control theory
NASA Technical Reports Server (NTRS)
Reuther, James
1996-01-01
Aerodynamic shape design has long persisted as a difficult scientific challenge due its highly nonlinear flow physics and daunting geometric complexity. However, with the emergence of Computational Fluid Dynamics (CFD) it has become possible to make accurate predictions of flows which are not dominated by viscous effects. It is thus worthwhile to explore the extension of CFD methods for flow analysis to the treatment of aerodynamic shape design. Two new aerodynamic shape design methods are developed which combine existing CFD technology, optimal control theory, and numerical optimization techniques. Flow analysis methods for the potential flow equation and the Euler equations form the basis of the two respective design methods. In each case, optimal control theory is used to derive the adjoint differential equations, the solution of which provides the necessary gradient information to a numerical optimization method much more efficiently then by conventional finite differencing. Each technique uses a quasi-Newton numerical optimization algorithm to drive an aerodynamic objective function toward a minimum. An analytic grid perturbation method is developed to modify body fitted meshes to accommodate shape changes during the design process. Both Hicks-Henne perturbation functions and B-spline control points are explored as suitable design variables. The new methods prove to be computationally efficient and robust, and can be used for practical airfoil design including geometric and aerodynamic constraints. Objective functions are chosen to allow both inverse design to a target pressure distribution and wave drag minimization. Several design cases are presented for each method illustrating its practicality and efficiency. These include non-lifting and lifting airfoils operating at both subsonic and transonic conditions.
Optimal Control via Self-Generated Stochasticity
NASA Technical Reports Server (NTRS)
Zak, Michail
2011-01-01
The problem of global maxima of functionals has been examined. Mathematical roots of local maxima are the same as those for a much simpler problem of finding global maximum of a multi-dimensional function. The second problem is instability even if an optimal trajectory is found, there is no guarantee that it is stable. As a result, a fundamentally new approach is introduced to optimal control based upon two new ideas. The first idea is to represent the functional to be maximized as a limit of a probability density governed by the appropriately selected Liouville equation. Then, the corresponding ordinary differential equations (ODEs) become stochastic, and that sample of the solution that has the largest value will have the highest probability to appear in ODE simulation. The main advantages of the stochastic approach are that it is not sensitive to local maxima, the function to be maximized must be only integrable but not necessarily differentiable, and global equality and inequality constraints do not cause any significant obstacles. The second idea is to remove possible instability of the optimal solution by equipping the control system with a self-stabilizing device. The applications of the proposed methodology will optimize the performance of NASA spacecraft, as well as robot performance.
Optimal motor control may mask sensory dynamics
Kiemel, Tim; Cowan, Noah J.; Jeka, John J.
2009-01-01
Properties of neural controllers for closed-loop sensorimotor behavior can be inferred with system identification. Under the standard paradigm, the closed-loop system is perturbed (input), measurements are taken (output), and the relationship between input and output reveals features of the system under study. Here we show that under common assumptions made about such systems (e.g. the system implements optimal control with a penalty on mechanical, but not sensory, states) important aspects of the neural controller (its zeros mask the modes of the sensors) remain hidden from standard system identification techniques. Only by perturbing or measuring the closed-loop system “between” the sensor and the control can these features be exposed with closed-loop system identification methods; while uncommon, there exist noninvasive techniques such as galvanic vestibular stimulation that perturb between sensor and controller in this way. PMID:19408009
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.
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.
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…
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
Laboratory transferability of optimally shaped laser pulses for quantum control.
Moore Tibbetts, Katharine; Xing, Xi; Rabitz, Herschel
2014-02-21
Optimal control experiments can readily identify effective shaped laser pulses, or "photonic reagents," that achieve a wide variety of objectives. An important additional practical desire is for photonic reagent prescriptions to produce good, if not optimal, objective yields when transferred to a different system or laboratory. Building on general experience in chemistry, the hope is that transferred photonic reagent prescriptions may remain functional even though all features of a shaped pulse profile at the sample typically cannot be reproduced exactly. As a specific example, we assess the potential for transferring optimal photonic reagents for the objective of optimizing a ratio of photoproduct ions from a family of halomethanes through three related experiments. First, applying the same set of photonic reagents with systematically varying second- and third-order chirp on both laser systems generated similar shapes of the associated control landscape (i.e., relation between the objective yield and the variables describing the photonic reagents). Second, optimal photonic reagents obtained from the first laser system were found to still produce near optimal yields on the second laser system. Third, transferring a collection of photonic reagents optimized on the first laser system to the second laser system reproduced systematic trends in photoproduct yields upon interaction with the homologous chemical family. These three transfers of photonic reagents are demonstrated to be successful upon paying reasonable attention to overall laser system characteristics. The ability to transfer photonic reagents from one laser system to another is analogous to well-established utilitarian operating procedures with traditional chemical reagents. The practical implications of the present results for experimental quantum control are discussed. PMID:24559348
Laboratory transferability of optimally shaped laser pulses for quantum control
NASA Astrophysics Data System (ADS)
Moore Tibbetts, Katharine; Xing, Xi; Rabitz, Herschel
2014-02-01
Optimal control experiments can readily identify effective shaped laser pulses, or "photonic reagents," that achieve a wide variety of objectives. An important additional practical desire is for photonic reagent prescriptions to produce good, if not optimal, objective yields when transferred to a different system or laboratory. Building on general experience in chemistry, the hope is that transferred photonic reagent prescriptions may remain functional even though all features of a shaped pulse profile at the sample typically cannot be reproduced exactly. As a specific example, we assess the potential for transferring optimal photonic reagents for the objective of optimizing a ratio of photoproduct ions from a family of halomethanes through three related experiments. First, applying the same set of photonic reagents with systematically varying second- and third-order chirp on both laser systems generated similar shapes of the associated control landscape (i.e., relation between the objective yield and the variables describing the photonic reagents). Second, optimal photonic reagents obtained from the first laser system were found to still produce near optimal yields on the second laser system. Third, transferring a collection of photonic reagents optimized on the first laser system to the second laser system reproduced systematic trends in photoproduct yields upon interaction with the homologous chemical family. These three transfers of photonic reagents are demonstrated to be successful upon paying reasonable attention to overall laser system characteristics. The ability to transfer photonic reagents from one laser system to another is analogous to well-established utilitarian operating procedures with traditional chemical reagents. The practical implications of the present results for experimental quantum control are discussed.
On necessary optimality conditions in discrete control systems
NASA Astrophysics Data System (ADS)
Mardanov, M. J.; Melikov, T. K.; Mahmudov, N. I.
2015-10-01
The paper deals with a nonlinear discrete-time optimal control problem with a cost functional of terminal type. Using a new variation of the control and new properties of optimal controls, we prove the linearised optimality conditions extending such classical optimality conditions. Along with this, various optimality conditions of quasi-singular controls are obtained. Finally, the examples illustrating the rich content of the obtained results are illustrated.
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 Qubit Control Using Single-Flux Quantum Pulses
NASA Astrophysics Data System (ADS)
Liebermann, Per J.; Wilhelm, Frank K.
2016-08-01
Single-flux quantum pulses are a natural candidate for on-chip control of superconducting qubits. We show that they can drive high-fidelity single-qubit rotations—even in leaky transmon qubits—if the pulse sequence is suitably optimized. We achieve this objective by showing that, for these restricted all-digital pulses, genetic algorithms can be made to converge to arbitrarily low error, verified up to a reduction in gate error by 2 orders of magnitude compared to an evenly spaced pulse train. Timing jitter of the pulses is taken into account, exploring the robustness of our optimized sequence. This approach takes us one step further towards on-chip qubit controls.
Optimal control of Atlantic population Canada geese
Hauser, C.E.; Runge, M.C.; Cooch, E.G.; Johnson, F.A.; Harvey, W.F.
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.
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 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.
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
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.
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.
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…
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.
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.
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
Optimal second order sliding mode control for nonlinear uncertain systems.
Das, Madhulika; Mahanta, Chitralekha
2014-07-01
In this paper, a chattering free optimal second order sliding mode control (OSOSMC) method is proposed to stabilize nonlinear systems affected by uncertainties. The nonlinear optimal control strategy is based on the control Lyapunov function (CLF). For ensuring robustness of the optimal controller in the presence of parametric uncertainty and external disturbances, a sliding mode control scheme is realized by combining an integral and a terminal sliding surface. The resulting second order sliding mode can effectively reduce chattering in the control input. Simulation results confirm the supremacy of the proposed optimal second order sliding mode control over some existing sliding mode controllers in controlling nonlinear systems affected by uncertainty.
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.
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 and robust control of robot manipulators
NASA Astrophysics Data System (ADS)
Grabbe, Michael Thomas
1992-01-01
The problem of controlling a robot manipulator typically requires determining the actuating torques at each joint, in the form of a feedback control law, which force the manipulator joint angles to follow a prescribed trajectory. This problem is often referred to as the trajectory tracking problem, and is difficult to solve due to the highly nonlinear dynamics associated with the robot manipulator and the time variance of the system induced by the prescribed trajectory. The complexity of the problem is compounded in cases where the manipulator end effector is constrained by contact with a surface, there are modeling or parametric uncertainties in the manipulator dynamics, or there are disturbances to the system. The trajectory tracking problem is addressed in two distinct cases. The first case involves the ideal situation in which the manipulator is unconstrained in its motion and there are no uncertainties or disturbances in the system. Optimal control theory is used to develop a class of feedback control laws which produce a globally uniformly asymptotically stable (GUAS) system. The second case involves both constrained motion and the possibilities of uncertainties and disturbances in the system. Two feedback control laws are developed which are robust with respect to uncertainties and disturbances, provide globally exponentially stable (GES) position tracking error, and provide a means of regulating the force applied.
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.
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.
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
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.
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).
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.
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.
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.
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.
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…
Quantum optimal control theory in the linear response formalism
Castro, Alberto; Tokatly, I. V.
2011-09-15
Quantum optimal control theory (QOCT) aims at finding an external field that drives a quantum system in such a way that optimally achieves some predefined target. In practice, this normally means optimizing the value of some observable, a so-called merit function. In consequence, a key part of the theory is a set of equations, which provides the gradient of the merit function with respect to parameters that control the shape of the driving field. We show that these equations can be straightforwardly derived using the standard linear response theory, only requiring a minor generalization: the unperturbed Hamiltonian is allowed to be time dependent. As a result, the aforementioned gradients are identified with certain response functions. This identification leads to a natural reformulation of QOCT in terms of the Keldysh contour formalism of the quantum many-body theory. In particular, the gradients of the merit function can be calculated using the diagrammatic technique for nonequilibrium Green's functions, which should be helpful in the application of QOCT to computationally difficult many-electron problems.
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).
Optimal singular control with applications to trajectory optimization
NASA Technical Reports Server (NTRS)
Vinh, N. X.
1979-01-01
The switching conditions are expressed explicitly in terms of the derivatives of the Hamiltonians at the two ends of the switching. A new expression of the Kelley-Contensou necessary condition for the optimality of a singular arc is given. Some examples illustrating the application of the theory are presented.
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.
Renganathan, K; Bhaskar, VidhyaCharan
2011-07-01
In this paper, we propose an approach for achieving detection and identification of faults, and provide fault tolerant control for systems that are modeled using timed hybrid Petri nets. For this purpose, an observer based technique is adopted which is useful in detection of faults, such as sensor faults, actuator faults, signal conditioning faults, etc. The concepts of estimation, reachability and diagnosability have been considered for analyzing faulty behaviors, and based on the detected faults, different schemes are proposed for achieving fault tolerant control using optimization techniques. These concepts are applied to a typical three tank system and numerical results are obtained.
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
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.
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.
Achieving Control of Occupational Exposures to Engineered Nanomaterials.
Juric, Amanda; Meldrum, Richard; Liberda, Eric N
2015-01-01
Occupational exposures resulting from Engineered Nanomaterials (ENMs) can pose a challenge for applying traditional risk assessment, control, or evaluation standards. This article discusses the limitations in traditional risk management approaches when it comes to ENM exposures, reviews current monitoring options, and suggests an interim management framework until research can meet the standard of evidence required by legislators. The proposed Nanomaterial Occupational Exposure Management Model (NOEM) offers a pragmatic approach that integrates resources from current academic research to provide a framework that can be applied by both industry and regulators. The NOEM Model focuses on addressing three concerns to exposure management: Risk Assessment, Exposure Control, and Exposure Monitoring. The resources supported for meeting these three components involve the integration of the Control Banding Nanotool and Nano Reference Values, both of which have been piloted and accepted through peer-reviewed processes and industry consultation.
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…
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.
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…
[Strategy of tuberculosis control and achievement in Okinawa].
2001-10-01
After fierce battles in World War II, Okinawa was occupied by military of U.S.A. and consequently was administrated by USCAR (United States Civil Administration of Ryukyus). During 27 years from April 1945 to May 1972, reversion to Japan, the public Health Activities including T.B. control were performed by Ryukyus Government indirectly controlled by USCAR. The first issue of T.B. statistics was made in 1950. It revealed remarkable reduction of T.B. death rate, a quarter of that before the war. The main reasons of the reduction were considered due to the over-death in battles. But epidemic of T.B. had increased rapidly, especially since the Korean War occurred in 1950. Constructions of the military base were booming, and T.B. infection was spread among laborers, employees, and also their families. Then, Ryukyus Government enacted a temporary law of T.B. prevention and control in 1954. Home-care treatment of T.B. patient was started with registration and management in newly constructed Public Health Centers. Because of shortage of government budget, man-power including doctor and poor institutes, a system of short-termed admission treatment (6 months) and home cared chemotherapy were started. Public Health Nurses (PHN) took care the patient at home, and medical fee of T.B. treatment was free in charge to patients. So activities of PHN were very important. In 1962, Dr. Shoukou Imamura, from JATA, came to study the system of home care treatment. And 7,000 cases under supervision of Public Health Center were investigated. He reported that this system was fairly efficacious in Okinawa. In 1976, after reversion to Japan, study of T.B. surveillance control system was advised and introduced by Dr. Masakazu Aoki and Dr. Tooru Mori (JATA). By this modern system of surveillance, T.B. control is improved progressively in Okinawa. PMID:11712390
Optimality Conditions for Semilinear Hyperbolic Equations with Controls in Coefficients
Li Bo; Lou Hongwei
2012-06-15
An optimal control problem for semilinear hyperbolic partial differential equations is considered. The control variable appears in coefficients. Necessary conditions for optimal controls are established by method of two-scale convergence and homogenized spike variation. Results for problems with state constraints are also stated.
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.
Design optimization of piezoelectric actuator patterns for static shape control of smart plates
NASA Astrophysics Data System (ADS)
Sun, Dongchang; Tong, Liyong
2005-12-01
This paper presents an investigation into design optimization of actuator patterns for static shape control of composite plates with piezoelectric actuator patches. An energy optimization based method for finding the optimal control voltages that can actuate a structure shape close to the desired one within a given error is described. Moreover, a voltage limitation for each actuator is also imposed to keep its control voltage within a practical range. An evolutionary actuator pattern optimization scheme is presented in which trivial actuators with the smallest voltages are electrically or physically removed step by step until the given tolerable error is reached. Finally, illustrative examples are given to demonstrate the effectiveness of the present equivalent element and the design optimization scheme. Numerical results show that satisfactory static shape control can be achieved even after a number of actuators are removed.
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.
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
Control of invasive meningococcal disease: is it achievable?
Marshall, Helen; Wang, Bing; Wesselingh, Steve; Snape, Matthew; Pollard, Andrew J
2016-03-01
Neisseria meningitidis still leads to deaths and severe disability in children, adolescents and adults. Six different capsular groups of N. meningitidis cause invasive meningococcal disease in the form of meningitis and septicaemia in humans. Although conjugate meningococcal vaccines have been developed to provide protection against four of the capsular groups causing most diseases in humans, vaccines against capsular group B, which causes 85% of cases in Australia and the United Kingdom, have only recently been developed. A capsular group B meningococcal vaccine - 4CMenB (Bexsero) - has recently been licensed in the European Union, Canada and Australia. In Australia, a submission for inclusion of 4CMenB in the funded national immunization programme has recently been rejected. The vaccine will now be introduced into the national immunization programme in the United Kingdom following negotiation of a cost-effective price. With the current low incidence of invasive meningococcal disease in many regions, cost-effectiveness of a new capsular group B meningococcal vaccine is borderline in both the United Kingdom and Australia. Cost-effectiveness of an infant programme is determined largely by the direct protection of those vaccinated and is driven by the higher rate of disease in this age group. However, for an adolescent programme to be cost-effective, it must provide both long-term protection against both disease and carriage. The potential of vaccination to reduce the rate of severe invasive disease is a real possibility. A dual approach using both an infant and adolescent immunization programme to provide direct protection to those age groups at highest risk of meningococcal disease and to optimize the potential herd immunity effects is likely to be the most effective means of reducing invasive meningococcal disease. This commentary aims to describe the known disease burden and consequences of meningococcal disease, and the development and potential effectiveness of
NASA Astrophysics Data System (ADS)
Briceño-Arias, Luis M.; Hoang, Nguyen Dinh; Peypouquet, Juan
2016-01-01
We study optimal control problems governed by maximal monotone differential inclusions with mixed control-state constraints in infinite dimensional spaces. We obtain some existence results for this kind of dynamics and construct the discrete approximations that allows us to strongly approximate optimal solutions of the continuous-type optimal control problems by their discrete counterparts. Our approach allows us to apply our results for a wide class of mappings that are applicable in mechanics and material sciences.
Optimal Control for a Parallel Hybrid Hydraulic Excavator Using Particle Swarm Optimization
Wang, Dong-yun; Guan, Chen
2013-01-01
Optimal control using particle swarm optimization (PSO) is put forward in a parallel hybrid hydraulic excavator (PHHE). A power-train mathematical model of PHHE is illustrated along with the analysis of components' parameters. Then, the optimal control problem is addressed, and PSO algorithm is introduced to deal with this nonlinear optimal problem which contains lots of inequality/equality constraints. Then, the comparisons between the optimal control and rule-based one are made, and the results show that hybrids with the optimal control would increase fuel economy. Although PSO algorithm is off-line optimization, still it would bring performance benchmark for PHHE and also help have a deep insight into hybrid excavators. PMID:23818832
Achievements in and Challenges of Tuberculosis Control in South Korea
Kim, Ji Han
2015-01-01
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
Smooth Optimal Quantum Control for Robust Solid-State Spin Magnetometry
NASA Astrophysics Data System (ADS)
Nöbauer, Tobias; Angerer, Andreas; Bartels, Björn; Trupke, Michael; Rotter, Stefan; Schmiedmayer, Jörg; Mintert, Florian; Majer, Johannes
2015-11-01
We experimentally demonstrate a simple yet versatile optimal quantum control technique that achieves tailored robustness against qubit inhomogeneities and control errors while requiring minimal bandwidth. We apply the technique to nitrogen-vacancy (NV) centers in diamond and verify its performance using quantum process tomography. In a wide-field NV center magnetometry scenario, we achieve a homogeneous sensitivity across a 33% drop in control amplitude, and we improve the sensitivity by up to 2 orders of magnitude for a normalized detuning as large as 40%, achieving a value of 20 nT Hz-1 /2 μ m3 /2 in sensitivity times square root volume.
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.
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
Pan, Zilai; Pang, Lifang; Li, Jianying; Zhang, Huan; Yang, Wenjie; Ding, Bei; Chai, Weimin; Chen, Kemin; Yao, Weiwu
2011-04-01
To evaluate the clinical value of a body mass index (BMI) based tube current (mA) selection method for obtaining consistent image quality with dose optimization in MDCT prospective ECG gated coronary calcium scoring. A formula for selecting mA to achieve desired image quality based on patient BMI was established using a control group (A) of 200 MDCT cardiac patients with a standard scan protocol. One hundred patients in Group B were scanned with this BMI-dependent mA for achieving a desired noise level of 18 HU at 2.5 mm slice thickness. The CTDIvol and image noise on the ascending aorta for the two groups were recorded. Two experienced radiologists quantitatively evaluated the image quality using scores of 1-4 with 4 being the highest. The image quality scores had no statistical difference (P = 0.71) at 3.89 ± 0.32, 3.87 ± 0.34, respectively, for groups A and B of similar BMI. The image noise in Group A had linear relationship with BMI. The image noise in Group B using BMI-dependent mA was independent of BMI with average value of 17.9 HU and smaller deviations for the noise values than in Group A (2.0 vs. 2.9 HU). There was a 35% dose reduction with BMI-dependent mA selection method on average with the lowest effective dose being only 0.35 mSv for patient with BMI of 18.3. A quantitative BMI-based mA selection method in MDCT prospective ECG gated coronary calcium scoring has been proposed to obtain a desired and consistent image quality and provide dose optimization across patient population.
Muscle function in avian flight: achieving power and control
Biewener, Andrew A.
2011-01-01
Flapping flight places strenuous requirements on the physiological performance of an animal. Bird flight muscles, particularly at smaller body sizes, generally contract at high frequencies and do substantial work in order to produce the aerodynamic power needed to support the animal's weight in the air and to overcome drag. This is in contrast to terrestrial locomotion, which offers mechanisms for minimizing energy losses associated with body movement combined with elastic energy savings to reduce the skeletal muscles' work requirements. Muscles also produce substantial power during swimming, but this is mainly to overcome body drag rather than to support the animal's weight. Here, I review the function and architecture of key flight muscles related to how these muscles contribute to producing the power required for flapping flight, how the muscles are recruited to control wing motion and how they are used in manoeuvring. An emergent property of the primary flight muscles, consistent with their need to produce considerable work by moving the wings through large excursions during each wing stroke, is that the pectoralis and supracoracoideus muscles shorten over a large fraction of their resting fibre length (33–42%). Both muscles are activated while being lengthened or undergoing nearly isometric force development, enhancing the work they perform during subsequent shortening. Two smaller muscles, the triceps and biceps, operate over a smaller range of contractile strains (12–23%), reflecting their role in controlling wing shape through elbow flexion and extension. Remarkably, pigeons adjust their wing stroke plane mainly via changes in whole-body pitch during take-off and landing, relative to level flight, allowing their wing muscles to operate with little change in activation timing, strain magnitude and pattern. PMID:21502121
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.
Optimal control theory for unitary transformations
Palao, Jose P.; Kosloff, Ronnie
2003-12-01
The dynamics of a quantum system driven by an external field is well described by a unitary transformation generated by a time-dependent Hamiltonian. The inverse problem of finding the field that generates a specific unitary transformation is the subject of study. The unitary transformation which can represent an algorithm in a quantum computation is imposed on a subset of quantum states embedded in a larger Hilbert space. Optimal control theory is used to solve the inversion problem irrespective of the initial input state. A unified formalism based on the Krotov method is developed leading to a different scheme. The schemes are compared for the inversion of a two-qubit Fourier transform using as registers the vibrational levels of the X {sup 1}{sigma}{sub g}{sup +} electronic state of Na{sub 2}. Raman-like transitions through the A {sup 1}{sigma}{sub u}{sup +} electronic state induce the transitions. Light fields are found that are able to implement the Fourier transform within a picosecond time scale. Such fields can be obtained by pulse-shaping techniques of a femtosecond pulse. Of the schemes studied, the square modulus scheme converges fastest. A study of the implementation of the Q qubit Fourier transform in the Na{sub 2} molecule was carried out for up to five qubits. The classical computation effort required to obtain the algorithm with a given fidelity is estimated to scale exponentially with the number of levels. The observed moderate scaling of the pulse intensity with the number of qubits in the transformation is rationalized.
Searching for quantum optimal controls under severe constraints
NASA Astrophysics Data System (ADS)
Riviello, Gregory; Tibbetts, Katharine Moore; Brif, Constantin; Long, Ruixing; Wu, Re-Bing; Ho, Tak-San; Rabitz, Herschel
2015-04-01
The success of quantum optimal control for both experimental and theoretical objectives is connected to the topology of the corresponding control landscapes, which are free from local traps if three conditions are met: (1) the quantum system is controllable, (2) the Jacobian of the map from the control field to the evolution operator is of full rank, and (3) there are no constraints on the control field. This paper investigates how the violation of assumption (3) affects gradient searches for globally optimal control fields. The satisfaction of assumptions (1) and (2) ensures that the control landscape lacks fundamental traps, but certain control constraints can still introduce artificial traps. Proper management of these constraints is an issue of great practical importance for numerical simulations as well as optimization in the laboratory. Using optimal control simulations, we show that constraints on quantities such as the number of control variables, the control duration, and the field strength are potentially severe enough to prevent successful optimization of the objective. For each such constraint, we show that exceeding quantifiable limits can prevent gradient searches from reaching a globally optimal solution. These results demonstrate that careful choice of relevant control parameters helps to eliminate artificial traps and facilitates successful optimization.
Liu, Ping; Li, Guodong; Liu, Xinggao
2015-09-01
Control vector parameterization (CVP) is an important approach of the engineering optimization for the industrial dynamic processes. However, its major defect, the low optimization efficiency caused by calculating the relevant differential equations in the generated nonlinear programming (NLP) problem repeatedly, limits its wide application in the engineering optimization for the industrial dynamic processes. A novel highly effective control parameterization approach, fast-CVP, is first proposed to improve the optimization efficiency for industrial dynamic processes, where the costate gradient formulae is employed and a fast approximate scheme is presented to solve the differential equations in dynamic process simulation. Three well-known engineering optimization benchmark problems of the industrial dynamic processes are demonstrated as illustration. The research results show that the proposed fast approach achieves a fine performance that at least 90% of the computation time can be saved in contrast to the traditional CVP method, which reveals the effectiveness of the proposed fast engineering optimization approach for the industrial dynamic processes.
Metal-binding sites are designed to achieve optimal mechanical and signaling properties.
Dutta, Anindita; Bahar, Ivet
2010-09-01
Many proteins require bound metals to achieve their function. We take advantage of increasing structural data on metal-binding proteins to elucidate three properties: the involvement of metal-binding sites in the global dynamics of the protein, predicted by elastic network models, their exposure/burial to solvent, and their signal-processing properties indicated by Markovian stochastics analysis. Systematic analysis of a data set of 145 structures reveals that the residues that coordinate metal ions enjoy remarkably efficient and precise signal transduction properties. These properties are rationalized in terms of their physical properties: participation in hinge sites that control the softest modes collectively accessible to the protein and occupancy of central positions minimally exposed to solvent. Our observations suggest that metal-binding sites may have been evolutionary selected to achieve optimum allosteric communication. They also provide insights into basic principles for designing metal-binding sites, which are verified to be met by recently designed de novo metal-binding proteins.
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.
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.
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.
Valiente, Carlos; Swanson, Jodi; Lemery-Chalfant, Kathryn; Berger, Rebecca H
2014-08-01
Given that early academic achievement is related to numerous developmental outcomes, understanding processes that promote early success in school is important. This study was designed to clarify how students' (N=291; M age in fall of kindergarten=5.66 years, SD=0.39 year) effortful control, relational peer victimization, and classroom participation relate to achievement, as students progress from kindergarten to first grade. Effortful control and achievement were assessed in kindergarten, classroom participation and relational peer victimization were assessed in the fall of first grade, and achievement was reassessed in the spring of first grade. Classroom participation, but not relational peer victimization, mediated relations between effortful control and first grade standardized and teacher-rated achievement, controlling for kindergarten achievement. Findings suggest that aspects of classroom participation, such as the ability to work independently, may be useful targets of intervention for enhancing academic achievement in young children. PMID:25107413
Bendall; Skinner
1998-10-01
for a single sech/tanh pulse. Residual splitting of the centerband, normally associated with incomplete or inefficient decoupling, is not seen in sech/tanh decoupling and therefore cannot be used as a measure of adiabatic decoupling efficiency. The calibrated experimental performance levels achieved in this study are within 20% of theoretical performance levels derived previously for ideal sech/tanh decoupling at high power, indicating a small scope for further improvement at practical RF power levels. The optimization procedures employed here will be generally applicable to any good combination of adiabatic inversion pulse and phase cycle. Copyright 1998 Academic Press. PMID:9761708
NASA Astrophysics Data System (ADS)
Hocker, David Lance
The control of quantum systems occurs across a broad range of length and energy scales in modern science, and efforts have demonstrated that locating suitable controls to perform a range of objectives has been widely successful. The justification for this success arises from a favorable topology of a quantum control landscape, defined as a mapping of the controls to a cost function measuring the success of the operation. This is summarized in the landscape principle that no suboptimal extrema exist on the landscape for well-suited control problems, explaining a trend of successful optimizations in both theory and experiment. This dissertation explores what additional lessons may be gleaned from the quantum control landscape through numerical and theoretical studies. The first topic examines the experimentally relevant problem of assessing and reducing disturbances due to noise. The local curvature of the landscape is found to play an important role on noise effects in the control of targeted quantum unitary operations, and provides a conceptual framework for assessing robustness to noise. Software for assessing noise effects in quantum computing architectures was also developed and applied to survey the performance of current quantum control techniques for quantum computing. A lack of competition between robustness and perfect unitary control operation was discovered to fundamentally limit noise effects, and highlights a renewed focus upon system engineering for reducing noise. This convergent behavior generally arises for any secondary objective in the situation of high primary objective fidelity. The other dissertation topic examines the utility of quantum control for a class of nonlinear Hamiltonians not previously considered under the landscape principle. Nonlinear Schrodinger equations are commonly used to model the dynamics of Bose-Einstein condensates (BECs), one of the largest known quantum objects. Optimizations of BEC dynamics were performed in which the
Optimizing Sensor and Actuator Arrays for ASAC Noise Control
NASA Technical Reports Server (NTRS)
Palumbo, Dan; Cabell, Ran
2000-01-01
This paper summarizes the development of an approach to optimizing the locations for arrays of sensors and actuators in active noise control systems. A type of directed combinatorial search, called Tabu Search, is used to select an optimal configuration from a much larger set of candidate locations. The benefit of using an optimized set is demonstrated. The importance of limiting actuator forces to realistic levels when evaluating the cost function is discussed. Results of flight testing an optimized system are presented. Although the technique has been applied primarily to Active Structural Acoustic Control systems, it can be adapted for use in other active noise control implementations.
Stochastic Optimal Control for Series Hybrid Electric Vehicles
Malikopoulos, Andreas
2013-01-01
Increasing demand for improving fuel economy and reducing emissions has stimulated significant research and investment in hybrid propulsion systems. In this paper, we address the problem of optimizing online the supervisory control in a series hybrid configuration by modeling its operation as a controlled Markov chain using the average cost criterion. We treat the stochastic optimal control problem as a dual constrained optimization problem. We show that the control policy that yields higher probability distribution to the states with low cost and lower probability distribution to the states with high cost is an optimal control policy, defined as an equilibrium control policy. We demonstrate the effectiveness of the efficiency of the proposed controller in a series hybrid configuration and compare it with a thermostat-type controller.
Winter, David G
2010-12-01
Several decades of research have established that implicit achievement motivation (n Achievement) is associated with success in business, particularly in entrepreneurial or sales roles. However, several political psychology studies have shown that achievement motivation is not associated with success in politics; rather, implicit power motivation often predicts political success. Having versus lacking control may be a key difference between business and politics. Case studies suggest that achievement-motivated U.S. presidents and other world leaders often become frustrated and thereby fail because of lack of control, whereas power-motivated presidents develop ways to work with this inherent feature of politics. A reevaluation of previous research suggests that, in fact, relationships between achievement motivation and business success only occur when control is high. The theme of control is also prominent in the development of achievement motivation. Cross-national data are also consistent with this analysis: In democratic industrialized countries, national levels of achievement motivation are associated with strong executive control. In countries with low opportunity for education (thus fewer opportunities to develop a sense of personal control), achievement motivation is associated with internal violence. Many of these manifestations of frustrated achievement motivation in politics resemble authoritarianism. This conclusion is tested by data from a longitudinal study of 113 male college students, showing that high initial achievement motivation combined with frustrated desires for control is related to increases in authoritarianism (F-scale scores) during the college years. Implications for the psychology of leadership and practical politics are discussed.
A criterion for joint optimization of identification and robust control
NASA Technical Reports Server (NTRS)
Bayard, D. S.; Yam, Y.; Mettler, E.
1992-01-01
A criterion for system identification is developed that is consistent with the intended used of the fitted model for modern robust control synthesis. Specifically, a joint optimization problem is posed which simultaneously solves the plant model estimate and control design, so as to optimize robust performance over the set of plants consistent with a specified experimental data set.
Educational Tool for Optimal Controller Tuning Using Evolutionary Strategies
ERIC Educational Resources Information Center
Carmona Morales, D.; Jimenez-Hornero, J. E.; Vazquez, F.; Morilla, F.
2012-01-01
In this paper, an optimal tuning tool is presented for control structures based on multivariable proportional-integral-derivative (PID) control, using genetic algorithms as an alternative to traditional optimization algorithms. From an educational point of view, this tool provides students with the necessary means to consolidate their knowledge on…
Attitude Control Optimization for ROCSAT-2 Operation
NASA Astrophysics Data System (ADS)
Chern, Jeng-Shing; Wu, A.-M.
one revolution. The purpose of this paper is to present the attitude control design optimization such that the maximum solar energy is ingested while minimum maneuvering energy is dissipated. The strategy includes the maneuvering sequence design, the minimization of angular path, the sizing of three magnetic torquers, and the trade-off of the size, number and orientations arrangement of momentum wheels.
In-flight performance optimization for rotorcraft with redundant controls
NASA Astrophysics Data System (ADS)
Ozdemir, Gurbuz Taha
A conventional helicopter has limits on performance at high speeds because of the limitations of main rotor, such as compressibility issues on advancing side or stall issues on retreating side. Auxiliary lift and thrust components have been suggested to improve performance of the helicopter substantially by reducing the loading on the main rotor. Such a configuration is called the compound rotorcraft. Rotor speed can also be varied to improve helicopter performance. In addition to improved performance, compound rotorcraft and variable RPM can provide a much larger degree of control redundancy. This additional redundancy gives the opportunity to further enhance performance and handling qualities. A flight control system is designed to perform in-flight optimization of redundant control effectors on a compound rotorcraft in order to minimize power required and extend range. This "Fly to Optimal" (FTO) control law is tested in simulation using the GENHEL model. A model of the UH-60, a compound version of the UH-60A with lifting wing and vectored thrust ducted propeller (VTDP), and a generic compound version of the UH-60A with lifting wing and propeller were developed and tested in simulation. A model following dynamic inversion controller is implemented for inner loop control of roll, pitch, yaw, heave, and rotor RPM. An outer loop controller regulates airspeed and flight path during optimization. A Golden Section search method was used to find optimal rotor RPM on a conventional helicopter, where the single redundant control effector is rotor RPM. The FTO builds off of the Adaptive Performance Optimization (APO) method of Gilyard by performing low frequency sweeps on a redundant control for a fixed wing aircraft. A method based on the APO method was used to optimize trim on a compound rotorcraft with several redundant control effectors. The controller can be used to optimize rotor RPM and compound control effectors through flight test or simulations in order to
Active vibration control for flexible rotor by optimal direct-output feedback control
NASA Technical Reports Server (NTRS)
Nonami, Kenzou; Dirusso, Eliseo; Fleming, David P.
1989-01-01
Experimental research tests were performed to actively control the rotor vibrations of a flexible rotor mounted on flexible bearing supports. The active control method used in the tests is called optimal direct-output feedback control. This method uses four electrodynamic actuators to apply control forces directly to the bearing housings in order to achieve effective vibration control of the rotor. The force actuators are controlled by an analog controller that accepts rotor displacement as input. The controller is programmed with experimentally determined feedback coefficients; the output is a control signal to the force actuators. The tests showed that this active control method reduced the rotor resonance peaks due to unbalance from approximately 250 micrometers down to approximately 25 micrometers (essentially runout level). The tests were conducted over a speed range from 0 to 10,000 rpm; the rotor system had nine critical speeds within this speed range. The method was effective in significantly reducing the rotor vibration for all of the vibration modes and critical speeds.
Active vibration control for flexible rotor by optimal direct-output feedback control
NASA Technical Reports Server (NTRS)
Nonami, K.; Dirusso, E.; Fleming, D. P.
1989-01-01
Experimental research tests were performed to actively control the rotor vibrations of a flexible rotor mounted on flexible bearing supports. The active control method used in the tests is called optimal direct-output feedback control. This method uses four electrodynamic actuators to apply control forces directly to the bearing housings in order to achieve effective vibration control of the rotor. The force actuators are controlled by an analog controller that accepts rotor displacement as input. The controller is programmed with experimentally determined feedback coefficients; the output is a control signal to the force actuators. The tests showed that this active control method reduced the rotor resonance peaks due to unbalance from approximately 250 microns down to approximately 25 microns (essentially runout level). The tests were conducted over a speed range from 0 to 10,000 rpm; the rotor system had nine critical speeds within this speed range. The method was effective in significantly reducing the rotor vibration for all of the vibration modes and critical speeds.
Optimization and Control of Electric Power Systems
Lesieutre, Bernard C.; Molzahn, Daniel K.
2014-10-17
The analysis and optimization needs for planning and operation of the electric power system are challenging due to the scale and the form of model representations. The connected network spans the continent and the mathematical models are inherently nonlinear. Traditionally, computational limits have necessitated the use of very simplified models for grid analysis, and this has resulted in either less secure operation, or less efficient operation, or both. The research conducted in this project advances techniques for power system optimization problems that will enhance reliable and efficient operation. The results of this work appear in numerous publications and address different application problems include optimal power flow (OPF), unit commitment, demand response, reliability margins, planning, transmission expansion, as well as general tools and algorithms.
Robust Airfoil Optimization to Achieve Consistent Drag Reduction Over a Mach Range
NASA Technical Reports Server (NTRS)
Li, Wu; Huyse, Luc; Padula, Sharon; Bushnell, Dennis M. (Technical Monitor)
2001-01-01
We prove mathematically that in order to avoid point-optimization at the sampled design points for multipoint airfoil optimization, the number of design points must be greater than the number of free-design variables. To overcome point-optimization at the sampled design points, a robust airfoil optimization method (called the profile optimization method) is developed and analyzed. This optimization method aims at a consistent drag reduction over a given Mach range and has three advantages: (a) it prevents severe degradation in the off-design performance by using a smart descent direction in each optimization iteration, (b) there is no random airfoil shape distortion for any iterate it generates, and (c) it allows a designer to make a trade-off between a truly optimized airfoil and the amount of computing time consumed. For illustration purposes, we use the profile optimization method to solve a lift-constrained drag minimization problem for 2-D airfoil in Euler flow with 20 free-design variables. A comparison with other airfoil optimization methods is also included.
The optimal dynamic immunization under a controlled heterogeneous node-based SIRS model
NASA Astrophysics Data System (ADS)
Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan
2016-05-01
Dynamic immunizations, under which the state of the propagation network of electronic viruses can be changed by adjusting the control measures, are regarded as an alternative to static immunizations. This paper addresses the optimal dynamical immunization under the widely accepted SIRS assumption. First, based on a controlled heterogeneous node-based SIRS model, an optimal control problem capturing the optimal dynamical immunization is formulated. Second, the existence of an optimal dynamical immunization scheme is shown, and the corresponding optimality system is derived. Next, some numerical examples are given to show that an optimal immunization strategy can be worked out by numerically solving the optimality system, from which it is found that the network topology has a complex impact on the optimal immunization strategy. Finally, the difference between a payoff and the minimum payoff is estimated in terms of the deviation of the corresponding immunization strategy from the optimal immunization strategy. The proposed optimal immunization scheme is justified, because it can achieve a low level of infections at a low cost.
New Applications of Variational Analysis to Optimization and Control
NASA Astrophysics Data System (ADS)
Mordukhovich, Boris S.
We discuss new applications of advanced tools of variational analysis and generalized differentiation to a number of important problems in optimization theory, equilibria, optimal control, and feedback control design. The presented results are largely based on the recent work by the author and his collaborators. Among the main topics considered and briefly surveyed in this paper are new calculus rules for generalized differentiation of nonsmooth and set-valued mappings; necessary and sufficient conditions for new notions of linear subextremality and suboptimality in constrained problems; optimality conditions for mathematical problems with equilibrium constraints; necessary optimality conditions for optimistic bilevel programming with smooth and nonsmooth data; existence theorems and optimality conditions for various notions of Pareto-type optimality in problems of multiobjective optimization with vector-valued and set-valued cost mappings; Lipschitzian stability and metric regularity aspects for constrained and variational systems.
Matching trajectory optimization and nonlinear tracking control for HALE
NASA Astrophysics Data System (ADS)
Lee, Sangjong; Jang, Jieun; Ryu, Hyeok; Lee, Kyun Ho
2014-11-01
This paper concerns optimal trajectory generation and nonlinear tracking control for stratospheric airship platform of VIA-200. To compensate for the mismatch between the point-mass model of optimal trajectory and the 6-DOF model of the nonlinear tracking problem, a new matching trajectory optimization approach is proposed. The proposed idea reduces the dissimilarity of both problems and reduces the uncertainties in the nonlinear equations of motion for stratospheric airship. In addition, its refined optimal trajectories yield better results under jet stream conditions during flight. The resultant optimal trajectories of VIA-200 are full three-dimensional ascent flight trajectories reflecting the realistic constraints of flight conditions and airship performance with and without a jet stream. Finally, 6-DOF nonlinear equations of motion are derived, including a moving wind field, and the vectorial backstepping approach is applied. The desirable tracking performance is demonstrated that application of the proposed matching optimization method enables the smooth linkage of trajectory optimization to tracking control problems.
Edge orientation for optimizing controllability of complex networks
NASA Astrophysics Data System (ADS)
Xiao, Yan-Dong; Lao, Song-Yang; Hou, Lv-Lin; Bai, Liang
2014-10-01
Recently, as the controllability of complex networks attracts much attention, how to design and optimize the controllability of networks has become a common and urgent problem in the field of controlling complex networks. Previous work focused on the structural perturbation and neglected the role of edge direction to optimize the network controllability. In a recent work [Phys. Rev. Lett. 103, 228702 (2009), 10.1103/PhysRevLett.103.228702], the authors proposed a simple method to enhance the synchronizability of networks by assignment of link direction while keeping network topology unchanged. However, the controllability is fundamentally different from synchronization. In this work, we systematically propose the definition of assigning direction to optimize controllability, which is called the edge orientation for optimal controllability problem (EOOC). To solve the EOOC problem, we construct a switching network and transfer the EOOC problem to find the maximum independent set of the switching network. We prove that the principle of our optimization method meets the sense of unambiguity and optimum simultaneously. Furthermore, the relationship between the degree-degree correlations and EOOC are investigated by experiments. The results show that the disassortativity pattern could weaken the orientation for optimal controllability, while the assortativity pattern has no correlation with EOOC. All the experimental results of this work verify that the network structure determines the network controllability and the optimization effects.
Edge orientation for optimizing controllability of complex networks.
Xiao, Yan-Dong; Lao, Song-Yang; Hou, Lv-Lin; Bai, Liang
2014-10-01
Recently, as the controllability of complex networks attracts much attention, how to design and optimize the controllability of networks has become a common and urgent problem in the field of controlling complex networks. Previous work focused on the structural perturbation and neglected the role of edge direction to optimize the network controllability. In a recent work [Phys. Rev. Lett. 103, 228702 (2009)], the authors proposed a simple method to enhance the synchronizability of networks by assignment of link direction while keeping network topology unchanged. However, the controllability is fundamentally different from synchronization. In this work, we systematically propose the definition of assigning direction to optimize controllability, which is called the edge orientation for optimal controllability problem (EOOC). To solve the EOOC problem, we construct a switching network and transfer the EOOC problem to find the maximum independent set of the switching network. We prove that the principle of our optimization method meets the sense of unambiguity and optimum simultaneously. Furthermore, the relationship between the degree-degree correlations and EOOC are investigated by experiments. The results show that the disassortativity pattern could weaken the orientation for optimal controllability, while the assortativity pattern has no correlation with EOOC. All the experimental results of this work verify that the network structure determines the network controllability and the optimization effects. PMID:25375546
Optimal Control of Airfoil Flow Separation using Fluidic Excitation
NASA Astrophysics Data System (ADS)
Shahrabi, Arireza F.
This thesis deals with the control of flow separation around a symmetric airfoils with the aid of multiple synthetic jet actuators (SJAs). CFD simulation methods have been implemented to uncover the flow separation regimes and associated properties such as frequencies and momentum ratio. In the first part of the study, the SJA was studied thoroughly. Large Eddy Simulations (LES) were performed for one individual cavity; the time history of SJA of the outlet velocity profile and the net momentum imparted to the flow were analyzed. The studied SJA is asymmetrical and operates with the aid of a piezoelectric (PZT) ceramic circular plate actuator. A three-dimensional mesh for the computational domain of the SJA and the surrounding volume was developed and was used to evaluate the details of the airflow conditions inside the SJA as well as at the outlet. The vibration of the PZT ceramic actuator was used as a boundary condition in the computational model to drive the SJA. Particular attention was given to developing a predictive model of the SJA outlet velocity. Results showed that the SJA velocity output is correlated to the PZT ceramic plate vibration, especially for the first frequency mode. SJAs are a particular class of zero net mass flux (ZNMF) fluidic devices with net imparted momentum to the flow. The net momentum imparted to the flow in the separated region is such that positive enhancement during AFC operations is achieved. Flows around the NACA 0015 airfoil were simulated for a range of operating conditions. Attention was given to the active open and closed loop control solutions for an airfoil with SJA at different angles of attack and flap angles. A large number of simulations using RANS & LES models were performed to study the effects of the momentum ratio (Cμ) in the range of 0 to 11% and of the non-dimensional frequency, F+, in the range of 0 to 2 for the control of flow separation at a practical angle of attack and flap angle. The optimum value of C
New attitude penalty functions for spacecraft optimal control problems
Schaub, H.; Junkins, J.L.; Robinett, R.D.
1996-03-01
A solution of a spacecraft optimal control problem, whose cost function relies on an attitude description, usually depends on the choice of attitude coordinates used. A problem could be solved using 3-2-1 Euler angles or using classical Rodriguez parameters and yield two different ``optimal`` solutions, unless the performance index in invariant with respect to the attitude coordinate choice. Another problem arising with many attitude coordinates is that they have no sense of when a body has tumbled beyond 180{degrees} from the reference attitude. In many such cases it would be easier (i.e. cost less) to let the body complete the revolution than to force it to reverse the rotation and return to the desired attitude. This paper develops a universal attitude penalty function g() whose value is independent of the attitude coordinates chosen to represent it. Furthermore, this function will achieve its maximum value only when a principal rotation of {plus_minus}180{degrees} from the target state is performed. This will implicitly permit the g() function to sense the shortest rotational distance back to the reference state. An attitude penalty function which depends on the Modified Rodriguez Parameters (MRP) will also be presented. These recently discovered MRPs are a non-singular three-parameter set which can describe any three-attitude. This MRP penalty function is simpler than the attitude coordinate independent g() function, but retains the useful property of avoiding lengthy principal rotations of more than {plus_minus}180{degrees}.
Stabilization of ultracold molecules using optimal control theory
Koch, Christiane P.; Palao, Jose P.; Kosloff, Ronnie; Masnou-Seeuws, Francoise
2004-07-01
In recent experiments on ultracold matter, molecules have been produced from ultracold atoms by photoassociation, Feshbach resonances, and three-body recombination. The created molecules are translationally cold, but vibrationally highly excited. This will eventually lead them to be lost from the trap due to collisions. We propose shaped laser pulses to transfer these highly excited molecules to their ground vibrational level. Optimal control theory is employed to find the light field that will carry out this task with minimum intensity. We present results for the sodium dimer. The final target can be reached to within 99% provided the initial guess field is physically motivated. We find that the optimal fields contain the transition frequencies required by a good Franck-Condon pumping scheme. The analysis identifies the ranges of intensity and pulse duration which are able to achieve this task before any other competing processes take place. Such a scheme could produce stable ultracold molecular samples or even stable molecular Bose-Einstein condensates.
Exact optimal solution for a class of dual control problems
NASA Astrophysics Data System (ADS)
Cao, Suping; Qian, Fucai; Wang, Xiaomei
2016-07-01
This paper considers a discrete-time stochastic optimal control problem for which only measurement equation is partially observed with unknown constant parameters taking value in a finite set of stochastic systems. Because of the fact that the cost-to-go function at each stage contains variance and the non-separability of the variance is so complicated that the dynamic programming cannot be successfully applied, the optimal solution has not been found. In this paper, a new approach to the optimal solution is proposed by embedding the original non-separable problem into a separable auxiliary problem. The theoretical condition on which the optimal solution of the original problem can be attained from a set of solutions of the auxiliary problem is established. In addition, the optimality of the interchanging algorithm is proved and the analytical solution of the optimal control is also obtained. The performance of this controller is illustrated with a simple example.
[Implementation of precision control to achieve the goal of schistosomiasis elimination in China].
Zhou, Xiao-nong
2016-02-01
The integrated strategy for schistosomiasis control with focus on infectious source control, which has been implemented since 2004, accelerated the progress towards schistosomiasis control in China, and achieved transmission control of the disease across the country by the end of 2015, which achieved the overall objective of the Mid- and Long-term National Plan for Prevention and Control of Schistosomiasis (2004-2015) on schedule. Then, the goal of schistosomiasis elimination by 2025 was proposed in China in 2014. To achieve this new goal on schedule, we have to address the key issues, and implement precision control measures with more precise identification of control targets, so that we are able to completely eradicate the potential factors leading to resurgence of schistosomiasis transmission and enable the achievement of schistosomiasis elimination on schedule. Precision schistosomiasis control, a theoretical innovation of precision medicine in schistosomiasis control, will provide new insights into schistosomiasis control based on the conception of precision medicine. This paper describes the definition, interventions and the role of precision schistosomiasis control in the elimination of schistosomiasis in China, and demonstrates that sustainable improvement of professionals and integrated control capability at grass-root level is a prerequisite to the implementation of schistosomiasis control, precision schistosomiasis control is a key to the further implementation of the integrated strategy for schistosomiasis control with focus on infectious source control, and precision schistosomiasis control is a guarantee of curing schistosomiasis patients and implementing schistosomiasis control program and interventions. PMID:27356396
[Implementation of precision control to achieve the goal of schistosomiasis elimination in China].
Zhou, Xiao-nong
2016-02-01
The integrated strategy for schistosomiasis control with focus on infectious source control, which has been implemented since 2004, accelerated the progress towards schistosomiasis control in China, and achieved transmission control of the disease across the country by the end of 2015, which achieved the overall objective of the Mid- and Long-term National Plan for Prevention and Control of Schistosomiasis (2004-2015) on schedule. Then, the goal of schistosomiasis elimination by 2025 was proposed in China in 2014. To achieve this new goal on schedule, we have to address the key issues, and implement precision control measures with more precise identification of control targets, so that we are able to completely eradicate the potential factors leading to resurgence of schistosomiasis transmission and enable the achievement of schistosomiasis elimination on schedule. Precision schistosomiasis control, a theoretical innovation of precision medicine in schistosomiasis control, will provide new insights into schistosomiasis control based on the conception of precision medicine. This paper describes the definition, interventions and the role of precision schistosomiasis control in the elimination of schistosomiasis in China, and demonstrates that sustainable improvement of professionals and integrated control capability at grass-root level is a prerequisite to the implementation of schistosomiasis control, precision schistosomiasis control is a key to the further implementation of the integrated strategy for schistosomiasis control with focus on infectious source control, and precision schistosomiasis control is a guarantee of curing schistosomiasis patients and implementing schistosomiasis control program and interventions.
Relations among Peer Acceptance, Inhibitory Control, and Math Achievement in Early Adolescence
ERIC Educational Resources Information Center
Oberle, Eva; Schonert-Reichl, Kimberly A.
2013-01-01
This study examined relations among peer acceptance, inhibitory control, and math achievement in ninety-nine 4th and 5th grade early adolescents. Teachers rated students on peer acceptance and students completed a computerized executive function task assessing inhibitory control. Math achievement was assessed via end of year math grades. Results…
ERIC Educational Resources Information Center
Nunn, Gary D.; And Others
1986-01-01
Investigated the relationships between student locus of control and academic achievement in grades five through eight. The Nowicki-Strickland Locus of Control Scale (NSLOCS) was used to measure motivation, and the Iowa Tests of Basic Skills (ITBS) to assess academic achievement. Results indicated moderate inverse relationships between level of…
ERIC Educational Resources Information Center
Vansteenkiste, Maarten; Lens, Willy; Elliot, Andrew J.; Soenens, Bart; Mouratidis, Athanasios
2014-01-01
An important recent development in the achievement goal literature is to define achievement goals strictly as aims. In this overview, we argue that this restrictive definition of achievement goals paves the way for a systematic consideration of the autonomous and controlled reasons underlying individuals' achievement goals, a distinction…
Weak Hamiltonian finite element method for optimal control problems
NASA Technical Reports Server (NTRS)
Hodges, Dewey H.; Bless, Robert R.
1991-01-01
A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.
A weak Hamiltonian finite element method for optimal control problems
NASA Technical Reports Server (NTRS)
Hodges, Dewey H.; Bless, Robert R.
1990-01-01
A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.
A weak Hamiltonian finite element method for optimal control problems
NASA Technical Reports Server (NTRS)
Hodges, Dewey H.; Bless, Robert R.
1989-01-01
A temporal finite element method based on a mixed form of the Hamiltonian weak principle is developed for dynamics and optimal control problems. The mixed form of Hamilton's weak principle contains both displacements and momenta as primary variables that are expanded in terms of nodal values and simple polynomial shape functions. Unlike other forms of Hamilton's principle, however, time derivatives of the momenta and displacements do not appear therein; instead, only the virtual momenta and virtual displacements are differentiated with respect to time. Based on the duality that is observed to exist between the mixed form of Hamilton's weak principle and variational principles governing classical optimal control problems, a temporal finite element formulation of the latter can be developed in a rather straightforward manner. Several well-known problems in dynamics and optimal control are illustrated. The example dynamics problem involves a time-marching problem. As optimal control examples, elementary trajectory optimization problems are treated.
ERIC Educational Resources Information Center
Sarouni, Ali Sedigh; Jenaabadi, Hossein; Pourghaz, Abdulwahab
2016-01-01
The present study aimed to examine the relationship of mental pressure with optimism and academic achievement motivation among second grade second period male high school students. This study followed a descriptive-correlational method. The sample included 200 second grade second period male high school students in Sooran. Data collection tools in…
ERIC Educational Resources Information Center
Boonen, Tinneke; Pinxten, Maarten; Van Damme, Jan; Onghena, Patrick
2014-01-01
Academic emphasis, collective efficacy, and faculty trust in students and parents (3 school characteristics positively associated with student achievement) are assumed to form a higher order latent construct, "academic optimism" (Hoy, Tarter, & Woolfolk Hoy, 2006a, 2006b). The aim of the present study is to corroborate the latent…
ERIC Educational Resources Information Center
Chang, I-Hua
2011-01-01
The purpose of this study was to explore the relationships between distributed leadership, teachers' academic optimism and student achievement in learning. The study targeted public elementary schools in Taiwan and adopted stratified random sampling to investigate 1500 teachers. Teachers' perceptions were collected by a self-report scale. In…
ERIC Educational Resources Information Center
Wu, Jason H.
2013-01-01
This study was designed to examine the construct of academic optimism and its relationship with collective responsibility in a sample of Taiwan elementary schools. The construct of academic optimism was tested using confirmatory factor analysis, and the whole structural model was tested with a structural equation modeling analysis. The data were…
Polyhedral Interpolation for Optimal Reaction Control System Jet Selection
NASA Technical Reports Server (NTRS)
Gefert, Leon P.; Wright, Theodore
2014-01-01
An efficient algorithm is described for interpolating optimal values for spacecraft Reaction Control System jet firing duty cycles. The algorithm uses the symmetrical geometry of the optimal solution to reduce the number of calculations and data storage requirements to a level that enables implementation on the small real time flight control systems used in spacecraft. The process minimizes acceleration direction errors, maximizes control authority, and minimizes fuel consumption.
A Riccati approach for constrained linear quadratic optimal control
NASA Astrophysics Data System (ADS)
Sideris, Athanasios; Rodriguez, Luis A.
2011-02-01
An active-set method is proposed for solving linear quadratic optimal control problems subject to general linear inequality path constraints including mixed state-control and state-only constraints. A Riccati-based approach is developed for efficiently solving the equality constrained optimal control subproblems generated during the procedure. The solution of each subproblem requires computations that scale linearly with the horizon length. The algorithm is illustrated with numerical examples.
Robust control systems design by H-infinity optimization theory
NASA Technical Reports Server (NTRS)
Chang, B. C.; Li, X. P.; Banda, S. S.; Yeh, H. H.
1991-01-01
In this paper, step-by-step procedures of applying the H-infinity theory to robust control systems design are given. The objective of the paper is to eliminate the possible difficulties a control engineer may encounter in applying H-infinity control theory and to clear up some misconceptions about H-infinity theory like high-gain controller and numerical obstacles, etc. An efficient algorithm is used to compute the optimal H-infinity norm. The Glover and Doyle (1988) controller formulas are slightly modified and used to construct an optimal controller without any numerical difficulties.
Neighboring extremal optimal control design including model mismatch errors
Kim, T.J.; Hull, D.G.
1994-11-01
The mismatch control technique that is used to simplify model equations of motion in order to determine analytic optimal control laws is extended using neighboring extremal theory. The first variation optimal control equations are linearized about the extremal path to account for perturbations in the initial state and the final constraint manifold. A numerical example demonstrates that the tuning procedure inherent in the mismatch control method increases the performance of the controls to the level of a numerically-determined piecewise-linear controller.
OPTIMAL CONTROL THEORY FOR SUSTAINABLE ENVIRONMENTAL MANAGEMENT
Sustainable management of the human and natural systems, taking into account their interactions, has become paramount. To achieve this complex multidisciplinary objective, systems theory based techniques prove useful. The proposed work is a step in that direction. Taking a food w...
Isometric Scaling in Developing Long Bones Is Achieved by an Optimal Epiphyseal Growth Balance
Stern, Tomer; Aviram, Rona; Rot, Chagai; Galili, Tal; Sharir, Amnon; Kalish Achrai, Noga; Keller, Yosi; Shahar, Ron; Zelzer, Elazar
2015-01-01
One of the major challenges that developing organs face is scaling, that is, the adjustment of physical proportions during the massive increase in size. Although organ scaling is fundamental for development and function, little is known about the mechanisms that regulate it. Bone superstructures are projections that typically serve for tendon and ligament insertion or articulation and, therefore, their position along the bone is crucial for musculoskeletal functionality. As bones are rigid structures that elongate only from their ends, it is unclear how superstructure positions are regulated during growth to end up in the right locations. Here, we document the process of longitudinal scaling in developing mouse long bones and uncover the mechanism that regulates it. To that end, we performed a computational analysis of hundreds of three-dimensional micro-CT images, using a newly developed method for recovering the morphogenetic sequence of developing bones. Strikingly, analysis revealed that the relative position of all superstructures along the bone is highly preserved during more than a 5-fold increase in length, indicating isometric scaling. It has been suggested that during development, bone superstructures are continuously reconstructed and relocated along the shaft, a process known as drift. Surprisingly, our results showed that most superstructures did not drift at all. Instead, we identified a novel mechanism for bone scaling, whereby each bone exhibits a specific and unique balance between proximal and distal growth rates, which accurately maintains the relative position of its superstructures. Moreover, we show mathematically that this mechanism minimizes the cumulative drift of all superstructures, thereby optimizing the scaling process. Our study reveals a general mechanism for the scaling of developing bones. More broadly, these findings suggest an evolutionary mechanism that facilitates variability in bone morphology by controlling the activity of
Isometric Scaling in Developing Long Bones Is Achieved by an Optimal Epiphyseal Growth Balance.
Stern, Tomer; Aviram, Rona; Rot, Chagai; Galili, Tal; Sharir, Amnon; Kalish Achrai, Noga; Keller, Yosi; Shahar, Ron; Zelzer, Elazar
2015-08-01
One of the major challenges that developing organs face is scaling, that is, the adjustment of physical proportions during the massive increase in size. Although organ scaling is fundamental for development and function, little is known about the mechanisms that regulate it. Bone superstructures are projections that typically serve for tendon and ligament insertion or articulation and, therefore, their position along the bone is crucial for musculoskeletal functionality. As bones are rigid structures that elongate only from their ends, it is unclear how superstructure positions are regulated during growth to end up in the right locations. Here, we document the process of longitudinal scaling in developing mouse long bones and uncover the mechanism that regulates it. To that end, we performed a computational analysis of hundreds of three-dimensional micro-CT images, using a newly developed method for recovering the morphogenetic sequence of developing bones. Strikingly, analysis revealed that the relative position of all superstructures along the bone is highly preserved during more than a 5-fold increase in length, indicating isometric scaling. It has been suggested that during development, bone superstructures are continuously reconstructed and relocated along the shaft, a process known as drift. Surprisingly, our results showed that most superstructures did not drift at all. Instead, we identified a novel mechanism for bone scaling, whereby each bone exhibits a specific and unique balance between proximal and distal growth rates, which accurately maintains the relative position of its superstructures. Moreover, we show mathematically that this mechanism minimizes the cumulative drift of all superstructures, thereby optimizing the scaling process. Our study reveals a general mechanism for the scaling of developing bones. More broadly, these findings suggest an evolutionary mechanism that facilitates variability in bone morphology by controlling the activity of
A mathematical basis for the design and design optimization of adaptive trusses in precision control
NASA Technical Reports Server (NTRS)
Das, S. K.; Utku, S.; Chen, G.-S.; Wada, B. K.
1991-01-01
A mathematical basis for the optimal design of adaptive trusses to be used in supporting precision equipment is provided. The general theory of adaptive structures is introduced, and the global optimization problem of placing a limited number, q, of actuators, so as to maximally achieve precision control and provide prestress, is stated. Two serialized optimization problems, namely, optimal actuator placement for prestress and optimal actuator placement for precision control, are addressed. In the case of prestressing, the computation of a 'desired' prestress is discussed, the interaction between actuators and redundants in conveying the prestress is shown in its mathematical form, and a methodology for arriving at the optimal placement of actuators and additional redundants is discussed. With regard to precision control, an optimal placement scheme (for q actuators) for maximum 'authority' over the precision points is suggested. The results of the two serialized optimization problems are combined to give a suboptimal solution to the global optimization problem. A method for improving this suboptimal actuator placement scheme by iteration is presented.
A duality framework for stochastic optimal control of complex systems
Malikopoulos, Andreas A.
2016-01-01
In this study, we address the problem of minimizing the long-run expected average cost of a complex system consisting of interactive subsystems. We formulate a multiobjective optimization problem of the one-stage expected costs of the subsystems and provide a duality framework to prove that the control policy yielding the Pareto optimal solution minimizes the average cost criterion of the system. We provide the conditions of existence and a geometric interpretation of the solution. For practical situations having constraints consistent with those studied here, our results imply that the Pareto control policy may be of value when we seek to derive online the optimal control policy in complex systems.
Optimal control of a harmonic oscillator: Economic interpretations
NASA Astrophysics Data System (ADS)
Janová, Jitka; Hampel, David
2013-10-01
Optimal control is a popular technique for modelling and solving the dynamic decision problems in economics. A standard interpretation of the criteria function and Lagrange multipliers in the profit maximization problem is well known. On a particular example, we aim to a deeper understanding of the possible economic interpretations of further mathematical and solution features of the optimal control problem: we focus on the solution of the optimal control problem for harmonic oscillator serving as a model for Phillips business cycle. We discuss the economic interpretations of arising mathematical objects with respect to well known reasoning for these in other problems.
Time dependent optimal switching controls in online selling models
Bradonjic, Milan; Cohen, Albert
2010-01-01
We present a method to incorporate dishonesty in online selling via a stochastic optimal control problem. In our framework, the seller wishes to maximize her average wealth level W at a fixed time T of her choosing. The corresponding Hamilton-Jacobi-Bellmann (HJB) equation is analyzed for a basic case. For more general models, the admissible control set is restricted to a jump process that switches between extreme values. We propose a new approach, where the optimal control problem is reduced to a multivariable optimization problem.
Bainbridge, Melissa; Kraft, Jana
2016-01-01
Transfer efficiencies of rumen-protected n-3 fatty acids (FA) to milk are low, thus we hypothesized that rumen-protection technologies allow for biohydrogenation and excretion of n-3 FA. The objectives of this study were to i) investigate the ruminal protection and post-ruminal release of the FA derived from the lipid-encapsulated echium oil (EEO), and ii) assess the bioavailability and metabolism of the EEO-derived FA through measuring the FA content in plasma lipid fractions, feces, and milk. The EEO was tested for rumen stability using the in situ nylon bag technique, then the apparent total-tract digestibility was assessed in vivo using six Holstein dairy cattle. Diets consisted of a control (no EEO); 1.5% of dry matter (DM) as EEO and 1.5% DM as encapsulation matrix; and 3% DM as EEO. The EEO was rumen-stable and had no effect on animal production. EEO-derived FA were incorporated into all plasma lipid fractions, with the highest proportion of n-3 FA observed in cholesterol esters. Fecal excretion of EEO-derived FA ranged from 7–14%. Biohydrogenation products increased in milk, plasma, and feces with EEO supplementation. In conclusion, lipid-encapsulation provides inadequate digestibility to achieve an optimal transfer efficiency of n-3 FA to milk. PMID:27741299
Optimal actuator location of minimum norm controls for heat equation with general controlled domain
NASA Astrophysics Data System (ADS)
Guo, Bao-Zhu; Xu, Yashan; Yang, Dong-Hui
2016-09-01
In this paper, we study optimal actuator location of the minimum norm controls for a multi-dimensional heat equation with control defined in the space L2 (Ω × (0 , T)). The actuator domain is time-varying in the sense that it is only required to have a prescribed Lebesgue measure for any moment. We select an optimal actuator location so that the optimal control takes its minimal norm over all possible actuator domains. We build a framework of finding the Nash equilibrium so that we can develop a sufficient and necessary condition to characterize the optimal relaxed solutions for both actuator location and corresponding optimal control of the open-loop system. The existence and uniqueness of the optimal classical solutions are therefore concluded. As a result, we synthesize both optimal actuator location and corresponding optimal control into a time-varying feedbacks.
Dynamics and linear quadratic optimal control of flexible multibody systems
NASA Astrophysics Data System (ADS)
Tung, Chin-Wei
1994-12-01
An efficient algorithm for the modeling, dynamic analysis, and optimal control of flexible multibody systems (FMBS) is presented. The cantilevered Bernoulli-Euler beam model and the assumed mode method are used to represent flexibility of elastic bodies in 3D vibration problems. Centrifugal stiffening effects are introduced to correctly represent the dynamic response. The governing equations of motion are based on Kane's equations, adopting a recursive formulation and strategic positioning of the generalized coordinates. The linear quadratic optimization scheme is employed to formulate the vibration control problem. The solutions to the Riccati equation and the use of Kalman gain as optimal control feedbacks to the control of flexibility are also introduced. Based on the optimal control theory and the property of the built-in redundancy for flexible multibody systems, the performance index measure in the optimization control of such systems can be classified into two manifolds: (1) using the extra degrees of freedom resulting from redundancy as control inputs and choosing an integral-type performance index which results in a global optimization scheme and (2) using the joint forces and torques as control inputs and allowing the system output state to keep close track to a reference state while the performance index is kept minimum. Several numerical examples are presented to demonstrate the effectiveness of the methodologies developed.
Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control
NASA Technical Reports Server (NTRS)
Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.
2015-01-01
The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.
Optimal Control of the Parametric Oscillator
ERIC Educational Resources Information Center
Andresen, B.; Hoffmann, K. H.; Nulton, J.; Tsirlin, A.; Salamon, P.
2011-01-01
We present a solution to the minimum time control problem for a classical harmonic oscillator to reach a target energy E[subscript T] from a given initial state (q[subscript i], p[subscript i]) by controlling its frequency [omega], [omega][subscript min] less than or equal to [omega] less than or equal to [omega][subscript max]. A brief synopsis…
Understanding Product Optimization: Kinetic versus Thermodynamic Control.
ERIC Educational Resources Information Center
Lin, King-Chuen
1988-01-01
Discusses the concept of kinetic versus thermodynamic control of reactions. Explains on the undergraduate level (1) the role of kinetic and thermodynamic control in kinetic equations, (2) the influence of concentration and temperature upon the reaction, and (3) the application of factors one and two to synthetic chemistry. (MVL)
Optimized synthesis of concurrently checked controllers
Leveugle, R.; Saucier, G. )
1990-04-01
Dedicated controllers (or FSM's) with concurrent checking capabilities are of prime importance in highly dependable applications. This paper presents a new method for introducing on-line test facilities in a controller with a very low overhead. This on-line test consists in detecting illegal paths in the control flow graph. These illegal paths may be due either to permanent faults or to transient errors. The state code flow is compacted through polynomial division. An implicit justifying signature method is applied at the state code level and ensures identical signatures before each join node of the control flow graph. The signatures are then independent of the path followed previously in the graph and the comparison to reference data is greatly facilitated. This property is obtained by a clever state assignment, nearly without area overhead. The controllers can then be checked by signature analysis, either by a built-in monitor or by an external checker.
OPTIMIZATION OF INTEGRATED URBAN WET-WEATHER CONTROL STRATEGIES
An optimization method for urban wet weather control (WWC) strategies is presented. The developed optimization model can be used to determine the most cost-effective strategies for the combination of centralized storage-release systems and distributed on-site WWC alternatives. T...
Optimal guidance law for cooperative attack of multiple missiles based on optimal control theory
NASA Astrophysics Data System (ADS)
Sun, Xiao; Xia, Yuanqing
2012-08-01
This article considers the problem of optimal guidance laws for cooperative attack of multiple missiles based on the optimal control theory. New guidance laws are presented such that multiple missiles attack a single target simultaneously. Simulation results show the effectiveness of the proposed algorithms.
Optimal control studies of solar heating systems
Winn, C B
1980-01-01
In the past few years fuel prices have seen steady increases. Also, the supply of fuel has been on the decline. Because of these two problems there has been an increase in the number of solar heated buildings. Since conventional fuel prices are increasing and as a solar heating system represents a high capital cost it is desirable to obtain the maximum performance from a solar heating system. The control scheme that is used in a solar heated building has an effect on the performance of the solar system. The best control scheme possible would, of course, be desired. This report deals with the control problems of a solar heated building. The first of these problems is to control the inside temperature of the building and to minimize the fuel consumption. This problem applies to both solar and conventionally heated buildings. The second problem considered is to control the collector fluid flow to maximize the difference between the useful energy collected and the energy required to pump the fluid. The third problem is to control the enclosure temperature of a building which has two sources of heat, one solar and the other conventional.
Optimal False Discovery Rate Control for Dependent Data.
Xie, Jichun; Cai, T Tony; Maris, John; Li, Hongzhe
2011-01-01
This paper considers the problem of optimal false discovery rate control when the test statistics are dependent. An optimal joint oracle procedure, which minimizes the false non-discovery rate subject to a constraint on the false discovery rate is developed. A data-driven marginal plug-in procedure is then proposed to approximate the optimal joint procedure for multivariate normal data. It is shown that the marginal procedure is asymptotically optimal for multivariate normal data with a short-range dependent covariance structure. Numerical results show that the marginal procedure controls false discovery rate and leads to a smaller false non-discovery rate than several commonly used p-value based false discovery rate controlling methods. The procedure is illustrated by an application to a genome-wide association study of neuroblastoma and it identifies a few more genetic variants that are potentially associated with neuroblastoma than several p-value-based false discovery rate controlling procedures.
Optimal Aircraft Control Upset Recovery With and Without Component Failures
NASA Technical Reports Server (NTRS)
Sparks, Dean W.; Moerder, Daniel D.
2002-01-01
This paper treats the problem of recovering sustainable nondescending (safe) flight in a transport aircraft after one or more of its control effectors fail. Such recovery can be a challenging goal for many transport aircraft currently in the operational fleet for two reasons. First, they have very little redundancy in their means of generating control forces and moments. These aircraft have, as primary control surfaces, a single rudder and pairwise elevators and aileron/spoiler units that provide yaw, pitch, and roll moments with sufficient bandwidth to be used in stabilizing and maneuvering the airframe. Beyond this, throttling the engines can provide additional moments, but on a much slower time scale. Other aerodynamic surfaces, such as leading and trailing edge flaps, are only intended to be placed in a position and left, and are, hence, very slow-moving. Because of this, loss of a primary control surface strongly degrades the controllability of the vehicle, particularly when the failed effector becomes stuck in a non-neutral position where it exerts a disturbance moment that must be countered by the remaining operating effectors. The second challenge in recovering safe flight is that these vehicles are not agile, nor can they tolerate large accelerations. This is of special importance when, at the outset of the recovery maneuver, the aircraft is flying toward the ground, as is frequently the case when there are major control hardware failures. Recovery of safe flight is examined in this paper in the context of trajectory optimization. For a particular transport aircraft, and a failure scenario inspired by an historical air disaster, recovery scenarios are calculated with and without control surface failures, to bring the aircraft to safe flight from the adverse flight condition that it had assumed, apparently as a result of contact with a vortex from a larger aircraft's wake. An effort has been made to represent relevant airframe dynamics, acceleration limits
Using Chemicals to Optimize Conformance Control in Fractured Reservoirs
Seright, Randall S.; Liang, Jenn-Tai; Schrader, Richard; Hagstrom II, John; Wang, Ying; Kumar, Ananad; Wavrik, Kathryn
2001-10-29
This report describes work performed during the third and final year of the project, Using Chemicals to Optimize Conformance Control in Fractured Reservoirs. This research project had three objectives. The first objective was to develop a capability to predict and optimize the ability of gels to reduce permeability to water more than that to oil or gas. The second objective was to develop procedures for optimizing blocking agent placement in wells where hydraulic fractures cause channeling problems. The third objective was to develop procedures to optimize blocking agent placement in naturally fractured reservoirs.
Cost-effectiveness analysis of optimal control measures for tuberculosis.
Rodrigues, Paula; Silva, Cristiana J; Torres, Delfim F M
2014-10-01
We propose and analyze an optimal control problem where the control system is a mathematical model for tuberculosis that considers reinfection. The control functions represent the fraction of early latent and persistent latent individuals that are treated. Our aim was to study how these control measures should be implemented, for a certain time period, in order to reduce the number of active infected individuals, while minimizing the interventions implementation costs. The optimal intervention is compared along different epidemiological scenarios, by varying the transmission coefficient. The impact of variation of the risk of reinfection, as a result of acquired immunity to a previous infection for treated individuals on the optimal controls and associated solutions, is analyzed. A cost-effectiveness analysis is done, to compare the application of each one of the control measures, separately or in combination.
Can price controls induce optimal physician behavior?
Wedig, G; Mitchell, J B; Cromwell, J
1989-01-01
Recently, budget-conscious policymakers have shifted their attention to the physician services market and have begun to consider a wide variety of price regulatory schemes for moderating expenditures in this market. In a recent article in this journal, Feldman and Sloan warned that price controls on physician services may cause undesirable declines in service quality, independent of their budgetary ramifications. Our aim in this article is to reconsider the effects of price controls in the broader context of insurance coverage and moral hazard. Our ultimate goal is to assess the benefits of price controls independent of specific assumptions about the controversial issues of demand inducement and income targeting. Using a simple extension of the Feldman/Sloan model, we find that price controls can be and almost certainly are welfare-improving as long as consumers are sufficiently well insured, regardless of where one stands on the inducement issue. The salutary effects of price controls, on the other hand, can be compromised by income-targeting behavior on the part of physicians. We also introduce evidence from Medicare's recent fee freeze to evaluate the possibility of income-targeting behavior empirically. While formal studies of income targeting suggest that its magnitude is small in cross-section, we warn that its effects may be larger over time; this is what our descriptive evidence suggests. We conclude that more dramatic short-term progress on physician fee inflation will require stronger measures, such as putting physicians at risk for consumer expenditures.
Preconception optimization of glycaemic control in diabetes.
Islam, Najmul
2016-09-01
The prevalence of Diabetes Mellitus is increasing worldwide. In developing countries 25% of adult females with diabetes are in the reproductive age. Thus in developing countries increased number of pregnancies are complicated by diabetes. Uncontrolled diabetes in pregnancy is associated with increased risk for both mother and foetus. These risks can be minimized by good control of diabetes before and during pregnancy. Management in the preconception period is discussed in this review article. Detailed management involves general advice of lifestyle modification followed by specific details of screening for complications of diabetes. Changes in the drugs for both glycaemic control and other co-morbid conditions are discussed. The recommended insulin regimen in the preconception period and monitoring of glycaemic control by self-monitoring of blood glucose (SMBG) and HbA1C has also been highlighted.
Preconception optimization of glycaemic control in diabetes.
Islam, Najmul
2016-09-01
The prevalence of Diabetes Mellitus is increasing worldwide. In developing countries 25% of adult females with diabetes are in the reproductive age. Thus in developing countries increased number of pregnancies are complicated by diabetes. Uncontrolled diabetes in pregnancy is associated with increased risk for both mother and foetus. These risks can be minimized by good control of diabetes before and during pregnancy. Management in the preconception period is discussed in this review article. Detailed management involves general advice of lifestyle modification followed by specific details of screening for complications of diabetes. Changes in the drugs for both glycaemic control and other co-morbid conditions are discussed. The recommended insulin regimen in the preconception period and monitoring of glycaemic control by self-monitoring of blood glucose (SMBG) and HbA1C has also been highlighted. PMID:27582143
Multiobjective optimization design of a fractional order PID controller for a gun control system.
Gao, Qiang; Chen, Jilin; Wang, Li; Xu, Shiqing; Hou, Yuanlong
2013-01-01
Motion control of gun barrels is an ongoing topic for the development of gun control equipments possessing excellent performances. In this paper, a typical fractional order PID control strategy is employed for the gun control system. To obtain optimal parameters of the controller, a multiobjective optimization scheme is developed from the loop-shaping perspective. To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. To enhance the robustness of the algorithm for different problems, an adapting scheme of the mutation operation is further employed. With assistance of the evolutionary algorithm, the optimal solution for the specified problem is selected. The numerical simulation results show that the control system can rapidly follow the demand signal with high accuracy and high robustness, demonstrating the efficiency of the proposed controller parameter tuning method.
Multidimensional optimal droop control for wind resources in DC microgrids
NASA Astrophysics Data System (ADS)
Bunker, Kaitlyn J.
Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.
On The Structure Of The Time-Optimal Control Of Robot Arms
NASA Astrophysics Data System (ADS)
Chen, Yaobin; Desrochers, Alan A.
1988-02-01
The time-optimal control problem with hard control bounds has long been of interest to control engineers and researchers. For linear systems, under suitable conditions, such as normality and controllability, the time-optimal control can be shown to be of the bang-bang type. Much of the theoretical study of this problem has been limited to linear systems. In this paper the problem of determining the structure of the minimum-time control for robotic manipulators is addressed. We derive an alternate dynamic model for a robot arm using state variables based on the Hamiltonian Canonical equations. We then show that the structure of the minimum time control law requires that at least one of the actuators is always in saturation while the others adjust their torques so that some constraints on the motion are not violated while enabling the manipulator to achieve its
Proper Orthogonal Decomposition in Optimal Control of Fluids
NASA Technical Reports Server (NTRS)
Ravindran, S. S.
1999-01-01
In this article, we present a reduced order modeling approach suitable for active control of fluid dynamical systems based on proper orthogonal decomposition (POD). The rationale behind the reduced order modeling is that numerical simulation of Navier-Stokes equations is still too costly for the purpose of optimization and control of unsteady flows. We examine the possibility of obtaining reduced order models that reduce computational complexity associated with the Navier-Stokes equations while capturing the essential dynamics by using the POD. The POD allows extraction of certain optimal set of basis functions, perhaps few, from a computational or experimental data-base through an eigenvalue analysis. The solution is then obtained as a linear combination of these optimal set of basis functions by means of Galerkin projection. This makes it attractive for optimal control and estimation of systems governed by partial differential equations. We here use it in active control of fluid flows governed by the Navier-Stokes equations. We show that the resulting reduced order model can be very efficient for the computations of optimization and control problems in unsteady flows. Finally, implementational issues and numerical experiments are presented for simulations and optimal control of fluid flow through channels.
Controlling subcellular delivery to optimize therapeutic effect
Mossalam, Mohanad; Dixon, Andrew S; Lim, Carol S
2010-01-01
This article focuses on drug targeting to specific cellular organelles for therapeutic purposes. Drugs can be delivered to all major organelles of the cell (cytosol, endosome/lysosome, nucleus, nucleolus, mitochondria, endoplasmic reticulum, Golgi apparatus, peroxisomes and proteasomes) where they exert specific effects in those particular subcellular compartments. Delivery can be achieved by chemical (e.g., polymeric) or biological (e.g., signal sequences) means. Unidirectional targeting to individual organelles has proven to be immensely successful for drug therapy. Newer technologies that accommodate multiple signals (e.g., protein switch and virus-like delivery systems) mimic nature and allow for a more sophisticated approach to drug delivery. Harnessing different methods of targeting multiple organelles in a cell will lead to better drug delivery and improvements in disease therapy. PMID:21113240
Optimal control of hopper unloading on collection conveyor
Bernshtein, A.I.
1987-11-01
This article describes a computer simulation and control approach for optimizing the configuration of a hopper-belt conveyor system for the excavation of coal from underground mine workings. The purpose of the approach is to optimize the placement of hoppers along the conveyor route for maximum load capacity and optimal load distribution. The simulation is based on linear programming and has been implemented to control hopper loading and unloading in the Krasnoarmeiskaya mine No. 1 of the Krasnoarmeiskugol' Coal Production Association. Input criteria are given.
Fundamental Solutions and Optimal Control of Neutral Systems
NASA Astrophysics Data System (ADS)
Liu, Kai
In this work, we shall consider standard optimal control problems for a class of neutral functional differential equations in Banach spaces. As the basis of a systematic theory of neutral models, the fundamental solution is constructed and a variation of constants formula of mild solutions is established. Necessary conditions in terms of the solutions of neutral adjoint systems are established to deal with the fixed time integral convex cost problem of optimality. Based on optimality conditions, the maximum principle for time varying control domain is presented.
Development of Independence: Locus of Control, Achievement Motivation and Self vs. Adult Evaluation.
ERIC Educational Resources Information Center
Dickie, Jane R.; Mast, Vicki A.
The development and interrelationship of various measures of independence in children ages 3-12 are examined. Subjects were scored on measures of locus of control and achievement motivation and were rated by teachers on independence and achievement. Subjects were also scored on reliance on adult evaluation and self-evaluation. The results showed…
ERIC Educational Resources Information Center
Zhou, Fan; Leung, Kwok; Bond, Michael Harris
2009-01-01
The present research examined the relationships between two social axiom dimensions, reward for application and fate control, with various achievement-related indexes across a wide range of cultures. Results showed that there was no relationship between reward for application and academic achievement or economic competitiveness, but reward for…
A Model of Parental Achievement-Oriented Psychological Control in Academically Gifted Students
ERIC Educational Resources Information Center
Garn, Alex C.; Jolly, Jennifer L.
2015-01-01
This study investigated achievement-oriented parent socialization as it pertains to school avoidance in a sample of gifted students. A serial mediation model examining relationships among parental achievement-oriented psychological control (APC), fear of academic failure, academic amotivation, and school avoidance was tested. The sample included…
Backward bifurcation and optimal control of Plasmodium Knowlesi malaria
NASA Astrophysics Data System (ADS)
Abdullahi, Mohammed Baba; Hasan, Yahya Abu; Abdullah, Farah Aini
2014-07-01
A deterministic model for the transmission dynamics of Plasmodium Knowlesi malaria with direct transmission is developed. The model is analyzed using dynamical system techniques and it shows that the backward bifurcation occurs for some range of parameters. The model is extended to assess the impact of time dependent preventive (biological and chemical control) against the mosquitoes and vaccination for susceptible humans, while treatment for infected humans. The existence of optimal control is established analytically by the use of optimal control theory. Numerical simulations of the problem, suggest that applying the four control measure can effectively reduce if not eliminate the spread of Plasmodium Knowlesi in a community.
Reproducibility, Controllability, and Optimization of Lenr Experiments
NASA Astrophysics Data System (ADS)
Nagel, David J.
2006-02-01
Low-energy nuclear reaction (LENR) measurements are significantly and increasingly reproducible. Practical control of the production of energy or materials by LENR has yet to be demonstrated. Minimization of costly inputs and maximization of desired outputs of LENR remain for future developments.
Linear stochastic optimal control and estimation
NASA Technical Reports Server (NTRS)
Geyser, L. C.; Lehtinen, F. K. B.
1976-01-01
Digital program has been written to solve the LSOCE problem by using a time-domain formulation. LSOCE problem is defined as that of designing controls for linear time-invariant system which is disturbed by white noise in such a way as to minimize quadratic performance index.
Reengineering for optimized control of DC networks
NASA Astrophysics Data System (ADS)
Vintea, Adela; Schiopu, Paul
2015-02-01
The management of the Independent Power Grids is the global body/structure with flexible technological support for Command-Control-Communications and Informatized Management having the responsibility for providing the conditions and information (the informational flux of decision) for the decision-maker aiming at predictable and harmonic administration of the situations (crises) and for generating the harmonic situations (results).
Genetic Algorithm Optimizes Q-LAW Control Parameters
NASA Technical Reports Server (NTRS)
Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard
2008-01-01
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
Hydro- abrasive jet machining modeling for computer control and optimization
NASA Astrophysics Data System (ADS)
Groppetti, R.; Jovane, F.
1993-06-01
Use of hydro-abrasive jet machining (HAJM) for machining a wide variety of materials—metals, poly-mers, ceramics, fiber-reinforced composites, metal-matrix composites, and bonded or hybridized mate-rials—primarily for two- and three-dimensional cutting and also for drilling, turning, milling, and deburring, has been reported. However, the potential of this innovative process has not been explored fully. This article discusses process control, integration, and optimization of HAJM to establish a plat-form for the implementation of real-time adaptive control constraint (ACC), adaptive control optimiza-tion (ACO), and CAD/CAM integration. It presents the approach followed and the main results obtained during the development, implementation, automation, and integration of a HAJM cell and its computer-ized controller. After a critical analysis of the process variables and models reported in the literature to identify process variables and to define a process model suitable for HAJM real-time control and optimi-zation, to correlate process variables and parameters with machining results, and to avoid expensive and time-consuming experiments for determination of the optimal machining conditions, a process predic-tion and optimization model was identified and implemented. Then, the configuration of the HAJM cell, architecture, and multiprogramming operation of the controller in terms of monitoring, control, process result prediction, and process condition optimization were analyzed. This prediction and optimization model for selection of optimal machining conditions using multi-objective programming was analyzed. Based on the definition of an economy function and a productivity function, with suitable constraints relevant to required machining quality, required kerfing depth, and available resources, the model was applied to test cases based on experimental results.
Weis, Mirjam; Trommsdorff, Gisela; Muñoz, Lorena
2016-01-01
Self-regulation can be developed through parent-child interactions and has been related to developmental outcomes, e.g., such as educational achievement. This study examined cross-cultural differences and similarities in maternal restrictive control, self-regulation (i.e., behavior and emotion regulation) and school achievement and relations among these variables in Germany and Chile. Seventy-six German and 167 Chilean fourth graders, their mothers, and their teachers participated. Mothers and teachers rated children's behavior regulation with a subscale of the Strengths and Difficulties Questionnaire. Children reported their use of emotion regulation strategies on the Questionnaire for the Measurement of Stress and Coping. Mothers rated maternal restrictive control by answering the Parenting Practice Questionnaire. School achievement was assessed by grades for language and mathematics. Results showed higher behavior regulation of German children in comparison to Chilean children and a higher preference of restrictive parental control in Chilean mothers than in German mothers. Regression analyses revealed positive relations between children's behavior regulation and school achievement in Germany and in Chile. Further, in both cultural contexts, maternal restrictive control was related negatively to behavior regulation and positively to anger-oriented emotion regulation. In sum, the study showed the central function of behavior regulation for school achievement underlining negative relations of maternal restrictive control with children's self-regulation and school achievement in diverse cultural contexts. Culturally adapted interventions related to parenting practices to promote children's behavior regulation may assist in also promoting children's school achievement. PMID:27303318
Weis, Mirjam; Trommsdorff, Gisela; Muñoz, Lorena
2016-01-01
Self-regulation can be developed through parent-child interactions and has been related to developmental outcomes, e.g., such as educational achievement. This study examined cross-cultural differences and similarities in maternal restrictive control, self-regulation (i.e., behavior and emotion regulation) and school achievement and relations among these variables in Germany and Chile. Seventy-six German and 167 Chilean fourth graders, their mothers, and their teachers participated. Mothers and teachers rated children's behavior regulation with a subscale of the Strengths and Difficulties Questionnaire. Children reported their use of emotion regulation strategies on the Questionnaire for the Measurement of Stress and Coping. Mothers rated maternal restrictive control by answering the Parenting Practice Questionnaire. School achievement was assessed by grades for language and mathematics. Results showed higher behavior regulation of German children in comparison to Chilean children and a higher preference of restrictive parental control in Chilean mothers than in German mothers. Regression analyses revealed positive relations between children's behavior regulation and school achievement in Germany and in Chile. Further, in both cultural contexts, maternal restrictive control was related negatively to behavior regulation and positively to anger-oriented emotion regulation. In sum, the study showed the central function of behavior regulation for school achievement underlining negative relations of maternal restrictive control with children's self-regulation and school achievement in diverse cultural contexts. Culturally adapted interventions related to parenting practices to promote children's behavior regulation may assist in also promoting children's school achievement. PMID:27303318
Fairness: How to Achieve It and How to Optimize in a Fair-Division Procedure
ERIC Educational Resources Information Center
Jones, Michael A.; Cohen, Stanley F.
2004-01-01
A simple and practical application of mathematics is for fairly resolving the dispute of division of items for which two parties have equal claim. Basic properties of fair division are explained, which would enable students to learn concepts on optimization without introducing calculus.
Tian, Xiao-Jun; Zhang, Hang; Sannerud, Jens; Xing, Jianhua
2016-05-24
Multiple-objective optimization is common in biological systems. In the mammalian olfactory system, each sensory neuron stochastically expresses only one out of up to thousands of olfactory receptor (OR) gene alleles; at the organism level, the types of expressed ORs need to be maximized. Existing models focus only on monoallele activation, and cannot explain recent observations in mutants, especially the reduced global diversity of expressed ORs in G9a/GLP knockouts. In this work we integrated existing information on OR expression, and constructed a comprehensive model that has all its components based on physical interactions. Analyzing the model reveals an evolutionarily optimized three-layer regulation mechanism, which includes zonal segregation, epigenetic barrier crossing coupled to a negative feedback loop that mechanistically differs from previous theoretical proposals, and a previously unidentified enhancer competition step. This model not only recapitulates monoallelic OR expression, but also elucidates how the olfactory system maximizes and maintains the diversity of OR expression, and has multiple predictions validated by existing experimental results. Through making an analogy to a physical system with thermally activated barrier crossing and comparative reverse engineering analyses, the study reveals that the olfactory receptor selection system is optimally designed, and particularly underscores cooperativity and synergy as a general design principle for multiobjective optimization in biology.
ERIC Educational Resources Information Center
Burgess, Melissa L.
2010-01-01
In this mixed methods study the potential for developmental readers to experience optimal experience (flow) within the multi-user virtual environment, "Second Life," was examined. In an educational context, "Second Life" provided a space for constructivist learning, socialization, exploration, discovery and creativity. The communicative, social…
Tian, Xiao-Jun; Zhang, Hang; Sannerud, Jens; Xing, Jianhua
2016-05-24
Multiple-objective optimization is common in biological systems. In the mammalian olfactory system, each sensory neuron stochastically expresses only one out of up to thousands of olfactory receptor (OR) gene alleles; at the organism level, the types of expressed ORs need to be maximized. Existing models focus only on monoallele activation, and cannot explain recent observations in mutants, especially the reduced global diversity of expressed ORs in G9a/GLP knockouts. In this work we integrated existing information on OR expression, and constructed a comprehensive model that has all its components based on physical interactions. Analyzing the model reveals an evolutionarily optimized three-layer regulation mechanism, which includes zonal segregation, epigenetic barrier crossing coupled to a negative feedback loop that mechanistically differs from previous theoretical proposals, and a previously unidentified enhancer competition step. This model not only recapitulates monoallelic OR expression, but also elucidates how the olfactory system maximizes and maintains the diversity of OR expression, and has multiple predictions validated by existing experimental results. Through making an analogy to a physical system with thermally activated barrier crossing and comparative reverse engineering analyses, the study reveals that the olfactory receptor selection system is optimally designed, and particularly underscores cooperativity and synergy as a general design principle for multiobjective optimization in biology. PMID:27162367
On-line optimal control for fed-batch culture of baker's yeast production
Wu, W.T.; Chen, K.C.; Chiou, H.W.
1985-05-01
A method of on-line optimal control for fed-batch culture of bakers yeast production is proposed. The feed rate is taken as the control variable. The specific growth rate of the yeast is the output variable and is determined from the balance equation of oxygen. A moving model is obtained by using the data from the feed rate and the specific growth rate. Based on the moving model, an optimal feed rate for fed-batch culture is then achieved. 11 references.
Optimization of Composite Material System and Lay-up to Achieve Minimum Weight Pressure Vessel
NASA Astrophysics Data System (ADS)
Mian, Haris Hameed; Wang, Gang; Dar, Uzair Ahmed; Zhang, Weihong
2013-10-01
The use of composite pressure vessels particularly in the aerospace industry is escalating rapidly because of their superiority in directional strength and colossal weight advantage. The present work elucidates the procedure to optimize the lay-up for composite pressure vessel using finite element analysis and calculate the relative weight saving compared with the reference metallic pressure vessel. The determination of proper fiber orientation and laminate thickness is very important to decrease manufacturing difficulties and increase structural efficiency. In the present work different lay-up sequences for laminates including, cross-ply [ 0 m /90 n ] s , angle-ply [ ±θ] ns , [ 90/±θ] ns and [ 0/±θ] ns , are analyzed. The lay-up sequence, orientation and laminate thickness (number of layers) are optimized for three candidate composite materials S-glass/epoxy, Kevlar/epoxy and Carbon/epoxy. Finite element analysis of composite pressure vessel is performed by using commercial finite element code ANSYS and utilizing the capabilities of ANSYS Parametric Design Language and Design Optimization module to automate the process of optimization. For verification, a code is developed in MATLAB based on classical lamination theory; incorporating Tsai-Wu failure criterion for first-ply failure (FPF). The results of the MATLAB code shows its effectiveness in theoretical prediction of first-ply failure strengths of laminated composite pressure vessels and close agreement with the FEA results. The optimization results shows that for all the composite material systems considered, the angle-ply [ ±θ] ns is the optimum lay-up. For given fixed ply thickness the total thickness of laminate is obtained resulting in factor of safety slightly higher than two. Both Carbon/epoxy and Kevlar/Epoxy resulted in approximately same laminate thickness and considerable percentage of weight saving, but S-glass/epoxy resulted in weight increment.
Adaptive control based on retrospective cost optimization
NASA Technical Reports Server (NTRS)
Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)
2012-01-01
A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.
Optimizing wind turbine control system parameters
NASA Astrophysics Data System (ADS)
Schluter, Larry L.; Vachon, William A.
1993-05-01
The impending expiration of the levelized period in the Interim Standard Offer Number 4 (ISO4) utility contracts for purchasing wind-generated power in California mandates, more than ever, that windplants be operated in a cost-effective manner. Operating plans and approaches are needed that maximize the net revenue from wind parks--after accounting for operation and maintenance costs. This paper describes a design tool that makes it possible to tailor a control system of a wind turbine (WT) to maximize energy production while minimizing the financial consequences of fatigue damage to key structural components. Plans for code enhancements to include expert systems and fuzzy logic are discussed, and typical results are presented in which the code is applied to study the controls of a generic Danish 15-m horizontal axis wind turbine (HAWT).
Optimizing wind turbine control system parameters
Schluter, L.L.; Vachon, W.A.
1993-08-01
The impending expiration of the levelized period in the Interim Standard Offer Number 4 (ISO4) utility contracts for purchasing wind-generated power in California mandates, more than ever, that windplants be operated in a cost-effective manner. Operating plans and approaches are needed that maximize the net revenue from wind parks--after accounting for operation and maintenance costs. This paper describes a design tool that makes it possible to tailor a control system of a wind turbine (WT) to maximize energy production while minimizing the financial consequences of fatigue damage to key structural components. Plans for code enhancements to include expert systems and fuzzy logic are discussed, and typical results are presented in which the code is applied to study the controls of a generic Danish 15-m horizontal axis wind turbine (HAWT).
Optimally Controlled Flexible Fuel Powertrain System
Duncan Sheppard; Bruce Woodrow; Paul Kilmurray; Simon Thwaite
2011-06-30
A multi phase program was undertaken with the stated goal of using advanced design and development tools to create a unique combination of existing technologies to create a powertrain system specification that allowed minimal increase of volumetric fuel consumption when operating on E85 relative to gasoline. Although on an energy basis gasoline / ethanol blends typically return similar fuel economy to straight gasoline, because of its lower energy density (gasoline ~ 31.8MJ/l and ethanol ~ 21.1MJ/l) the volume based fuel economy of gasoline / ethanol blends are typically considerably worse. This project was able to define an initial engine specification envelope, develop specific hardware for the application, and test that hardware in both single and multi-cylinder test engines to verify the ability of the specified powertrain to deliver reduced E85 fuel consumption. Finally, the results from the engine testing were used in a vehicle drive cycle analysis tool to define a final vehicle level fuel economy result. During the course of the project, it was identified that the technologies utilized to improve fuel economy on E85 also enabled improved fuel economy when operating on gasoline. However, the E85 fueled powertrain provided improved vehicle performance when compared to the gasoline fueled powertrain due to the improved high load performance of the E85 fuel. Relative to the baseline comparator engine and considering current market fuels, the volumetric fuel consumption penalty when running on E85 with the fully optimized project powertrain specification was reduced significantly. This result shows that alternative fuels can be utilized in high percentages while maintaining or improving vehicle performance and with minimal or positive impact on total cost of ownership to the end consumer. The justification for this project was two-fold. In order to reduce the US dependence on crude oil, much of which is imported, the US Environmental Protection Agency (EPA
Optimal doping control of magnetic semiconductors via subsurfactant epitaxy
Zeng, Changgan; Zhang, Zhenyu; van Benthem, Klaus; Chisholm, Matthew F; Weitering, Harm H
2008-02-01
Dilute magnetic semiconductors (DMS) with high ferromagnetic ordering temperatures (T{sub c}) have vast potential for advancing spin-based electronics or 'spintronics'. To date, achieving high-T{sub c} DMS typically required doping levels of order 5%. Such high doping levels inevitably compromise the structural homogeneity and carrier mobility of the DMS. Here, we establish 'subsurfactant epitaxy' as a novel kinetic pathway for synthesizing Mn-doped germanium with T{sub c} much higher than room temperature, at dramatically reduced doping levels. This is accomplished by optimal control of the diffusion kinetics of the dopant atoms near the growth front in two separate deposition steps. The first involves a submonolayer dose of Mn on Ge(100) at low temperature, which populates subsurface interstitial sites with Mn while suppressing lateral Mn diffusion and clustering. The second step involves epitaxial growth of Ge at elevated temperature, taking advantage of the strong floating ability of the interstitial Mn dopants towards the newly defined subsurface sites at the growth front. Most remarkably, the Mn dopants trapped inside the film are uniformly distributed at substitutional sites, and the resulting film exhibits ferromagnetism above 400 K at the nominal doping level of only 0.2%.
Divisive gain modulation of motoneurons by inhibition optimizes muscular control.
Vestergaard, Mikkel; Berg, Rune W
2015-02-25
When using muscles, the precision with which force is delivered is as important as the delivery of force itself. Force is regulated by both the number of recruited motoneurons and their spike frequency. While it is known that the recruitment is ordered to reduce variability in force, it remains unclear whether the motoneuron gain, i.e., the slope of the transformation between synaptic input and spiking output, is also modulated to reduce variability in force. To address this issue, we use turtle hindlimb scratching as a model for fine motor control, since this behavior involves precise limb movement to rub the location of somatic nuisance touch. We recorded intracellularly from motoneurons in a reduced preparation where the limbs were removed to increase mechanical stability and the motor nerve activity served as a surrogate for muscle force. We found that not only is the gain of motoneurons regulated on a subsecond timescale, it is also adjusted to minimize variability. The modulation is likely achieved via an expansive nonlinearity between spike rate and membrane potential with inhibition having a divisive influence. These findings reveal a versatile mechanism of modulating neuronal sensitivity and suggest that such modulation is fundamentally linked to optimization.
Control optimization of the cryoplant warm compressor station for EAST
Zhuang, M.; Hu, L. B.; Zhou, Z. W.; Xia, G. H.
2014-01-29
The cryogenic control system for EAST (Experimental Advanced Superconducting Tokamak) was designed based on DeltaV DCS of Emerson Corporation. The automatic control of the cryoplant warm compressors has been implemented. However, with ever-degrading performance of critical equipment, the cryoplant operation in the partial design conditions makes the control system fluctuate and unstable. In this paper, the warm compressor control system was optimized to eliminate the pressure oscillation based on the expert PID theory.
Lyapunov optimal feedback control of a nonlinear inverted pendulum
NASA Technical Reports Server (NTRS)
Grantham, W. J.; Anderson, M. J.
1989-01-01
Liapunov optimal feedback control is applied to a nonlinear inverted pendulum in which the control torque was constrained to be less than the nonlinear gravity torque in the model. This necessitates a control algorithm which 'rocks' the pendulum out of its potential wells, in order to stabilize it at a unique vertical position. Simulation results indicate that a preliminary Liapunov feedback controller can successfully overcome the nonlinearity and bring almost all trajectories to the target.
An optimized buffer controlled data compression system
NASA Technical Reports Server (NTRS)
Dosik, P. H.; Schwartz, M.
1974-01-01
The digital data compression system considered uses a buffer controlled aperture algorithm which minimizes the mean-squared error between the reconstructed receiver output and transmitter input. The data compression technique selected is based on the zero-order floating aperture prediction rule. It is assumed that the statistics of the input data are initially uniformly distributed, stationary, and first-order Markov. The problem is solved for stationary data. An approach is presented for extending the results to slowly varying uniformly distributed nonstationary Markov data.
Solving Optimal Control Problems by Exploiting Inherent Dynamical Systems Structures
NASA Astrophysics Data System (ADS)
Flaßkamp, Kathrin; Ober-Blöbaum, Sina; Kobilarov, Marin
2012-08-01
Computing globally efficient solutions is a major challenge in optimal control of nonlinear dynamical systems. This work proposes a method combining local optimization and motion planning techniques based on exploiting inherent dynamical systems structures, such as symmetries and invariant manifolds. Prior to the optimal control, the dynamical system is analyzed for structural properties that can be used to compute pieces of trajectories that are stored in a motion planning library. In the context of mechanical systems, these motion planning candidates, termed primitives, are given by relative equilibria induced by symmetries and motions on stable or unstable manifolds of e.g. fixed points in the natural dynamics. The existence of controlled relative equilibria is studied through Lagrangian mechanics and symmetry reduction techniques. The proposed framework can be used to solve boundary value problems by performing a search in the space of sequences of motion primitives connected using optimized maneuvers. The optimal sequence can be used as an admissible initial guess for a post-optimization. The approach is illustrated by two numerical examples, the single and the double spherical pendula, which demonstrates its benefit compared to standard local optimization techniques.
Tao, Ye; Xu, Lijia; Zhang, Zhen; Chen, Runfeng; Li, Huanhuan; Xu, Hui; Zheng, Chao; Huang, Wei
2016-08-01
Current static-state explorations of organic semiconductors for optimal material properties and device performance are hindered by limited insights into the dynamically changed molecular states and charge transport and energy transfer processes upon device operation. Here, we propose a simple yet successful strategy, resonance variation-based dynamic adaptation (RVDA), to realize optimized self-adaptive properties in donor-resonance-acceptor molecules by engineering the resonance variation for dynamic tuning of organic semiconductors. Organic light-emitting diodes hosted by these RVDA materials exhibit remarkably high performance, with external quantum efficiencies up to 21.7% and favorable device stability. Our approach, which supports simultaneous realization of dynamically adapted and selectively enhanced properties via resonance engineering, illustrates a feasible design map for the preparation of smart organic semiconductors capable of dynamic structure and property modulations, promoting the studies of organic electronics from static to dynamic. PMID:27403886
Polynomial method for PLL controller optimization.
Wang, Ta-Chung; Lall, Sanjay; Chiou, Tsung-Yu
2011-01-01
The Phase-Locked Loop (PLL) is a key component of modern electronic communication and control systems. PLL is designed to extract signals from transmission channels. It plays an important role in systems where it is required to estimate the phase of a received signal, such as carrier tracking from global positioning system satellites. In order to robustly provide centimeter-level accuracy, it is crucial for the PLL to estimate the instantaneous phase of an incoming signal which is usually buried in random noise or some type of interference. This paper presents an approach that utilizes the recent development in the semi-definite programming and sum-of-squares field. A Lyapunov function will be searched as the certificate of the pull-in range of the PLL system. Moreover, a polynomial design procedure is proposed to further refine the controller parameters for system response away from the equilibrium point. Several simulation results as well as an experiment result are provided to show the effectiveness of this approach. PMID:22163973
Fu, Xingang; Li, Shuhui; Fairbank, Michael; Wunsch, Donald C; Alonso, Eduardo
2015-09-01
This paper investigates how to train a recurrent neural network (RNN) using the Levenberg-Marquardt (LM) algorithm as well as how to implement optimal control of a grid-connected converter (GCC) using an RNN. To successfully and efficiently train an RNN using the LM algorithm, a new forward accumulation through time (FATT) algorithm is proposed to calculate the Jacobian matrix required by the LM algorithm. This paper explores how to incorporate FATT into the LM algorithm. The results show that the combination of the LM and FATT algorithms trains RNNs better than the conventional backpropagation through time algorithm. This paper presents an analytical study on the optimal control of GCCs, including theoretically ideal optimal and suboptimal controllers. To overcome the inapplicability of the optimal GCC controller under practical conditions, a new RNN controller with an improved input structure is proposed to approximate the ideal optimal controller. The performance of an ideal optimal controller and a well-trained RNN controller was compared in close to real-life power converter switching environments, demonstrating that the proposed RNN controller can achieve close to ideal optimal control performance even under low sampling rate conditions. The excellent performance of the proposed RNN controller under challenging and distorted system conditions further indicates the feasibility of using an RNN to approximate optimal control in practical applications.
OPTIMIZATION OF DECENTRALIZED BMP CONTROLS IN URBAN AREAS
This paper will present an overview of a recently completed project for the US EPA entitled, Optimization of Urban Wet-weather Flow Control Systems. The focus of this effort is on techniques that are suitable for evaluating decentralized BMP controls. The four major components ...
OPTIMIZATION OF DECENTRALIZED BMP CONTROLS IN URBAN AREAS
This paper will present an overview of a recently completed project for the US EPA entitled Optimization of Urban Wet-weather Flow Control Systems. The focus of this effort is on techniques that are suitable for evaluating decentralized BMP controls. The four major components o...
Sensitivity Analysis and Optimal Control of Anthroponotic Cutaneous Leishmania
Zamir, Muhammad; Zaman, Gul; Alshomrani, Ali Saleh
2016-01-01
This paper is focused on the transmission dynamics and optimal control of Anthroponotic Cutaneous Leishmania. The threshold condition R0 for initial transmission of infection is obtained by next generation method. Biological sense of the threshold condition is investigated and discussed in detail. The sensitivity analysis of the reproduction number is presented and the most sensitive parameters are high lighted. On the basis of sensitivity analysis, some control strategies are introduced in the model. These strategies positively reduce the effect of the parameters with high sensitivity indices, on the initial transmission. Finally, an optimal control strategy is presented by taking into account the cost associated with control strategies. It is also shown that an optimal control exists for the proposed control problem. The goal of optimal control problem is to minimize, the cost associated with control strategies and the chances of infectious humans, exposed humans and vector population to become infected. Numerical simulations are carried out with the help of Runge-Kutta fourth order procedure. PMID:27505634
Semilinear Kolmogorov Equations and Applications to Stochastic Optimal Control
Masiero, Federica
2005-03-15
Semilinear parabolic differential equations are solved in a mild sense in an infinite-dimensional Hilbert space. Applications to stochastic optimal control problems are studied by solving the associated Hamilton-Jacobi-Bellman equation. These results are applied to some controlled stochastic partial differential equations.
Optimal Control of a Dengue Epidemic Model with Vaccination
NASA Astrophysics Data System (ADS)
Rodrigues, Helena Sofia; Teresa, M.; Monteiro, T.; Torres, Delfim F. M.
2011-09-01
We present a SIR+ASI epidemic model to describe the interaction between human and dengue fever mosquito populations. A control strategy in the form of vaccination, to decrease the number of infected individuals, is used. An optimal control approach is applied in order to find the best way to fight the disease.
Recursive multibody dynamics and discrete-time optimal control
NASA Technical Reports Server (NTRS)
Deleuterio, G. M. T.; Damaren, C. J.
1989-01-01
A recursive algorithm is developed for the solution of the simulation dynamics problem for a chain of rigid bodies. Arbitrary joint constraints are permitted, that is, joints may allow translational and/or rotational degrees of freedom. The recursive procedure is shown to be identical to that encountered in a discrete-time optimal control problem. For each relevant quantity in the multibody dynamics problem, there exists an analog in the context of optimal control. The performance index that is minimized in the control problem is identified as Gibbs' function for the chain of bodies.
Optimization of an Aeroservoelastic Wing with Distributed Multiple Control Surfaces
NASA Technical Reports Server (NTRS)
Stanford, Bret K.
2015-01-01
This paper considers the aeroelastic optimization of a subsonic transport wingbox under a variety of static and dynamic aeroelastic constraints. Three types of design variables are utilized: structural variables (skin thickness, stiffener details), the quasi-steady deflection scheduling of a series of control surfaces distributed along the trailing edge for maneuver load alleviation and trim attainment, and the design details of an LQR controller, which commands oscillatory hinge moments into those same control surfaces. Optimization problems are solved where a closed loop flutter constraint is forced to satisfy the required flight margin, and mass reduction benefits are realized by relaxing the open loop flutter requirements.
Optimal member damper controller design for large space structures
NASA Technical Reports Server (NTRS)
Joshi, S. M.; Groom, N. J.
1980-01-01
Consideration is given to the selection of velocity feedback gains for individual dampers for the members of a structurally controlled large flexible space structure. The problem is formulated as an optimal output feedback regulator problem, and necessary conditions are derived for minimizing a quadratic performance function. The diagonal nature of the gain matrix is taken into account, along with knowledge of noise covariances. It is pointed out that the method presented offers a systematic approach to the design of a class of controllers for enhancing structural damping, which have significant potential if used in conjunction with a reduced-order optimal controller for rigid-body modes and selected structural modes.
Solving the optimal attention allocation problem in manual control
NASA Technical Reports Server (NTRS)
Kleinman, D. L.
1976-01-01
Within the context of the optimal control model of human response, analytic expressions for the gradients of closed-loop performance metrics with respect to human operator attention allocation are derived. These derivatives serve as the basis for a gradient algorithm that determines the optimal attention that a human should allocate among several display indicators in a steady-state manual control task. Application of the human modeling techniques are made to study the hover control task for a CH-46 VTOL flight tested by NASA.
State-Constrained Optimal Control Problems of Impulsive Differential Equations
Forcadel, Nicolas; Rao Zhiping Zidani, Hasnaa
2013-08-01
The present paper studies an optimal control problem governed by measure driven differential systems and in presence of state constraints. The first result shows that using the graph completion of the measure, the optimal solutions can be obtained by solving a reparametrized control problem of absolutely continuous trajectories but with time-dependent state-constraints. The second result shows that it is possible to characterize the epigraph of the reparametrized value function by a Hamilton-Jacobi equation without assuming any controllability assumption.
Topology of classical molecular optimal control landscapes in phase space
NASA Astrophysics Data System (ADS)
Joe-Wong, Carlee; Ho, Tak-San; Long, Ruixing; Rabitz, Herschel; Wu, Rebing
2013-03-01
Optimal control of molecular dynamics is commonly expressed from a quantum mechanical perspective. However, in most contexts the preponderance of molecular dynamics studies utilize classical mechanical models. This paper treats laser-driven optimal control of molecular dynamics in a classical framework. We consider the objective of steering a molecular system from an initial point in phase space to a target point, subject to the dynamic constraint of Hamilton's equations. The classical control landscape corresponding to this objective is a functional of the control field, and the topology of the landscape is analyzed through its gradient and Hessian with respect to the control. Under specific assumptions on the regularity of the control fields, the classical control landscape is found to be free of traps that could hinder reaching the objective. The Hessian associated with an optimal control field is shown to have finite rank, indicating the presence of an inherent degree of robustness to control noise. Extensive numerical simulations are performed to illustrate the theoretical principles on (a) a model diatomic molecule, (b) two coupled Morse oscillators, and (c) a chaotic system with a coupled quartic oscillator, confirming the absence of traps in the classical control landscape. We compare the classical formulation with the mathematically analogous quantum state-to-state transition probability control landscape.
Topology of classical molecular optimal control landscapes in phase space.
Joe-Wong, Carlee; Ho, Tak-San; Long, Ruixing; Rabitz, Herschel; Wu, Rebing
2013-03-28
Optimal control of molecular dynamics is commonly expressed from a quantum mechanical perspective. However, in most contexts the preponderance of molecular dynamics studies utilize classical mechanical models. This paper treats laser-driven optimal control of molecular dynamics in a classical framework. We consider the objective of steering a molecular system from an initial point in phase space to a target point, subject to the dynamic constraint of Hamilton's equations. The classical control landscape corresponding to this objective is a functional of the control field, and the topology of the landscape is analyzed through its gradient and Hessian with respect to the control. Under specific assumptions on the regularity of the control fields, the classical control landscape is found to be free of traps that could hinder reaching the objective. The Hessian associated with an optimal control field is shown to have finite rank, indicating the presence of an inherent degree of robustness to control noise. Extensive numerical simulations are performed to illustrate the theoretical principles on (a) a model diatomic molecule, (b) two coupled Morse oscillators, and (c) a chaotic system with a coupled quartic oscillator, confirming the absence of traps in the classical control landscape. We compare the classical formulation with the mathematically analogous quantum state-to-state transition probability control landscape.
Optimal control methods for rapidly time-varying Hamiltonians
Motzoi, F.; Merkel, S. T.; Wilhelm, F. K.; Gambetta, J. M.
2011-08-15
In this article, we develop a numerical method to find optimal control pulses that accounts for the separation of timescales between the variation of the input control fields and the applied Hamiltonian. In traditional numerical optimization methods, these timescales are treated as being the same. While this approximation has had much success, in applications where the input controls are filtered substantially or mixed with a fast carrier, the resulting optimized pulses have little relation to the applied physical fields. Our technique remains numerically efficient in that the dimension of our search space is only dependent on the variation of the input control fields, while our simulation of the quantum evolution is accurate on the timescale of the fast variation in the applied Hamiltonian.
Kim, Dong-Hun; Lim, Kyung-Geun; Park, Jong Hyeok; Lee, Tae-Woo
2012-10-01
Hole extraction in organic photovoltaic cells (OPVs) can be modulated by a surface-enriched layer formed on top of the conducting polymer-based hole extraction layer (HEL). This tunes the surface work function of the HEL to better align with the ionization potential of the polymeric photoactive layer. Results show noticeable improvement in device power conversion efficiencies (PCEs) in OPVs. We achieved a 6.1 % PCE from the OPV by optimizing the surface-enriched layer.
Control optimization, stabilization and computer algorithms for aircraft applications
NASA Technical Reports Server (NTRS)
Athans, M. (Editor); Willsky, A. S. (Editor)
1982-01-01
The analysis and design of complex multivariable reliable control systems are considered. High performance and fault tolerant aircraft systems are the objectives. A preliminary feasibility study of the design of a lateral control system for a VTOL aircraft that is to land on a DD963 class destroyer under high sea state conditions is provided. Progress in the following areas is summarized: (1) VTOL control system design studies; (2) robust multivariable control system synthesis; (3) adaptive control systems; (4) failure detection algorithms; and (5) fault tolerant optimal control theory.
Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong
2015-04-01
Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness.
Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong
2015-04-01
Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness. PMID:25794375
Optimal control of coupled PDE networks with automated code generation
NASA Astrophysics Data System (ADS)
Papadopoulos, D.
2012-09-01
The purpose of this work is to present a framework for the optimal control of coupled PDE networks. A coupled PDE network is a system of partial differential equations coupled together. Such systems can be represented as a directed graph. A domain specific language (DSL)—an extension of the DOT language—is used for the description of such a coupled PDE network. The adjoint equations and the gradient, required for its optimal control, are computed with the help of a computer algebra system (CAS). Automated code generation techniques have been used for the generation of the PDE systems of both the direct and the adjoint equations. Both the direct and adjoint equations are solved with the standard finite element method. Finally, for the numerical optimization of the system standard optimization techniques are used such as BFGS and Newton conjugate gradient.
Thermodynamic framework for discrete optimal control in multiphase flow systems
NASA Astrophysics Data System (ADS)
Sieniutycz, Stanislaw
1999-08-01
Bellman's method of dynamic programming is used to synthesize diverse optimization approaches to active (work producing) and inactive (entropy generating) multiphase flow systems. Thermal machines, optimally controlled unit operations, nonlinear heat conduction, spontaneous relaxation processes, and self-propagating wave fronts are all shown to satisfy a discrete Hamilton-Jacobi-Bellman equation and a corresponding discrete optimization algorithm of Pontryagin's type, with the maximum principle for a Hamiltonian. The extremal structures are always canonical. A common unifying criterion is set for all considered systems, which is the criterion of a minimum generated entropy. It is shown that constraints can modify the entropy functionals in a different way for each group of the processes considered; thus the resulting structures of these functionals may differ significantly. Practical conclusions are formulated regarding the energy savings and energy policy in optimally controlled systems.
On the Relation of Locus of Control and L2 Reading and Writing Achievement
ERIC Educational Resources Information Center
Ghonsooly, Behzad; Shirvan, Majid Elahi
2011-01-01
Locus of control, a psychological construct, has been the focus of attention in recent decades. Psychologists have discussed the effect of locus of control on achieving life goals in social/psychological interactions. While learning a foreign language involves both social interactions and psychological processes, the role and relation of locus of…
Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2012-01-01
This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.
NASA Astrophysics Data System (ADS)
Mangold, Claudia; Neogi, Sanghamitra; Donadio, Davide
2016-08-01
Silicon nanostructures with reduced dimensionality, such as nanowires, membranes, and thin films, are promising thermoelectric materials, as they exhibit considerably reduced thermal conductivity. Here, we utilize density functional theory and Boltzmann transport equation to compute the electronic properties of ultra-thin crystalline silicon membranes with thickness between 1 and 12 nm. We predict that an optimal thickness of ˜7 nm maximizes the thermoelectric figure of merit of membranes with native oxide surface layers. Further thinning of the membranes, although attainable in experiments, reduces the electrical conductivity and worsens the thermoelectric efficiency.
Optimized Reactive Power Compensation Using Fuzzy Logic Controller
NASA Astrophysics Data System (ADS)
George, S.; Mini, K. N.; Supriya, K.
2015-03-01
Reactive power flow in a long transmission line plays a vital role in power transfer capability and voltage stability in power system. Traditionally, shunt connected compensators are used to control reactive power in long transmission line. Thyristor controlled reactor is used to control reactive power under lightly loaded condition. By controlling firing angle of thyristor, it is possible to control reactive power in the transmission lines. However, thyristor controlled reactor will inject harmonic current into the system. An attempt to reduce reactive power injection will increase harmonic distortion in the line current and vice versa. Thus, there is a trade-off between reactive power injection and harmonics in current. By optimally controlling the reactive power injection, harmonics in current can be brought within the specified limit. In this paper, a Fuzzy Logic Controller is implemented to obtain optimal control of reactive power of the compensator to maintain voltage and harmonic in current within the limits. An algorithm which optimizes the firing angle in each fuzzy subset by calculating the rank of feasible firing angles is proposed for the construction of rules in Fuzzy Logic Controller. The novelty of the algorithm is that it uses a simple error formula for the calculation of the rank of the feasible firing angles in each fuzzy subset.
Optimal Robust Motion Controller Design Using Multiobjective Genetic Algorithm
Svečko, Rajko
2014-01-01
This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm—differential evolution. PMID:24987749
Optimal robust motion controller design using multiobjective genetic algorithm.
Sarjaš, Andrej; Svečko, Rajko; Chowdhury, Amor
2014-01-01
This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm-differential evolution. PMID:24987749
Efficient algorithms for the laboratory discovery of optimal quantum controls
NASA Astrophysics Data System (ADS)
Turinici, Gabriel; Le Bris, Claude; Rabitz, Herschel
2004-07-01
The laboratory closed-loop optimal control of quantum phenomena, expressed as minimizing a suitable cost functional, is currently implemented through an optimization algorithm coupled to the experimental apparatus. In practice, the most commonly used search algorithms are variants of genetic algorithms. As an alternative choice, a direct search deterministic algorithm is proposed in this paper. For the simple simulations studied here, it outperforms the existing approaches. An additional algorithm is introduced in order to reveal some properties of the cost functional landscape.
Solving bi-objective optimal control problems with rectangular framing
NASA Astrophysics Data System (ADS)
Wijaya, Karunia Putra; Götz, Thomas
2016-06-01
Optimization problems, e.g. arising from epidemiology models, often ask for solutions minimizing multi-criteria objective functions. In this paper we discuss a novel approach for solving bi-objective optimal control problems. The set of non-dominated points is constructed via a decreasing sequence of rectangles. Particular attention is paid to a problem with disconnected set of non-dominated points. Several examples from epidemiology are investigated and show the applicability of the method.
Optimizing laser pulses to control photoinduced states of matter
NASA Astrophysics Data System (ADS)
Hwang, Bin; Duxbury, P. M.
2016-10-01
We present a computational approach to optimal laser pulse shaping directed at accessing novel photoinduced states of matter. Results are illustrated for a simple charge-density wave (CDW) model where the targeted effect is CDW melting and negative temperature states. Optimal control is implemented using the Krotov method applied to nonequilibrium tight-binding Hamiltonians where the laser pulse is introduced using the Peierls substitution, and we demonstrate monotonic convergence for this class of problem.
Optimal periodic control for spacecraft pointing and attitude determination
NASA Technical Reports Server (NTRS)
Pittelkau, Mark E.
1993-01-01
A new approach to autonomous magnetic roll/yaw control of polar-orbiting, nadir-pointing momentum bias spacecraft is considered as the baseline attitude control system for the next Tiros series. It is shown that the roll/yaw dynamics with magnetic control are periodically time varying. An optimal periodic control law is then developed. The control design features a state estimator that estimates attitude, attitude rate, and environmental torque disturbances from Earth sensor and sun sensor measurements; no gyros are needed. The state estimator doubles as a dynamic attitude determination and prediction function. In addition to improved performance, the optimal controller allows a much smaller momentum bias than would otherwise be necessary. Simulation results are given.
Optimal Variable-Structure Control Tracking of Spacecraft Maneuvers
NASA Technical Reports Server (NTRS)
Crassidis, John L.; Vadali, Srinivas R.; Markley, F. Landis
1999-01-01
An optimal control approach using variable-structure (sliding-mode) tracking for large angle spacecraft maneuvers is presented. The approach expands upon a previously derived regulation result using a quaternion parameterization for the kinematic equations of motion. This parameterization is used since it is free of singularities. The main contribution of this paper is the utilization of a simple term in the control law that produces a maneuver to the reference attitude trajectory in the shortest distance. Also, a multiplicative error quaternion between the desired and actual attitude is used to derive the control law. Sliding-mode switching surfaces are derived using an optimal-control analysis. Control laws are given using either external torque commands or reaction wheel commands. Global asymptotic stability is shown for both cases using a Lyapunov analysis. Simulation results are shown which use the new control strategy to stabilize the motion of the Microwave Anisotropy Probe spacecraft.
Optimization in Hardy space and the problem of controller optimization (Review)
NASA Astrophysics Data System (ADS)
Larin, V. B.
1992-02-01
Problems related to optimization in Hardy space H2 are examined with particular reference to approaches based on the Wiener-Kolmogorov and Wiener-Hopf methods. The existing parametrization procedures for sets of stabilizing controllers are compared. The use of the LQG approach and H2 optimization in applied problems is discussed using specific examples. Consideration is also given to the solution of the Riccati algebraic equation and factorization of matrix polynomials.
NASA Technical Reports Server (NTRS)
Postma, Barry Dirk
2005-01-01
This thesis discusses application of a robust constrained optimization approach to control design to develop an Auto Balancing Controller (ABC) for a centrifuge rotor to be implemented on the International Space Station. The design goal is to minimize a performance objective of the system, while guaranteeing stability and proper performance for a range of uncertain plants. The Performance objective is to minimize the translational response of the centrifuge rotor due to a fixed worst-case rotor imbalance. The robustness constraints are posed with respect to parametric uncertainty in the plant. The proposed approach to control design allows for both of these objectives to be handled within the framework of constrained optimization. The resulting controller achieves acceptable performance and robustness characteristics.
A Higher Harmonic Optimal Controller to Optimise Rotorcraft Aeromechanical Behaviour
NASA Technical Reports Server (NTRS)
Leyland, Jane Anne
1996-01-01
Three methods to optimize rotorcraft aeromechanical behavior for those cases where the rotorcraft plant can be adequately represented by a linear model system matrix were identified and implemented in a stand-alone code. These methods determine the optimal control vector which minimizes the vibration metric subject to constraints at discrete time points, and differ from the commonly used non-optimal constraint penalty methods such as those employed by conventional controllers in that the constraints are handled as actual constraints to an optimization problem rather than as just additional terms in the performance index. The first method is to use a Non-linear Programming algorithm to solve the problem directly. The second method is to solve the full set of non-linear equations which define the necessary conditions for optimality. The third method is to solve each of the possible reduced sets of equations defining the necessary conditions for optimality when the constraints are pre-selected to be either active or inactive, and then to simply select the best solution. The effects of maneuvers and aeroelasticity on the systems matrix are modelled by using a pseudo-random pseudo-row-dependency scheme to define the systems matrix. Cases run to date indicate that the first method of solution is reliable, robust, and easiest to use, and that it was superior to the conventional controllers which were considered.
Advanced launch system trajectory optimization using suboptimal control
NASA Technical Reports Server (NTRS)
Shaver, Douglas A.; Hull, David G.
1993-01-01
The maximum-final mass trajectory of a proposed configuration of the Advanced Launch System is presented. A model for the two-stage rocket is given; the optimal control problem is formulated as a parameter optimization problem; and the optimal trajectory is computed using a nonlinear programming code called VF02AD. Numerical results are presented for the controls (angle of attack and velocity roll angle) and the states. After the initial rotation, the angle of attack goes to a positive value to keep the trajectory as high as possible, returns to near zero to pass through the transonic regime and satisfy the dynamic pressure constraint, returns to a positive value to keep the trajectory high and to take advantage of minimum drag at positive angle of attack due to aerodynamic shading of the booster, and then rolls off to negative values to satisfy the constraints. Because the engines cannot be throttled, the maximum dynamic pressure occurs at a single point; there is no maximum dynamic pressure subarc. To test approximations for obtaining analytical solutions for guidance, two additional optimal trajectories are computed: one using untrimmed aerodynamics and one using no atmospheric effects except for the dynamic pressure constraint. It is concluded that untrimmed aerodynamics has a negligible effect on the optimal trajectory and that approximate optimal controls should be able to be obtained by treating atmospheric effects as perturbations.
Optimal control of switched linear systems based on Migrant Particle Swarm Optimization algorithm
NASA Astrophysics Data System (ADS)
Xie, Fuqiang; Wang, Yongji; Zheng, Zongzhun; Li, Chuanfeng
2009-10-01
The optimal control problem for switched linear systems with internally forced switching has more constraints than with externally forced switching. Heavy computations and slow convergence in solving this problem is a major obstacle. In this paper we describe a new approach for solving this problem, which is called Migrant Particle Swarm Optimization (Migrant PSO). Imitating the behavior of a flock of migrant birds, the Migrant PSO applies naturally to both continuous and discrete spaces, in which definitive optimization algorithm and stochastic search method are combined. The efficacy of the proposed algorithm is illustrated via a numerical example.
Integrated control/structure optimization by multilevel decomposition
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Gilbert, Michael G.
1990-01-01
A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The present paper fully decomposes the system into structural and control subsystem designs and produces an improved design. Theory, implementation, and results for the method are presented and compared with the benchmark example.
Optimal Discrete Event Supervisory Control of Aircraft Gas Turbine Engines
NASA Technical Reports Server (NTRS)
Litt, Jonathan (Technical Monitor); Ray, Asok
2004-01-01
This report presents an application of the recently developed theory of optimal Discrete Event Supervisory (DES) control that is based on a signed real measure of regular languages. The DES control techniques are validated on an aircraft gas turbine engine simulation test bed. The test bed is implemented on a networked computer system in which two computers operate in the client-server mode. Several DES controllers have been tested for engine performance and reliability.
Integrated control/structure optimization by multilevel decomposition
NASA Technical Reports Server (NTRS)
Zeiler, Thomas A.; Gilbert, Michael G.
1990-01-01
A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The system is fully decomposed into structural and control subsystem designs and an improved design is produced. Theory, implementation, and results for the method are presented and compared with the benchmark example.
An optimal performance control scheme for a 3D crane
NASA Astrophysics Data System (ADS)
Maghsoudi, Mohammad Javad; Mohamed, Z.; Husain, A. R.; Tokhi, M. O.
2016-01-01
This paper presents an optimal performance control scheme for control of a three dimensional (3D) crane system including a Zero Vibration shaper which considers two control objectives concurrently. The control objectives are fast and accurate positioning of a trolley and minimum sway of a payload. A complete mathematical model of a lab-scaled 3D crane is simulated in Simulink. With a specific cost function the proposed controller is designed to cater both control objectives similar to a skilled operator. Simulation and experimental studies on a 3D crane show that the proposed controller has better performance as compared to a sequentially tuned PID-PID anti swing controller. The controller provides better position response with satisfactory payload sway in both rail and trolley responses. Experiments with different payloads and cable lengths show that the proposed controller is robust to changes in payload with satisfactory responses.
Force control of a tri-layer conducting polymer actuator using optimized fuzzy logic control
NASA Astrophysics Data System (ADS)
Itik, Mehmet; Sabetghadam, Mohammadreza; Alici, Gursel
2014-12-01
Conducting polymers actuators (CPAs) are potential candidates for replacing conventional actuators in various fields, such as robotics and biomedical engineering, due to their advantageous properties, which includes their low cost, light weight, low actuation voltage and biocompatibility. As these actuators are very suitable for use in micro-nano manipulation and in injection devices in which the magnitude of the force applied to the target is of crucial importance, the force generated by CPAs needs to be accurately controlled. In this paper, a fuzzy logic (FL) controller with a Mamdani inference system is designed to control the blocking force of a trilayer CPA with polypyrrole electrodes, which operates in air. The particle swarm optimization (PSO) method is employed to optimize the controller’s membership function parameters and therefore enhance the performance of the FL controller. An adaptive neuro-fuzzy inference system model, which can capture the nonlinear dynamics of the actuator, is utilized in the optimization process. The optimized Mamdani FL controller is then implemented on the CPA experimentally, and its performance is compared with a non-optimized fuzzy controller as well as with those obtained from a conventional PID controller. The results presented indicate that the blocking force at the tip of the CPA can be effectively controlled by the optimized FL controller, which shows excellent transient and steady state characteristics but increases the control voltage compared to the non-optimized fuzzy controllers.
Optimally controlling the internal dynamics of a randomly oriented ensemble of molecules
NASA Astrophysics Data System (ADS)
Turinici, Gabriel; Rabitz, Herschel
2004-12-01
The ultrafast control of large polyatomic molecules in the gas and condensed phases entails working with a randomly oriented ensemble. During the short control period, little reorientation may occur, especially for cases in the condensed phases. This paper addresses the degree to which all members of the ensemble may be simultaneously controlled with respect to their internal motion by a single laser pulse. It is shown that all members of the ensemble are fully controllable if any one member is. Numerical optimal control simulations also show that excellent quality full ensemble control can be achieved even with reasonable constraints placed on the control fields. Although the full ensemble may be controlled to a high degree, the control mechanism is likely to differ for each ensemble member.
Optimal control strategy for abnormal innate immune response.
Tan, Jinying; Zou, Xiufen
2015-01-01
Innate immune response plays an important role in control and clearance of pathogens following viral infection. However, in the majority of virus-infected individuals, the response is insufficient because viruses are known to use different evasion strategies to escape immune response. In this study, we use optimal control theory to investigate how to control the innate immune response. We present an optimal control model based on an ordinary-differential-equation system from a previous study, which investigated the dynamics and regulation of virus-triggered innate immune signaling pathways, and we prove the existence of a solution to the optimal control problem involving antiviral treatment or/and interferon therapy. We conduct numerical experiments to investigate the treatment effects of different control strategies through varying the cost function and control efficiency. The results show that a separate treatment, that is, only inhibiting viral replication (u1(t)) or enhancing interferon activity (u2(t)), has more advantages for controlling viral infection than a mixed treatment, that is, controlling both (u1(t)) and (u2(t)) simultaneously, including the smallest cost and operability. These findings would provide new insight for developing effective strategies for treatment of viral infectious diseases.
A duality framework for stochastic optimal control of complex systems
Malikopoulos, Andreas A.
2016-01-01
In this study, we address the problem of minimizing the long-run expected average cost of a complex system consisting of interactive subsystems. We formulate a multiobjective optimization problem of the one-stage expected costs of the subsystems and provide a duality framework to prove that the control policy yielding the Pareto optimal solution minimizes the average cost criterion of the system. We provide the conditions of existence and a geometric interpretation of the solution. For practical situations having constraints consistent with those studied here, our results imply that the Pareto control policy may be of value when we seek to derivemore » online the optimal control policy in complex systems.« less
An optimal control approach to probabilistic Boolean networks
NASA Astrophysics Data System (ADS)
Liu, Qiuli
2012-12-01
External control of some genes in a genetic regulatory network is useful for avoiding undesirable states associated with some diseases. For this purpose, a number of stochastic optimal control approaches have been proposed. Probabilistic Boolean networks (PBNs) as powerful tools for modeling gene regulatory systems have attracted considerable attention in systems biology. In this paper, we deal with a problem of optimal intervention in a PBN with the help of the theory of discrete time Markov decision process. Specifically, we first formulate a control model for a PBN as a first passage model for discrete time Markov decision processes and then find, using a value iteration algorithm, optimal effective treatments with the minimal expected first passage time over the space of all possible treatments. In order to demonstrate the feasibility of our approach, an example is also displayed.
Single step optimization of manipulator maneuvers with variable structure control
NASA Technical Reports Server (NTRS)
Chen, N.; Dwyer, T. A. W., III
1987-01-01
One step ahead optimization has been recently proposed for spacecraft attitude maneuvers as well as for robot manipulator maneuvers. Such a technique yields a discrete time control algorithm implementable as a sequence of state-dependent, quadratic programming problems for acceleration optimization. Its sensitivity to model accuracy, for the required inversion of the system dynamics, is shown in this paper to be alleviated by a fast variable structure control correction, acting between the sampling intervals of the slow one step ahead discrete time acceleration command generation algorithm. The slow and fast looping concept chosen follows that recently proposed for optimal aiming strategies with variable structure control. Accelerations required by the VSC correction are reserved during the slow one step ahead command generation so that the ability to overshoot the sliding surface is guaranteed.
How do different components of Effortful Control contribute to children's mathematics achievement?
Sánchez-Pérez, Noelia; Fuentes, Luis J; Pina, Violeta; López-López, Jose A; González-Salinas, Carmen
2015-01-01
This work sought to investigate the specific contribution of two different components of Effortful Control (EC) -attentional focusing (AF) and inhibitory control- to children's mathematics achievement. The sample was composed of 142 children aged 9-12 year-old. EC components were measured through the Temperament in Middle Childhood Questionnaire (TMCQ; parent's report); math achievement was measured via teacher's report and through the standard Woodcock-Johnson test. Additionally, the contribution of other cognitive and socio-emotional processes was taken into account. Our results showed that only AF significantly contributed to the variance of children's mathematics achievement; interestingly, mediational models showed that the relationship between effortful attentional self-regulation and mathematics achievement was mediated by academic peer popularity, as well as by intelligence and study skills. Results are discussed in the light of the current theories on the role of children's self-regulation abilities in the context of school.
How do different components of Effortful Control contribute to children's mathematics achievement?
Sánchez-Pérez, Noelia; Fuentes, Luis J; Pina, Violeta; López-López, Jose A; González-Salinas, Carmen
2015-01-01
This work sought to investigate the specific contribution of two different components of Effortful Control (EC) -attentional focusing (AF) and inhibitory control- to children's mathematics achievement. The sample was composed of 142 children aged 9-12 year-old. EC components were measured through the Temperament in Middle Childhood Questionnaire (TMCQ; parent's report); math achievement was measured via teacher's report and through the standard Woodcock-Johnson test. Additionally, the contribution of other cognitive and socio-emotional processes was taken into account. Our results showed that only AF significantly contributed to the variance of children's mathematics achievement; interestingly, mediational models showed that the relationship between effortful attentional self-regulation and mathematics achievement was mediated by academic peer popularity, as well as by intelligence and study skills. Results are discussed in the light of the current theories on the role of children's self-regulation abilities in the context of school. PMID:26441758
A multiple objective optimization approach to quality control
NASA Technical Reports Server (NTRS)
Seaman, Christopher Michael
1991-01-01
The use of product quality as the performance criteria for manufacturing system control is explored. The goal in manufacturing, for economic reasons, is to optimize product quality. The problem is that since quality is a rather nebulous product characteristic, there is seldom an analytic function that can be used as a measure. Therefore standard control approaches, such as optimal control, cannot readily be applied. A second problem with optimizing product quality is that it is typically measured along many dimensions: there are many apsects of quality which must be optimized simultaneously. Very often these different aspects are incommensurate and competing. The concept of optimality must now include accepting tradeoffs among the different quality characteristics. These problems are addressed using multiple objective optimization. It is shown that the quality control problem can be defined as a multiple objective optimization problem. A controller structure is defined using this as the basis. Then, an algorithm is presented which can be used by an operator to interactively find the best operating point. Essentially, the algorithm uses process data to provide the operator with two pieces of information: (1) if it is possible to simultaneously improve all quality criteria, then determine what changes to the process input or controller parameters should be made to do this; and (2) if it is not possible to improve all criteria, and the current operating point is not a desirable one, select a criteria in which a tradeoff should be made, and make input changes to improve all other criteria. The process is not operating at an optimal point in any sense if no tradeoff has to be made to move to a new operating point. This algorithm ensures that operating points are optimal in some sense and provides the operator with information about tradeoffs when seeking the best operating point. The multiobjective algorithm was implemented in two different injection molding scenarios
Optimization of the cooling profile to achieve crack-free Yb:S-FAP crystals
NASA Astrophysics Data System (ADS)
Fang, H. S.; Qiu, S. R.; Zheng, L. L.; Schaffers, K. I.; Tassano, J. B.; Caird, J. A.; Zhang, H.
2008-08-01
Yb:S-FAP [Yb 3+:Sr 5(PO 4) 3F] crystals are an important gain medium for diode-pumped laser applications. Growth of 7.0 cm diameter Yb:S-FAP crystals utilizing the Czochralski (CZ) method from SrF 2-rich melts often encounters cracks during the post-growth cool-down stage. To suppress cracking during cool-down, a numerical simulation of the growth system was used to understand the correlation between the furnace power during cool-down and the radial temperature differences within the crystal. The critical radial temperature difference, above which the crystal cracks, has been determined by benchmarking the simulation results against experimental observations. Based on this comparison, an optimal three-stage ramp-down profile was implemented, which produced high-quality, crack-free Yb:S-FAP crystals.
Optimization of the cooling profile to achieve crack-free Yb:S-FAP crystals
Fang, H; Qiu, S; Kheng, L; Schaffers, K; Tassano, J; Caird, J; Zhang, H
2007-08-20
Yb:S-FAP [Yb{sup 3+}:Sr{sub 5}(PO{sub 4}){sub 3}F] crystals are an important gain medium for diode-pumped laser applications. Growth of 7.0 cm diameter Yb:S-FAP crystals utilizing the Czochralski (CZ) method from SrF{sub 2}-rich melts often encounter cracks during the post growth cool down stage. To suppress cracking during cool down, a numerical simulation of the growth system was used to understand the correlation between the furnace power during cool down and the radial temperature differences within the crystal. The critical radial temperature difference, above which the crystal cracks, has been determined by benchmarking the simulation results against experimental observations. Based on this comparison, an optimal three-stage ramp-down profile was implemented and produced high quality, crack-free Yb:S-FAP crystals.
Multidisciplinary optimization of controlled space structures with global sensitivity equations
NASA Technical Reports Server (NTRS)
Padula, Sharon L.; James, Benjamin B.; Graves, Philip C.; Woodard, Stanley E.
1991-01-01
A new method for the preliminary design of controlled space structures is presented. The method coordinates standard finite element structural analysis, multivariable controls, and nonlinear programming codes and allows simultaneous optimization of the structures and control systems of a spacecraft. Global sensitivity equations are a key feature of this method. The preliminary design of a generic geostationary platform is used to demonstrate the multidisciplinary optimization method. Fifteen design variables are used to optimize truss member sizes and feedback gain values. The goal is to reduce the total mass of the structure and the vibration control system while satisfying constraints on vibration decay rate. Incorporating the nonnegligible mass of actuators causes an essential coupling between structural design variables and control design variables. The solution of the demonstration problem is an important step toward a comprehensive preliminary design capability for structures and control systems. Use of global sensitivity equations helps solve optimization problems that have a large number of design variables and a high degree of coupling between disciplines.
Quadratic Optimization in the Problems of Active Control of Sound
NASA Technical Reports Server (NTRS)
Loncaric, J.; Tsynkov, S. V.; Bushnell, Dennis M. (Technical Monitor)
2002-01-01
We analyze the problem of suppressing the unwanted component of a time-harmonic acoustic field (noise) on a predetermined region of interest. The suppression is rendered by active means, i.e., by introducing the additional acoustic sources called controls that generate the appropriate anti-sound. Previously, we have obtained general solutions for active controls in both continuous and discrete formulations of the problem. We have also obtained optimal solutions that minimize the overall absolute acoustic source strength of active control sources. These optimal solutions happen to be particular layers of monopoles on the perimeter of the protected region. Mathematically, minimization of acoustic source strength is equivalent to minimization in the sense of L(sub 1). By contrast. in the current paper we formulate and study optimization problems that involve quadratic functions of merit. Specifically, we minimize the L(sub 2) norm of the control sources, and we consider both the unconstrained and constrained minimization. The unconstrained L(sub 2) minimization is certainly the easiest problem to address numerically. On the other hand, the constrained approach allows one to analyze sophisticated geometries. In a special case, we call compare our finite-difference optimal solutions to the continuous optimal solutions obtained previously using a semi-analytic technique. We also show that the optima obtained in the sense of L(sub 2) differ drastically from those obtained in the sense of L(sub 1).
Optimal design of clinical trials comparing several treatments with a control.
Marschner, Ian C
2007-01-01
Clinical trials are often designed to compare several treatments with a common control arm in pairwise fashion. In this paper we study optimal designs for such studies, based on minimizing the total number of patients required to achieve a given level of power. A common approach when designing studies to compare several treatments with a control is to achieve the desired power for each individual pairwise treatment comparison. However, it is often more appropriate to characterize power in terms of the family of null hypotheses being tested, and to control the probability of rejecting all, or alternatively any, of these individual hypotheses. While all approaches lead to unbalanced designs with more patients allocated to the control arm, it is found that the optimal design and required number of patients can vary substantially depending on the chosen characterization of power. The methods make allowance for both continuous and binary outcomes and are illustrated with reference to two clinical trials, one involving multiple doses compared to placebo and the other involving combination therapy compared to mono-therapies. In one example a 55% reduction in sample size is achieved through an optimal design combined with the appropriate characterization of power. PMID:17323312
An inverter/controller subsystem optimized for photovoltaic applications
NASA Technical Reports Server (NTRS)
Pickrell, R. L.; Osullivan, G.; Merrill, W. C.
1978-01-01
Conversion of solar array dc power to ac power stimulated the specification, design, and simulation testing of an inverter/controller subsystem tailored to the photovoltaic power source characteristics. Optimization of the inverter/controller design is discussed as part of an overall photovoltaic power system designed for maximum energy extraction from the solar array. The special design requirements for the inverter/ controller include: a power system controller (PSC) to control continuously the solar array operating point at the maximum power level based on variable solar insolation and cell temperatures; and an inverter designed for high efficiency at rated load and low losses at light loadings to conserve energy.
Locus of control, test anxiety, academic procrastination, and achievement among college students.
Carden, Randy; Bryant, Courtney; Moss, Rebekah
2004-10-01
114 undergraduates completed the Internal-External Locus of Control scale, the Procrastination Scale, and the Achievement Anxiety Test. They also provided a self-report of their cumulative GPA. Students were divided into two groups by a median-split of 10.5, yielding an internally oriented group of 57 and an externally oriented group of 57. The former students showed significantly lower academic procrastination, debilitating test anxiety, and reported higher academic achievement than the latter.
Torque-based optimal acceleration control for electric vehicle
NASA Astrophysics Data System (ADS)
Lu, Dongbin; Ouyang, Minggao
2014-03-01
The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin's maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle(EV) has not been reported. In this paper, the permanent magnet synchronous motor(PMSM) is controlled by the field oriented control(FOC) method and the electric drive system for the EV(including the PMSM, the inverter and the battery) is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming(DP). This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV's acceleration process and the analytical algorithm is easy to be implemented in real-time control.
Control design variable linking for optimization of structural/control systems
NASA Technical Reports Server (NTRS)
Jin, I. M.; Schmit, L. A.
1991-01-01
In this study a method is presented to integrate the design space of structural/control system optimization problems in the case of state feedback control. Conventional structural sizing variables and elements of the feedback gain matrix are both treated as strictly independent design variables in the optimization by extending design variable linking concepts to the control gains. Examples which involve a variety of behavior constraints, including dynamic transient response and control force limits, are effectively solved by using the method presented.
NASA Technical Reports Server (NTRS)
Cunefare, K. A.; Koopmann, G. H.
1991-01-01
This paper presents the theoretical development of an approach to active noise control (ANC) applicable to three-dimensional radiators. The active noise control technique, termed ANC Optimization Analysis, is based on minimizing the total radiated power by adding secondary acoustic sources on the primary noise source. ANC Optimization Analysis determines the optimum magnitude and phase at which to drive the secondary control sources in order to achieve the best possible reduction in the total radiated power from the noise source/control source combination. For example, ANC Optimization Analysis predicts a 20 dB reduction in the total power radiated from a sphere of radius at a dimensionless wavenumber ka of 0.125, for a single control source representing 2.5 percent of the total area of the sphere. ANC Optimization Analysis is based on a boundary element formulation of the Helmholtz Integral Equation, and thus, the optimization analysis applies to a single frequency, while multiple frequencies can be treated through repeated analyses.
Optimizing Locomotion Controllers Using Biologically-Based Actuators and Objectives
Wang, Jack M.; Hamner, Samuel R.; Delp, Scott L.; Koltun, Vladlen
2015-01-01
We present a technique for automatically synthesizing walking and running controllers for physically-simulated 3D humanoid characters. The sagittal hip, knee, and ankle degrees-of-freedom are actuated using a set of eight Hill-type musculotendon models in each leg, with biologically-motivated control laws. The parameters of these control laws are set by an optimization procedure that satisfies a number of locomotion task terms while minimizing a biological model of metabolic energy expenditure. We show that the use of biologically-based actuators and objectives measurably increases the realism of gaits generated by locomotion controllers that operate without the use of motion capture data, and that metabolic energy expenditure provides a simple and unifying measurement of effort that can be used for both walking and running control optimization. PMID:26251560
Optimal control alleviation of tilting proprotor gust response
NASA Technical Reports Server (NTRS)
Johnson, W.
1975-01-01
Optimal control theory is applied to the design of a control system for alleviation of the gust response of tilting proprotor aircraft. Using a proprotor and cantilever wing analytical model, the uncontrolled and controlled gust response is examined over the entire operating range of the aircraft except for hover: helicopter mode, conversion, and airplane mode flight. Substantial improvements in the loads, ride quality, and aeroelastic stability are possible with a properly designed controller. A single controller, nominally optimal only at the design point speed (160 knots here), operated efficiently over the entire speed range, with the possible exception of very low speed in helicopter mode. Kalman-Bucy filters were used as compensation networks to provide state estimates from various measurements in the wing motion, rotor speed perturbation, and tip-path-plane tilt.
Fuel optimal control of an experimental multi-mode system
NASA Technical Reports Server (NTRS)
Redmond, J.; Mayer, J. L.; Silverberg, L.
1992-01-01
In this paper, the dynamic characteristics associated with the fuel optimal control of a harmonic oscillator are utilized in the development of a near fuel optimal feedback control strategy for spacecraft vibration suppression. In this scheme, single level thrust actuators are governed by recursive computations of the standard deviations of displacement and velocity at the actuator's locations. The algorithm was tested on an experimental structure possessing a significant number of flexible body modes. The structure's response to both single and multiple mode excitation is presented.
Optimal control of underactuated mechanical systems: A geometric approach
NASA Astrophysics Data System (ADS)
Colombo, Leonardo; Martín De Diego, David; Zuccalli, Marcela
2010-08-01
In this paper, we consider a geometric formalism for optimal control of underactuated mechanical systems. Our techniques are an adaptation of the classical Skinner and Rusk approach for the case of Lagrangian dynamics with higher-order constraints. We study a regular case where it is possible to establish a symplectic framework and, as a consequence, to obtain a unique vector field determining the dynamics of the optimal control problem. These developments will allow us to develop a new class of geometric integrators based on discrete variational calculus.
Optimal placement of active elements in control augmented structural synthesis
NASA Technical Reports Server (NTRS)
Sepulveda, A. E.; Jin, I. M.; Schmit, L. A., Jr.
1992-01-01
A methodology for structural/control synthesis is presented in which the optimal location of active members is treated in terms of (0,1) variables. Structural member sizes, control gains and (0,1) placement variables are treated simultaneously as design variables. Optimization is carried out by generating and solving a sequence of explicit approximate problems using a branch and bound strategy. Intermediate design variable and intermediate response quantity concepts are used to enhance the quality of the approximate design problems. Numerical results for example problems are presented to illustrate the efficacy of the design procedure set forth.
Optimal control of quaternion propagation errors in spacecraft navigation
NASA Technical Reports Server (NTRS)
Vathsal, S.
1986-01-01
Optimal control techniques are used to drive the numerical error (truncation, roundoff, commutation) in computing the quaternion vector to zero. The normalization of the quaternion is carried out by appropriate choice of a performance index, which can be optimized. The error equations are derived from Friedland's (1978) theoretical development, and a matrix Riccati equation results for the computation of the gain matrix. Simulation results show that a high precision of the order of 10 to the -12th can be obtained using this technique in meeting the q(T)q=1 constraint. The performance of the estimator in the presence of the feedback control that maintains the normalization, is studied.
Control and structural optimization for maneuvering large spacecraft
NASA Technical Reports Server (NTRS)
Chun, H. M.; Turner, J. D.; Yu, C. C.
1990-01-01
Presented here are the results of an advanced control design as well as a discussion of the requirements for automating both the structures and control design efforts for maneuvering a large spacecraft. The advanced control application addresses a general three dimensional slewing problem, and is applied to a large geostationary platform. The platform consists of two flexible antennas attached to the ends of a flexible truss. The control strategy involves an open-loop rigid body control profile which is derived from a nonlinear optimal control problem and provides the main control effort. A perturbation feedback control reduces the response due to the flexibility of the structure. Results are shown which demonstrate the usefulness of the approach. Software issues are considered for developing an integrated structures and control design environment.
NASA Astrophysics Data System (ADS)
Chong, Lee Wai; Wong, Yee Wan; Rajkumar, Rajprasad Kumar; Isa, Dino
2016-11-01
This paper proposes an optimal control strategy for a standalone PV system with Battery-Supercapacitor Hybrid Energy Storage System to prolong battery lifespan by reducing the dynamic stress and peak current demand of the battery. Unlike the conventional methods which only use either filtration based controller (FBC) or fuzzy logic controller (FLC), the proposed control strategy comprises of a low-pass filter (LPF) and FLC. Firstly, LPF removes the high dynamic components from the battery demand. FLC minimizes the battery peak current demand while constantly considering the state-of-charge of the supercapacitor. Particle swarm optimization (PSO) algorithm optimizes the membership functions of the FLC to achieve optimal battery peak current reduction. The proposed system is compared to the conventional system with battery-only storage and the systems with conventional control strategies (Rule Based Controller and FBC). The proposed system reduces the battery peak current, battery peak power, maximum absolute value of the rate of change of power and average absolute value of the rate of change of power by 16.05%, 15.19%, 77.01%, and 95.59%, respectively as compared to the conventional system with battery-only storage. Moreover, he proposed system increases the level of supercapacitor utilization up to 687.122% in comparison to the conventional control strategies.
Occupant-responsive optimal control of smart facade systems
NASA Astrophysics Data System (ADS)
Park, Cheol-Soo
Windows provide occupants with daylight, direct sunlight, visual contact with the outside and a feeling of openness. Windows enable the use of daylighting and offer occupants a outside view. Glazing may also cause a number of problems: undesired heat gain/loss in winter. An over-lit window can cause glare, which is another major complaint by occupants. Furthermore, cold or hot window surfaces induce asymmetric thermal radiation which can result in thermal discomfort. To reduce the potential problems of window systems, double skin facades and airflow window systems have been introduced in the 1970s. They typically contain interstitial louvers and ventilation openings. The current problem with double skin facades and airflow windows is that their operation requires adequate dynamic control to reach their expected performance. Many studies have recognized that only an optimal control enables these systems to truly act as active energy savers and indoor environment controllers. However, an adequate solution for this dynamic optimization problem has thus far not been developed. The primary objective of this study is to develop occupant responsive optimal control of smart facade systems. The control could be implemented as a smart controller that operates the motorized Venetian blind system and the opening ratio of ventilation openings. The objective of the control is to combine the benefits of large windows with low energy demands for heating and cooling, while keeping visual well-being and thermal comfort at an optimal level. The control uses a simulation model with an embedded optimization routine that allows occupant interaction via the Web. An occupant can access the smart controller from a standard browser and choose a pre-defined mode (energy saving mode, visual comfort mode, thermal comfort mode, default mode, nighttime mode) or set a preferred mode (user-override mode) by moving preference sliders on the screen. The most prominent feature of these systems is the
Optimal control, investment and utilization schemes for energy storage under uncertainty
NASA Astrophysics Data System (ADS)
Mirhosseini, Niloufar Sadat
Energy storage has the potential to offer new means for added flexibility on the electricity systems. This flexibility can be used in a number of ways, including adding value towards asset management, power quality and reliability, integration of renewable resources and energy bill savings for the end users. However, uncertainty about system states and volatility in system dynamics can complicate the question of when to invest in energy storage and how best to manage and utilize it. This work proposes models to address different problems associated with energy storage within a microgrid, including optimal control, investment, and utilization. Electric load, renewable resources output, storage technology cost and electricity day-ahead and spot prices are the factors that bring uncertainty to the problem. A number of analytical methodologies have been adopted to develop the aforementioned models. Model Predictive Control and discretized dynamic programming, along with a new decomposition algorithm are used to develop optimal control schemes for energy storage for two different levels of renewable penetration. Real option theory and Monte Carlo simulation, coupled with an optimal control approach, are used to obtain optimal incremental investment decisions, considering multiple sources of uncertainty. Two stage stochastic programming is used to develop a novel and holistic methodology, including utilization of energy storage within a microgrid, in order to optimally interact with energy market. Energy storage can contribute in terms of value generation and risk reduction for the microgrid. The integration of the models developed here are the basis for a framework which extends from long term investments in storage capacity to short term operational control (charge/discharge) of storage within a microgrid. In particular, the following practical goals are achieved: (i) optimal investment on storage capacity over time to maximize savings during normal and emergency
Digital robust control law synthesis using constrained optimization
NASA Technical Reports Server (NTRS)
Mukhopadhyay, Vivekananda
1989-01-01
Development of digital robust control laws for active control of high performance flexible aircraft and large space structures is a research area of significant practical importance. The flexible system is typically modeled by a large order state space system of equations in order to accurately represent the dynamics. The active control law must satisy multiple conflicting design requirements and maintain certain stability margins, yet should be simple enough to be implementable on an onboard digital computer. Described here is an application of a generic digital control law synthesis procedure for such a system, using optimal control theory and constrained optimization technique. A linear quadratic Gaussian type cost function is minimized by updating the free parameters of the digital control law, while trying to satisfy a set of constraints on the design loads, responses and stability margins. Analytical expressions for the gradients of the cost function and the constraints with respect to the control law design variables are used to facilitate rapid numerical convergence. These gradients can be used for sensitivity study and may be integrated into a simultaneous structure and control optimization scheme.
Optimal control for stochastic systems with polynomial chaos
NASA Astrophysics Data System (ADS)
Gallagher, David James
Assuring robustness of control system performance against model uncertainty is a significant component of control design. Current methods for developing a robust controller, however, are typically either too conservative or too computationally expensive. This thesis uses generalized polynomial chaos alongside finite-horizon optimal control as a new method of robust control design for a stochastic system. Since the equations for the mean and variance of the response can be expressed in terms of coefficients from a polynomial chaos expansion, optimizing a polynomial chaos expansion can be used to optimize the mean and variance, thus providing robust responses in a stochastic system. This thesis first provides a review of the concepts and literature then the rationale as well as the derivation of the proposed robust control method. Three examples are given to show the effectiveness of the new control method and are discussed. In particular, the final example demonstrates the applicability of using polynomial chaos to provide robust control for a stochastic soft landing problem.
Tian, Chao; Chen, Jia; Zhang, Bo; Shan, Lianqiang; Zhou, Weimin; Liu, Dongxiao; Bi, Bi; Zhang, Feng; Wang, Weiwu; Zhang, Baohan; Gu, Yuqiu
2015-05-01
The uniformity of the compression driver is of fundamental importance for inertial confinement fusion (ICF). In this paper, the illumination uniformity on a spherical capsule during the initial imprinting phase directly driven by laser beams has been considered. We aim to explore methods to achieve high direct drive illumination uniformity on laser facilities designed for indirect drive ICF. There are many parameters that would affect the irradiation uniformity, such as Polar Direct Drive displacement quantity, capsule radius, laser spot size and intensity distribution within a laser beam. A novel approach to reduce the root mean square illumination non-uniformity based on multi-parameter optimizing approach (particle swarm optimization) is proposed, which enables us to obtain a set of optimal parameters over a large parameter space. Finally, this method is applied to improve the direct drive illumination uniformity provided by Shenguang III laser facility and the illumination non-uniformity is reduced from 5.62% to 0.23% for perfectly balanced beams. Moreover, beam errors (power imbalance and pointing error) are taken into account to provide a more practical solution and results show that this multi-parameter optimization approach is effective.
Automated design of multiphase space missions using hybrid optimal control
NASA Astrophysics Data System (ADS)
Chilan, Christian Miguel
A modern space mission is assembled from multiple phases or events such as impulsive maneuvers, coast arcs, thrust arcs and planetary flybys. Traditionally, a mission planner would resort to intuition and experience to develop a sequence of events for the multiphase mission and to find the space trajectory that minimizes propellant use by solving the associated continuous optimal control problem. This strategy, however, will most likely yield a sub-optimal solution, as the problem is sophisticated for several reasons. For example, the number of events in the optimal mission structure is not known a priori and the system equations of motion change depending on what event is current. In this work a framework for the automated design of multiphase space missions is presented using hybrid optimal control (HOC). The method developed uses two nested loops: an outer-loop that handles the discrete dynamics and finds the optimal mission structure in terms of the categorical variables, and an inner-loop that performs the optimization of the corresponding continuous-time dynamical system and obtains the required control history. Genetic algorithms (GA) and direct transcription with nonlinear programming (NLP) are introduced as methods of solution for the outer-loop and inner-loop problems, respectively. Automation of the inner-loop, continuous optimal control problem solver, required two new technologies. The first is a method for the automated construction of the NLP problems resulting from the use of a direct solver for systems with different structures, including different numbers of categorical events. The method assembles modules, consisting of parameters and constraints appropriate to each event, sequentially according to the given mission structure. The other new technology is for a robust initial guess generator required by the inner-loop NLP problem solver. Two new methods were developed for cases including low-thrust trajectories. The first method, based on GA
Optimization and Control of Cyber-Physical Vehicle Systems.
Bradley, Justin M; Atkins, Ella M
2015-01-01
A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined. PMID:26378541
Optimization and Control of Cyber-Physical Vehicle Systems.
Bradley, Justin M; Atkins, Ella M
2015-09-11
A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.
Optimization and Control of Cyber-Physical Vehicle Systems
Bradley, Justin M.; Atkins, Ella M.
2015-01-01
A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined. PMID:26378541
Standardization and Optimization of Computed Tomography Protocols to Achieve Low-Dose
Chin, Cynthia; Cody, Dianna D.; Gupta, Rajiv; Hess, Christopher P.; Kalra, Mannudeep K.; Kofler, James M.; Krishnam, Mayil S.; Einstein, Andrew J.
2014-01-01
The increase in radiation exposure due to CT scans has been of growing concern in recent years. CT scanners differ in their capabilities and various indications require unique protocols, but there remains room for standardization and optimization. In this paper we summarize approaches to reduce dose, as discussed in lectures comprising the first session of the 2013 UCSF Virtual Symposium on Radiation Safety in Computed Tomography. The experience of scanning at low dose in different body regions, for both diagnostic and interventional CT procedures, is addressed. An essential primary step is justifying the medical need for each scan. General guiding principles for reducing dose include tailoring a scan to a patient, minimizing scan length, use of tube current modulation and minimizing tube current, minimizing-tube potential, iterative reconstruction, and periodic review of CT studies. Organized efforts for standardization have been spearheaded by professional societies such as the American Association of Physicists in Medicine. Finally, all team members should demonstrate an awareness of the importance of minimizing dose. PMID:24589403
An optimal control model for reducing and trading of carbon emissions
NASA Astrophysics Data System (ADS)
Guo, Huaying; Liang, Jin
2016-03-01
A stochastic optimal control model of reducing and trading for carbon emissions is established in this paper. With considerations of reducing the carbon emission growth and the price of the allowances in the market, an optimal policy is searched to have the minimum total costs to achieve the agreement of emission reduction targets. The model turns to a two-dimension HJB equation problem. By the methods of reducing dimension and Cole-Hopf transformation, a semi-closed form solution of the corresponding HJB problem under some assumptions is obtained. For more general cases, the numerical calculations, analysis and comparisons are presented.
Using Chemicals to Optimize Conformance Control in Fractured Reservoirs
Seright, Randall S.; Liang, Jenn-Tai; Schrader, Richard; Hagstrom II, John; Liu, Jin; Wavrik, Kathryn
1999-09-27
This report describes work performed during the first year of the project, ''Using Chemicals to Optimize Conformance Control in Fractured Reservoirs.'' This research project has three objectives. The first objective is to develop a capability to predict and optimize the ability of gels to reduce permeability to water more than that to oil or gas. The second objective is to develop procedures for optimizing blocking agent placement in wells where hydraulic fractures cause channeling problems. The third objective is to develop procedures to optimize blocking agent placement in naturally fractured reservoirs. This research project consists of three tasks, each of which addresses one of the above objectives. Our work is directed at both injection wells and production wells and at vertical, horizontal, and highly deviated wells.
Advanced, Integrated Control for Building Operations to Achieve 40% Energy Saving
Lu, Yan; Song, Zhen; Loftness, Vivian; Ji, Kun; Zheng, Sam; Lasternas, Bertrand; Marion, Flore; Yuebin, Yu
2012-10-15
We developed and demonstrated a software based integrated advanced building control platform called Smart Energy Box (SEB), which can coordinate building subsystem controls, integrate variety of energy optimization algorithms and provide proactive and collaborative energy management and control for building operations using weather and occupancy information. The integrated control system is a low cost solution and also features: Scalable component based architecture allows to build a solution for different building control system configurations with needed components; Open Architecture with a central data repository for data exchange among runtime components; Extendible to accommodate variety of communication protocols. Optimal building control for central loads, distributed loads and onsite energy resource; uses web server as a loosely coupled way to engage both building operators and building occupants in collaboration for energy conservation. Based on the open platform of SEB, we have investigated and evaluated a variety of operation and energy saving control strategies on Carnegie Mellon University Intelligent Work place which is equipped with alternative cooling/heating/ventilation/lighting methods, including radiant mullions, radiant cooling/heating ceiling panels, cool waves, dedicated ventilation unit, motorized window and blinds, and external louvers. Based on the validation results of these control strategies, they were integrated in SEB in a collaborative and dynamic way. This advanced control system was programmed and computer tested with a model of the Intelligent Workplace's northern section (IW_{n}). The advanced control program was then installed in the IW_{n} control system; the performance was measured and compared with that of the state of the art control system to verify the overall energy savings great than 40%. In addition advanced human machine interfaces (HMI's) were developed to communicate both with building occupants and
Rapidly optimizing an aptamer based BoNT sensor by feedback system control (FSC) scheme.
Wei, Fang; Bai, Bin; Ho, Chih-Ming
2011-12-15
The sensitivity and detection time of an aptamer based biosensor for detecting botulinum neurotoxin (BoNT) depend upon the formation of proper tertiary architecture of aptamer, which closely correlates with the combinatorial effects of multiple types of ions and their concentrations presented in the buffer. Finding the optimal conditions for four different ions at 12 different concentrations, 20,736 possible combinations, by brute force is an extremely laborious and time-consuming task. Here, we introduce a feedback system control (FSC) scheme that can rapidly identify the best combination of components to form the optimal aptamer structure binding to a target molecule. In this study, rapid identification of optimized ionic combinations for electrochemical aptasensor of BoNT type A (BoNT/A) detection has been achieved. Only about 10 iterations with about 50 tests in each iteration are needed to identify the optimal ionic concentration out of the 20,736 possibilities. The most exciting finding was that a very short detection time and high sensitivity could be achieved with the optimized combinational ion buffer. Only a 5-min detection time, compared with hours or even days, was needed for aptamer-based BoNT/A detection with a limit of detection of 40 pg/ml. The methodologies described here can be applied to other multi-parameter chemical systems, which should significantly improve the rate of parameter optimization.
Optimal preview game theory approach to vehicle stability controller design
NASA Astrophysics Data System (ADS)
Tamaddoni, Seyed Hossein; Taheri, Saied; Ahmadian, Mehdi
2011-12-01
Dynamic game theory brings together different features that are keys to many situations in control design: optimisation behaviour, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In the presented methodology, vehicle stability is represented by a cooperative dynamic/difference game such that its two agents (players), namely the driver and the direct yaw controller (DYC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the DYC control algorithm is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degrees-of-freedom vehicle-handling performance model is put into discrete form to develop the game equations of motion. To evaluate the developed control algorithm, CarSim with its built-in nonlinear vehicle model along with the Pacejka tire model is used. The control algorithm is evaluated for a lane change manoeuvre, and the optimal set of steering angle and corrective yaw moment is calculated and fed to the test vehicle. Simulation results show that the optimal preview control algorithm can significantly reduce lateral velocity, yaw rate, and roll angle, which all contribute to enhancing vehicle stability.
Computer simulation of control strategies for optimal anaerobic digestion.
Strömberg, S; Possfelt, M O; Liu, J
2013-01-01
Three previously published control strategies for anaerobic digestion were implemented in Simulink/Matlab using Anaerobic Digestion Model No. 1 (ADM1) to model the biological process. The controllers' performance were then simulated and evaluated based on their responses from five different types of process scenarios i.e. start-up and steady state performance as well as disturbances from concentration, pH and ammonia in the inflow. Of the three evaluated control strategies, the extremum-seeking variable gain controller gave the best overall performance. However, a proportional feedback controller based on the pH-level, used as a reference case in the evaluation, proved to give as good results as the extremum-seeking variable gain controller but with a lower wear on the pump. It was therefore concluded that a fast proportional control of the reactor pH is a key element for optimally controlling a low-buffering anaerobic digestion process.
Lossless Convexification of Control Constraints for a Class of Nonlinear Optimal Control Problems
NASA Technical Reports Server (NTRS)
Blackmore, Lars; Acikmese, Behcet; Carson, John M.,III
2012-01-01
In this paper we consider a class of optimal control problems that have continuous-time nonlinear dynamics and nonconvex control constraints. We propose a convex relaxation of the nonconvex control constraints, and prove that the optimal solution to the relaxed problem is the globally optimal solution to the original problem with nonconvex control constraints. This lossless convexification enables a computationally simpler problem to be solved instead of the original problem. We demonstrate the approach in simulation with a planetary soft landing problem involving a nonlinear gravity field.
NASA Astrophysics Data System (ADS)
Ross, Steven M.
A method is presented to couple and solve the optimal control and the optimal estimation problems simultaneously, allowing systems with bearing-only sensors to maneuver to obtain observability for relative navigation without unnecessarily detracting from a primary mission. A fundamentally new approach to trajectory optimization and the dual control problem is presented, constraining polynomial approximations of the Fisher Information Matrix to provide an information gradient and allow prescription of the level of future estimation certainty required for mission accomplishment. Disturbances, modeling deficiencies, and corrupted measurements are addressed recursively using Radau pseudospectral collocation methods and sequential quadratic programming for the optimal path and an Unscented Kalman Filter for the target position estimate. The underlying real-time optimal control (RTOC) algorithm is developed, specifically addressing limitations of current techniques that lose error integration. The resulting guidance method can be applied to any bearing-only system, such as submarines using passive sonar, anti-radiation missiles, or small UAVs seeking to land on power lines for energy harvesting. System integration, variable timing methods, and discontinuity management techniques are provided for actual hardware implementation. Validation is accomplished with both simulation and flight test, autonomously landing a quadrotor helicopter on a wire.
Modified Newton-Raphson GRAPE methods for optimal control of spin systems
NASA Astrophysics Data System (ADS)
Goodwin, D. L.; Kuprov, Ilya
2016-05-01
Quadratic convergence throughout the active space is achieved for the gradient ascent pulse engineering (GRAPE) family of quantum optimal control algorithms. We demonstrate in this communication that the Hessian of the GRAPE fidelity functional is unusually cheap, having the same asymptotic complexity scaling as the functional itself. This leads to the possibility of using very efficient numerical optimization techniques. In particular, the Newton-Raphson method with a rational function optimization (RFO) regularized Hessian is shown in this work to require fewer system trajectory evaluations than any other algorithm in the GRAPE family. This communication describes algebraic and numerical implementation aspects (matrix exponential recycling, Hessian regularization, etc.) for the RFO Newton-Raphson version of GRAPE and reports benchmarks for common spin state control problems in magnetic resonance spectroscopy.
Effect of wind turbine response time on optimal dynamic induction control of wind farms
NASA Astrophysics Data System (ADS)
Munters, Wim; Meyers, Johan
2016-09-01
In this work, we extend recent research efforts on induction-based optimal control in large-eddy simulations of wind farms in the turbulent atmospheric boundary layer. More precisely, we investigate the effect of wind turbine response time to requested power setpoints on achievable power gains. We do this by including a time-filtering of the thrust coefficient setpoints in the optimal control framework. We consider simulation cases restricted to underinduction compared to the Betz limit, as well as cases that also allow overinduction. Optimization results show that, except for the most restrictive underinductive slow-response case, all cases still yield increases in energy extraction in the order of 10% and more.
Frye, Richard E; Rossignol, Daniel A
2016-01-01
the optimal treatments for these abnormalities. PMID:27330338
Frye, Richard E.; Rossignol, Daniel A.
2016-01-01
the optimal treatments for these abnormalities. PMID:27330338
Frye, Richard E; Rossignol, Daniel A
2016-01-01
the optimal treatments for these abnormalities.
NASA Astrophysics Data System (ADS)
Bartl, J.; Sætran, L.
2016-09-01
In state-of-the-art wind farms each turbine is controlled individually aiming for optimum turbine power not considering wake effects on downstream turbines. Wind farm control concepts aim for optimizing the overall power output of the farm taking wake interactions between the individual turbines into account. This experimental wind tunnel study investigates axial induction based control concepts. It is examined how the total array efficiency of two in-line model turbines is affected when the upstream turbine's tip speed ratio (λcontrol) or blade pitch angle (β-control) is modified. The focus is particularly directed on how the wake flow behind the upstream rotor is affected when its axial induction is reduced in order to leave more kinetic energy in the wake to be recovered by a downstream turbine. It is shown that the radial distribution of kinetic energy in the wake area can be controlled by modifying the upstream turbine's tip speed ratio. By pitching out the upstream turbine's blades, however, the available kinetic energy in the wake is increased at an equal rate over the entire blade span. Furthermore, the total array efficiency of the two turbine setup is mapped depending on the upstream turbines tip speed ratio and pitch angle. For a small turbine separation distance of x/D=3 the downstream turbine is able to recover the major part of the power lost on the upstream turbine. However, no significant increase in the two-turbine array efficiency is achieved by altering the upstream turbine's operation point away from its optimum.
Various methods of optimizing control pulses for quantum systems with decoherence
NASA Astrophysics Data System (ADS)
Pawela, Łukasz; Sadowski, Przemysław
2016-05-01
We design control setting that allows the implementation of an approximation of an unitary operation of a quantum system under decoherence using various quantum system layouts and numerical algorithms. We focus our attention on the possibility of adding ancillary qubits which help to achieve a desired quantum map on the initial system. Furthermore, we use three methods of optimizing the control pulses: genetic optimization, approximate evolution method and approximate gradient method. To model the noise in the system we use the Lindblad equation. We obtain results showing that applying the control pulses to the ancilla allows one to successfully implement unitary operation on a target system in the presence of noise, which is not possible which control field applied to the system qubits.
Quantum optimal control of photoelectron spectra and angular distributions
NASA Astrophysics Data System (ADS)
Goetz, R. Esteban; Karamatskou, Antonia; Santra, Robin; Koch, Christiane P.
2016-01-01
Photoelectron spectra and photoelectron angular distributions obtained in photoionization reveal important information on, e.g., charge transfer or hole coherence in the parent ion. Here we show that optimal control of the underlying quantum dynamics can be used to enhance desired features in the photoelectron spectra and angular distributions. To this end, we combine Krotov's method for optimal control theory with the time-dependent configuration interaction singles formalism and a splitting approach to calculate photoelectron spectra and angular distributions. The optimization target can account for specific desired properties in the photoelectron angular distribution alone, in the photoelectron spectrum, or in both. We demonstrate the method for hydrogen and then apply it to argon under strong XUV radiation, maximizing the difference of emission into the upper and lower hemispheres, in order to realize directed electron emission in the XUV regime.
Optimal control of systems with intermediate phase constraints
Kirichenko, S.B.
1995-03-01
In this paper, we derive necessary conditions of minimum for the general optimal control problem with the following characteristics: the trajectory is corrected at intermediate time instants using matching relationships; the system dynamics may vary in each time interval; the optimand functional and the functional constraints depend on the intermediate time instants, the momenta, and the phase coordinates of the trajectories. The result is derived by the methods of modern optimization theory and nonsmooth analysis. It is presented in the form of a maximum principle. The specific solution scheme for this problem has been developed in greater detail elsewhere for systems of the form x{sub i}={line_integral}{sub i}(t, x{sub i}). Much of the previous manipulations and results on the structure of the conjugate cone and the form of the directional derivatives are used also in this paper. This is legitimate because the optimized parameters and controls are independent.
Optimal Control of a Parabolic Equation with Dynamic Boundary Condition
Hoemberg, D. Krumbiegel, K.; Rehberg, J.
2013-02-15
We investigate a control problem for the heat equation. The goal is to find an optimal heat transfer coefficient in the dynamic boundary condition such that a desired temperature distribution at the boundary is adhered. To this end we consider a function space setting in which the heat flux across the boundary is forced to be an L{sup p} function with respect to the surface measure, which in turn implies higher regularity for the time derivative of temperature. We show that the corresponding elliptic operator generates a strongly continuous semigroup of contractions and apply the concept of maximal parabolic regularity. This allows to show the existence of an optimal control and the derivation of necessary and sufficient optimality conditions.
Learning the Optimal Control of Coordinated Eye and Head Movements
Saeb, Sohrab; Weber, Cornelius; Triesch, Jochen
2011-01-01
Various optimality principles have been proposed to explain the characteristics of coordinated eye and head movements during visual orienting behavior. At the same time, researchers have suggested several neural models to underly the generation of saccades, but these do not include online learning as a mechanism of optimization. Here, we suggest an open-loop neural controller with a local adaptation mechanism that minimizes a proposed cost function. Simulations show that the characteristics of coordinated eye and head movements generated by this model match the experimental data in many aspects, including the relationship between amplitude, duration and peak velocity in head-restrained and the relative contribution of eye and head to the total gaze shift in head-free conditions. Our model is a first step towards bringing together an optimality principle and an incremental local learning mechanism into a unified control scheme for coordinated eye and head movements. PMID:22072953
Stochastic Maximum Principle for Optimal Control of SPDEs
Fuhrman, Marco; Hu, Ying; Tessitore, Gianmario
2013-10-15
We prove a version of the maximum principle, in the sense of Pontryagin, for the optimal control of a stochastic partial differential equation driven by a finite dimensional Wiener process. The equation is formulated in a semi-abstract form that allows direct applications to a large class of controlled stochastic parabolic equations. We allow for a diffusion coefficient dependent on the control parameter, and the space of control actions is general, so that in particular we need to introduce two adjoint processes. The second adjoint process takes values in a suitable space of operators on L{sup 4}.
Health benefit modelling and optimization of vehicular pollution control strategies
NASA Astrophysics Data System (ADS)
Sonawane, Nayan V.; Patil, Rashmi S.; Sethi, Virendra
2012-12-01
This study asserts that the evaluation of pollution reduction strategies should be approached on the basis of health benefits. The framework presented could be used for decision making on the basis of cost effectiveness when the strategies are applied concurrently. Several vehicular pollution control strategies have been proposed in literature for effective management of urban air pollution. The effectiveness of these strategies has been mostly studied as a one at a time approach on the basis of change in pollution concentration. The adequacy and practicality of such an approach is studied in the present work. Also, the assessment of respective benefits of these strategies has been carried out when they are implemented simultaneously. An integrated model has been developed which can be used as a tool for optimal prioritization of various pollution management strategies. The model estimates health benefits associated with specific control strategies. ISC-AERMOD View has been used to provide the cause-effect relation between control options and change in ambient air quality. BenMAP, developed by U.S. EPA, has been applied for estimation of health and economic benefits associated with various management strategies. Valuation of health benefits has been done for impact indicators of premature mortality, hospital admissions and respiratory syndrome. An optimization model has been developed to maximize overall social benefits with determination of optimized percentage implementations for multiple strategies. The model has been applied for sub-urban region of Mumbai city for vehicular sector. Several control scenarios have been considered like revised emission standards, electric, CNG, LPG and hybrid vehicles. Reduction in concentration and resultant health benefits for the pollutants CO, NOx and particulate matter are estimated for different control scenarios. Finally, an optimization model has been applied to determine optimized percentage implementation of specific
Improved Sensitivity Relations in State Constrained Optimal Control
Bettiol, Piernicola; Frankowska, Hélène; Vinter, Richard B.
2015-04-15
Sensitivity relations in optimal control provide an interpretation of the costate trajectory and the Hamiltonian, evaluated along an optimal trajectory, in terms of gradients of the value function. While sensitivity relations are a straightforward consequence of standard transversality conditions for state constraint free optimal control problems formulated in terms of control-dependent differential equations with smooth data, their verification for problems with either pathwise state constraints, nonsmooth data, or for problems where the dynamic constraint takes the form of a differential inclusion, requires careful analysis. In this paper we establish validity of both ‘full’ and ‘partial’ sensitivity relations for an adjoint state of the maximum principle, for optimal control problems with pathwise state constraints, where the underlying control system is described by a differential inclusion. The partial sensitivity relation interprets the costate in terms of partial Clarke subgradients of the value function with respect to the state variable, while the full sensitivity relation interprets the couple, comprising the costate and Hamiltonian, as the Clarke subgradient of the value function with respect to both time and state variables. These relations are distinct because, for nonsmooth data, the partial Clarke subdifferential does not coincide with the projection of the (full) Clarke subdifferential on the relevant coordinate space. We show for the first time (even for problems without state constraints) that a costate trajectory can be chosen to satisfy the partial and full sensitivity relations simultaneously. The partial sensitivity relation in this paper is new for state constraint problems, while the full sensitivity relation improves on earlier results in the literature (for optimal control problems formulated in terms of Lipschitz continuous multifunctions), because a less restrictive inward pointing hypothesis is invoked in the proof, and because
Optimal control by least squares support vector machines.
Suykens, J A; Vandewalle, J; De Moor, B
2001-01-01
Support vector machines have been very successful in pattern recognition and function estimation problems. In this paper we introduce the use of least squares support vector machines (LS-SVM's) for the optimal control of nonlinear systems. Linear and neural full static state feedback controllers are considered. The problem is formulated in such a way that it incorporates the N-stage optimal control problem as well as a least squares support vector machine approach for mapping the state space into the action space. The solution is characterized by a set of nonlinear equations. An alternative formulation as a constrained nonlinear optimization problem in less unknowns is given, together with a method for imposing local stability in the LS-SVM control scheme. The results are discussed for support vector machines with radial basis function kernel. Advantages of LS-SVM control are that no number of hidden units has to be determined for the controller and that no centers have to be specified for the Gaussian kernels when applying Mercer's condition. The curse of dimensionality is avoided in comparison with defining a regular grid for the centers in classical radial basis function networks. This is at the expense of taking the trajectory of state variables as additional unknowns in the optimization problem, while classical neural network approaches typically lead to parametric optimization problems. In the SVM methodology the number of unknowns equals the number of training data, while in the primal space the number of unknowns can be infinite dimensional. The method is illustrated both on stabilization and tracking problems including examples on swinging up an inverted pendulum with local stabilization at the endpoint and a tracking problem for a ball and beam system.
Optimal control of charge transfer for slow H+ + D collisions with shaped laser pulses.
Zhang, Wei; Shu, Chuan-Cun; Ho, Tak-San; Rabitz, Herschel; Cong, Shu-Lin
2014-03-01
We show that optimally shaped laser pulses can beneficially influence charge transfer in slow H(+)+D collisions. Time-dependent wave packet optimal control simulations are performed based on a two-state adiabatic Hamiltonian. Optimal control is performed using either an adaptive or a fixed target to obtain the desired laser control field. In the adaptive target scheme, the target state is updated according to the renormalized fragmentary yield in the exit channel throughout the optimization process. In the fixed target scheme, the target state in the exit channel is a normalized outgoing Gaussian wave packet located at a large internuclear separation. Both approaches produced excellent optimal outcomes, far exceeding that achieved in the field-free collisional charge transfer. The adaptive target scheme proves to be more efficient, and often with complex final wave packet. In contrast, the fixed target scheme, although more slowly convergent, is found to produce high fidelity for the desired target wave packet. The control mechanism in both cases utilizes bound vibrational states of the transient HD(+) complex.
Optimal control of charge transfer for slow H+ + D collisions with shaped laser pulses
NASA Astrophysics Data System (ADS)
Zhang, Wei; Shu, Chuan-Cun; Ho, Tak-San; Rabitz, Herschel; Cong, Shu-Lin
2014-03-01
We show that optimally shaped laser pulses can beneficially influence charge transfer in slow H++D collisions. Time-dependent wave packet optimal control simulations are performed based on a two-state adiabatic Hamiltonian. Optimal control is performed using either an adaptive or a fixed target to obtain the desired laser control field. In the adaptive target scheme, the target state is updated according to the renormalized fragmentary yield in the exit channel throughout the optimization process. In the fixed target scheme, the target state in the exit channel is a normalized outgoing Gaussian wave packet located at a large internuclear separation. Both approaches produced excellent optimal outcomes, far exceeding that achieved in the field-free collisional charge transfer. The adaptive target scheme proves to be more efficient, and often with complex final wave packet. In contrast, the fixed target scheme, although more slowly convergent, is found to produce high fidelity for the desired target wave packet. The control mechanism in both cases utilizes bound vibrational states of the transient HD+ complex.
Optimal control of molecular motion expressed through quantum fluid dynamics
NASA Astrophysics Data System (ADS)
Dey, Bijoy K.; Rabitz, Herschel; Askar, Attila
2000-04-01
A quantum fluid-dynamic (QFD) control formulation is presented for optimally manipulating atomic and molecular systems. In QFD the control quantum system is expressed in terms of the probability density ρ and the quantum current j. This choice of variables is motivated by the generally expected slowly varying spatial-temporal dependence of the fluid-dynamical variables. The QFD approach is illustrated for manipulation of the ground electronic state dynamics of HCl induced by an external electric field.
Discover for Yourself: An Optimal Control Model in Insect Colonies
ERIC Educational Resources Information Center
Winkel, Brian
2013-01-01
We describe the enlightening path of self-discovery afforded to the teacher of undergraduate mathematics. This is demonstrated as we find and develop background material on an application of optimal control theory to model the evolutionary strategy of an insect colony to produce the maximum number of queen or reproducer insects in the colony at…
A Connection between Singular Stochastic Control and Optimal Stopping
Espen Benth, Fred Reikvam, Kristin
2003-12-15
We show that the value function of a singular stochastic control problem is equal to the integral of the value function of an associated optimal stopping problem. The connection is proved for a general class of diffusions using the method of viscosity solutions.
A Control Theory Solution to Optimal Faculty Staffing.
ERIC Educational Resources Information Center
Rowe, Stephen M.; And Others
This study investigates the resource allocation problem of faculty hiring and promotion patterns using the techniques of optimal control theory. The mathematical structure of an academic faculty is described by a linear dynamic model whose parameters were estimated from actual data by two different techniques. The principal characteristics of the…
Quasivelocities and Optimal Control for underactuated Mechanical Systems
NASA Astrophysics Data System (ADS)
Colombo, L.; de Diego, D. Martín
2010-07-01
This paper is concerned with the application of the theory of quasivelocities for optimal control for underactuated mechanical systems. Using this theory, we convert the original problem in a variational second-order lagrangian system subjected to constraints. The equations of motion are geometrically derived using an adaptation of the classical Skinner and Rusk formalism.
The Relationship between Pupil Control Ideology and Academic Optimism
ERIC Educational Resources Information Center
Gilbert, Michael J.
2012-01-01
This study investigates the relationship between pupil control ideology and academic optimism. Information was generated through responses to a questionnaire emailed to teachers in two school districts in Central New Jersey. The districts were categorized GH, as determined by the State's district factor grouping. The research concludes that…
Optimizing a mobile robot control system using GPU acceleration
NASA Astrophysics Data System (ADS)
Tuck, Nat; McGuinness, Michael; Martin, Fred
2012-01-01
This paper describes our attempt to optimize a robot control program for the Intelligent Ground Vehicle Competition (IGVC) by running computationally intensive portions of the system on a commodity graphics processing unit (GPU). The IGVC Autonomous Challenge requires a control program that performs a number of different computationally intensive tasks ranging from computer vision to path planning. For the 2011 competition our Robot Operating System (ROS) based control system would not run comfortably on the multicore CPU on our custom robot platform. The process of profiling the ROS control program and selecting appropriate modules for porting to run on a GPU is described. A GPU-targeting compiler, Bacon, is used to speed up development and help optimize the ported modules. The impact of the ported modules on overall performance is discussed. We conclude that GPU optimization can free a significant amount of CPU resources with minimal effort for expensive user-written code, but that replacing heavily-optimized library functions is more difficult, and a much less efficient use of time.
Neural network learning of optimal Kalman prediction and control.
Linsker, Ralph
2008-11-01
Although there are many neural network (NN) algorithms for prediction and for control, and although methods for optimal estimation (including filtering and prediction) and for optimal control in linear systems were provided by Kalman in 1960 (with nonlinear extensions since then), there has been, to my knowledge, no NN algorithm that learns either Kalman prediction or Kalman control (apart from the special case of stationary control). Here we show how optimal Kalman prediction and control (KPC), as well as system identification, can be learned and executed by a recurrent neural network composed of linear-response nodes, using as input only a stream of noisy measurement data. The requirements of KPC appear to impose significant constraints on the allowed NN circuitry and signal flows. The NN architecture implied by these constraints bears certain resemblances to the local-circuit architecture of mammalian cerebral cortex. We discuss these resemblances, as well as caveats that limit our current ability to draw inferences for biological function. It has been suggested that the local cortical circuit (LCC) architecture may perform core functions (as yet unknown) that underlie sensory, motor, and other cortical processing. It is reasonable to conjecture that such functions may include prediction, the estimation or inference of missing or noisy sensory data, and the goal-driven generation of control signals. The resemblances found between the KPC NN architecture and that of the LCC are consistent with this conjecture.
Peer Victimization and Effortful Control: Relations to School Engagement and Academic Achievement
ERIC Educational Resources Information Center
Iyer, Roopa V.; Kochenderfer-Ladd, Becky; Eisenberg, Nancy; Thompson, Marilyn
2010-01-01
The relations among peer victimization, effortful control, school engagement, and academic achievement were examined in a group of 390 (212 boys and 178 girls) racially diverse (38.20% Latino and 46.70% White) 6- to 10-year-old children. Specifically, a multimethod, multi-informant approach was used in which data were gathered using self-report,…
Effortful Control and Impulsivity as Concurrent and Longitudinal Predictors of Academic Achievement
ERIC Educational Resources Information Center
Valiente, Carlos; Eisenberg, Nancy; Spinrad, Tracy L.; Haugen, Rg; Thompson, Marilyn S.; Kupfer, Anne
2013-01-01
The goal of this study was to test if both effortful control (EC) and impulsivity, a reactive index of temperament, uniquely predict adolescents' academic achievement, concurrently and longitudinally (Time 1: "N" = 168, X-bar[subscript age] = 12 years). At Time 1, parents and teachers reported on students' EC and impulsivity.…
ERIC Educational Resources Information Center
Stupnisky, Robert H.; Perry, Raymond P.; Hall, Nathan C.; Guay, Frederic
2012-01-01
The aim of the present study was to examine the intraindividual level and instability of perceived academic control (PC) among first-year college students, and their predictive effects on academic achievement. Two studies were conducted measuring situational (state) PC on different schedules: Study 1 (N = 242) five times over a 6-month period and…
On-Line Tutoring for Math Achievement Testing: A Controlled Evaluation
ERIC Educational Resources Information Center
Beal, Carole R.; Walles, Rena; Arroyo, Ivon; Woolf, Beverly P.
2007-01-01
We report the results of a controlled evaluation of an interactive on-line tutoring system for high school math achievement test problem solving. High school students (N = 202) completed a math pre-test and were then assigned by teachers to receive interactive on-line multimedia tutoring or their regular classroom instruction. The on-line tutored…
ERIC Educational Resources Information Center
Shih, Shu-Shen
2013-01-01
The author attempted to explore potential antecedents of achievement goals and relations of teacher and parental autonomy support versus psychological control to Taiwanese adolescents' perfectionistic tendencies. A total of 512 eighth-grade students completed self-reported questionnaires assessing variables of interest. Results indicated that…
ERIC Educational Resources Information Center
Early, Diane; Barrett, Marty
This 2-year study examined the relative potency of locus of control (LOC) and motivational orientation (MO) as predictors of standardized achievement scores and learned helplessness. Also tested was the prediction that children with an extrinsic MO would be prone to adopt an external LOC over time. In the first year of the study, subjects were 158…
ERIC Educational Resources Information Center
Gómez, David Maximiliano; Jiménez, Abelino; Bobadilla, Roberto; Reyes, Cristián; Dartnell, Pablo
2015-01-01
Individual differences in inhibitory control have been shown to relate to general mathematics achievement, but whether this relation varies for specific areas within mathematics is a question that remains open. Here, we evaluate if inhibitory processes play a specific role in the particular case of fraction comparison, where learners must ignore…
Wayne Penrod; David Moyeda
2003-07-01
The objective of this project is to demonstrate the use of an Integrated Combustion Optimization System to achieve NO{sub x} emissions levels in the range of 0.15 to 0.22 lb/MMBtu while simultaneously enabling increased power output. The project consists of the integration of low-NO{sub x} burners and advanced overfire air technology with various process measurement and control devices on the Holcomb Station Unit 1 boiler. The project includes the use of sophisticated neural networks or other artificial intelligence technologies and complex software that can optimize several operating parameters, including NO{sub x} emissions, boiler efficiency, and CO emissions. The program is being performed in three phases. In Phase I, the boiler is being equipped with sensors that can be used to monitor furnace conditions and coal flow to permit improvements in boiler operation. In Phase II, the boiler will be equipped with burner modifications designed to reduce NO{sub x} emissions and automated coal flow dampers to permit on-line fuel balancing. In Phase III, the boiler will be equipped with an overfire air system to permit deep reductions in NO{sub x} emissions to be achieved. Integration of the overfire air system with the improvements made in Phases I and II will permit optimization of the boiler performance, output, and emissions. During this reporting period, efforts were focused on completion of Phase I and Phase II activities. The low-NO{sub x} burner modifications, the coal flow dampers, and the coal flow monitoring system were procured and installed during a boiler outage in March 2003. During this reporting period, optimization tests were performed to evaluate system performance and identify optimum operating conditions for the installed equipment. The overfire air system process design activities and preliminary engineering design were completed.
A model based technique for the design of flight directors. [optimal control models
NASA Technical Reports Server (NTRS)
Levison, W. H.
1973-01-01
A new technique for designing flight directors is discussed. This technique uses the optimal-control pilot/vehicle model to determine the appropriate control strategy. The dynamics of this control strategy are then incorporated into the director control laws, thereby enabling the pilot to operate at a significantly lower workload. A preliminary design of a control director for maintaining a STOL vehicle on the approach path in the presence of random air turbulence is evaluated. By selecting model parameters in terms of allowable path deviations and pilot workload levels, a set of director laws is achieved which allows improved system performance at reduced workload levels. The pilot acts essentially as a proportional controller with regard to the director signals, and control motions are compatible with those appropriate to status-only displays.
Optimal control analysis of the dynamic growth behavior of microorganisms.
Mandli, Aravinda R; Modak, Jayant M
2014-12-01
Understanding the growth behavior of microorganisms using modeling and optimization techniques is an active area of research in the fields of biochemical engineering and systems biology. In this paper, we propose a general modeling framework, based on Monod model, to model the growth of microorganisms. Utilizing the general framework, we formulate an optimal control problem with the objective of maximizing a long-term cellular goal and solve it analytically under various constraints for the growth of microorganisms in a two substrate batch environment. We investigate the relation between long term and short term cellular goals and show that the objective of maximizing cellular concentration at a fixed final time is equivalent to maximization of instantaneous growth rate. We then establish the mathematical connection between the generalized framework and optimal and cybernetic modeling frameworks and derive generalized governing dynamic equations for optimal and cybernetic models. We finally illustrate the influence of various constraints in the cybernetic modeling framework on the optimal growth behavior of microorganisms by solving several dynamic optimization problems using genetic algorithms.
Park, Wan Beom; Cho, Joo-Youn; Park, Sang-In; Kim, Eun Jung; Yoon, Seonghae; Yoon, Seo Hyun; Lee, Jeong-Ok; Koh, Youngil; Song, Kyoung-Ho; Choe, Pyoeng Gyun; Yu, Kyung-Sang; Kim, Eu Suk; Bang, Su Mi; Kim, Nam Joong; Kim, Inho; Oh, Myoung-Don; Kim, Hong Bin; Song, Sang Hoon
2016-07-01
Few data are available on whether adjusting the dose of posaconazole syrup is effective in patients receiving anti-cancer chemotherapy. The aim of this prospective study was to analyse the impact of increasing the frequency of posaconazole administration on optimal plasma concentrations in adult patients with haematological malignancy. A total of 133 adult patients receiving chemotherapy for acute myeloid leukaemia or myelodysplastic syndrome who received posaconazole syrup 200 mg three times daily for fungal prophylaxis were enrolled in this study. Drug trough levels were measured by liquid chromatography-tandem mass spectrometry. In 20.2% of patients (23/114) the steady-state concentration of posaconazole was suboptimal (<500 ng/mL) on Day 8. In these patients, the frequency of posaconazole administration was increased to 200 mg four times daily. On Day 15, the median posaconazole concentration was significantly increased from 368 ng/mL [interquartile range (IQR), 247-403 ng/mL] to 548 ng/mL (IQR, 424-887 ng/mL) (P = 0.0003). The median increase in posaconazole concentration was 251 ng/mL (IQR, 93-517 ng/mL). Among the patients with initially suboptimal levels, 79% achieved the optimal level unless the steady-state level was <200 ng/mL. This study shows that increasing the administration frequency of posaconazole syrup is effective for achieving optimal levels in patients with haematological malignancy undergoing chemotherapy. PMID:27234674
Multi Objective Controller Design for Linear System via Optimal Interpolation
NASA Technical Reports Server (NTRS)
Ozbay, Hitay
1996-01-01
We propose a methodology for the design of a controller which satisfies a set of closed-loop objectives simultaneously. The set of objectives consists of: (1) pole placement, (2) decoupled command tracking of step inputs at steady-state, and (3) minimization of step response transients with respect to envelope specifications. We first obtain a characterization of all controllers placing the closed-loop poles in a prescribed region of the complex plane. In this characterization, the free parameter matrix Q(s) is to be determined to attain objectives (2) and (3). Objective (2) is expressed as determining a Pareto optimal solution to a vector valued optimization problem. The solution of this problem is obtained by transforming it to a scalar convex optimization problem. This solution determines Q(O) and the remaining freedom in choosing Q(s) is used to satisfy objective (3). We write Q(s) = (l/v(s))bar-Q(s) for a prescribed polynomial v(s). Bar-Q(s) is a polynomial matrix which is arbitrary except that Q(O) and the order of bar-Q(s) are fixed. Obeying these constraints bar-Q(s) is now to be 'shaped' to minimize the step response characteristics of specific input/output pairs according to the maximum envelope violations. This problem is expressed as a vector valued optimization problem using the concept of Pareto optimality. We then investigate a scalar optimization problem associated with this vector valued problem and show that it is convex. The organization of the report is as follows. The next section includes some definitions and preliminary lemmas. We then give the problem statement which is followed by a section including a detailed development of the design procedure. We then consider an aircraft control example. The last section gives some concluding remarks. The Appendix includes the proofs of technical lemmas, printouts of computer programs, and figures.
NASA Technical Reports Server (NTRS)
Newson, J. R.
1979-01-01
The results of optimal control theory are used to synthesize a feedback filter. The feedback filter is used to force the output of the filtered frequency response to match that of a desired optimal frequency response over a finite frequency range. This matching is accomplished by employing a nonlinear programing algorithm to search for the coefficients of the feedback filter that minimize the error between the optimal frequency response and the filtered frequency response. The method is applied to the synthesis of an active flutter-suppression control law for an aeroelastic wind-tunnel model. It is shown that the resulting control law suppresses flutter over a wide range of subsonic Mach numbers. This is a promising method for synthesizing practical control laws using the results of optimal control theory.
Optimal control in a model of malaria with differential susceptibility
NASA Astrophysics Data System (ADS)
Hincapié, Doracelly; Ospina, Juan
2014-06-01
A malaria model with differential susceptibility is analyzed using the optimal control technique. In the model the human population is classified as susceptible, infected and recovered. Susceptibility is assumed dependent on genetic, physiological, or social characteristics that vary between individuals. The model is described by a system of differential equations that relate the human and vector populations, so that the infection is transmitted to humans by vectors, and the infection is transmitted to vectors by humans. The model considered is analyzed using the optimal control method when the control consists in using of insecticide-treated nets and educational campaigns; and the optimality criterion is to minimize the number of infected humans, while keeping the cost as low as is possible. One first goal is to determine the effects of differential susceptibility in the proposed control mechanism; and the second goal is to determine the algebraic form of the basic reproductive number of the model. All computations are performed using computer algebra, specifically Maple. It is claimed that the analytical results obtained are important for the design and implementation of control measures for malaria. It is suggested some future investigations such as the application of the method to other vector-borne diseases such as dengue or yellow fever; and also it is suggested the possible application of free software of computer algebra like Maxima.
Optimal control of systems with capacity: Related noises
NASA Technical Reports Server (NTRS)
Ruan, Milfang; Choudhury, Ajit K.
1991-01-01
In the ordinary theory of optimal control (LQR and Kalman filter), the variances of the actuators and the sensors are assumed to be known (not related to the capacities of the devices). This assumption is not true in practice. Generally, a device with greater capacity to exert actuating forces and a sensor capable of sensing greater sensing range will generate noise of greater power spectral density. When the ordinary theory of optimal control is used to estimate the errors of the outputs in such cases it will lead to faulty results, because the capacities of such devices are unknown before the system is designed. The performance of the system designed by the ordinary theory will not be optimal as the variances of the sensors and the actuators are neither known nor constant. The interaction between the control system and structure could be serious because the ordinary method will lead to greater feedback (Kalman gain) matrices. Methods which can optimize the performance of systems when noises of the actuators and the sensors are related to their capacities are developed. These methods will result in smaller feedback (Kalman gain) matrix.
Optimal Load Control via Frequency Measurement and Neighborhood Area Communication
Zhao, CH; Topcu, U; Low, SH
2013-11-01
We propose a decentralized optimal load control scheme that provides contingency reserve in the presence of sudden generation drop. The scheme takes advantage of flexibility of frequency responsive loads and neighborhood area communication to solve an optimal load control problem that balances load and generation while minimizing end-use disutility of participating in load control. Local frequency measurements enable individual loads to estimate the total mismatch between load and generation. Neighborhood area communication helps mitigate effects of inconsistencies in the local estimates due to frequency measurement noise. Case studies show that the proposed scheme can balance load with generation and restore the frequency within seconds of time after a generation drop, even when the loads use a highly simplified power system model in their algorithms. We also investigate tradeoffs between the amount of communication and the performance of the proposed scheme through simulation-based experiments.
The population model of bone remodelling employed the optimal control.
Moroz, Adam
2012-11-01
Several models have been developed in recent years which apply population dynamics methods to describe the mechanisms of bone remodelling. This study incorporates the population kinetics model of bone turnover (including the osteocyte loop regulation) with the optimal control technique. Model simulations have been performed with a wide range of rate parameters using the Monte Carlo method. The regression method has also been used to investigate the interdependence of the location of equilibrium and the characteristics of the equilibrium/relaxation time on the rate parameters employed. The dynamic optimal control outlook for the regulation of bone remodelling processes, in the context of the osteocyte-control population model, has been discussed. Optimisation criteria have been formulated from the perspective of the energetic and metabolic losses in the tissue, with respect to the performance of the bone multicellular unit.
Optimal control of Formula One car energy recovery systems
NASA Astrophysics Data System (ADS)
Limebeer, D. J. N.; Perantoni, G.; Rao, A. V.
2014-10-01
The utility of orthogonal collocation methods in the solution of optimal control problems relating to Formula One racing is demonstrated. These methods can be used to optimise driver controls such as the steering, braking and throttle usage, and to optimise vehicle parameters such as the aerodynamic down force and mass distributions. Of particular interest is the optimal usage of energy recovery systems (ERSs). Contemporary kinetic energy recovery systems are studied and compared with future hybrid kinetic and thermal/heat ERSs known as ERS-K and ERS-H, respectively. It is demonstrated that these systems, when properly controlled, can produce contemporary lap time using approximately two-thirds of the fuel required by earlier generation (2013 and prior) vehicles.
Operational optimization and real-time control of fuel-cell systems
NASA Astrophysics Data System (ADS)
Hasikos, J.; Sarimveis, H.; Zervas, P. L.; Markatos, N. C.
Fuel cells is a rapidly evolving technology with applications in many industries including transportation, and both portable and stationary power generation. The viability, efficiency and robustness of fuel-cell systems depend strongly on optimization and control of their operation. This paper presents the development of an integrated optimization and control tool for Proton Exchange Membrane Fuel-Cell (PEMFC) systems. Using a detailed simulation model, a database is generated first, which contains steady-state values of the manipulated and controlled variables over the full operational range of the fuel-cell system. In a second step, the database is utilized for producing Radial Basis Function (RBF) neural network "meta-models". In the third step, a Non-Linear Programming Problem (NLP) is formulated, that takes into account the constraints and limitations of the system and minimizes the consumption of hydrogen, for a given value of power demand. Based on the formulation and solution of the NLP problem, a look-up table is developed, containing the optimal values of the system variables for any possible value of power demand. In the last step, a Model Predictive Control (MPC) methodology is designed, for the optimal control of the system response to successive sep-point changes of power demand. The efficiency of the produced MPC system is illustrated through a number of simulations, which show that a successful dynamic closed-loop behaviour can be achieved, while at the same time the consumption of hydrogen is minimized.
The controlled growth method - A tool for structural optimization
NASA Technical Reports Server (NTRS)
Hajela, P.; Sobieszczanski-Sobieski, J.
1981-01-01
An adaptive design variable linking scheme in a NLP based optimization algorithm is proposed and evaluated for feasibility of application. The present scheme, based on an intuitive effectiveness measure for each variable, differs from existing methodology in that a single dominant variable controls the growth of all others in a prescribed optimization cycle. The proposed method is implemented for truss assemblies and a wing box structure for stress, displacement and frequency constraints. Substantial reduction in computational time, even more so for structures under multiple load conditions, coupled with a minimal accompanying loss in accuracy, vindicates the algorithm.
Solving inverse problems of identification type by optimal control methods
Lenhart, S.; Protopopescu, V.; Jiongmin Yong
1997-06-01
Inverse problems of identification type for nonlinear equations are considered within the framework of optimal control theory. The rigorous solution of any particular problem depends on the functional setting, type of equation, and unknown quantity (or quantities) to be determined. Here the authors present only the general articulations of the formalism. Compared to classical regularization methods (e.g. Tikhonov coupled with optimization schemes), their approach presents several advantages, namely: (i) a systematic procedure to solve inverse problems of identification type; (ii) an explicit expression for the approximations of the solution; and (iii) a convenient numerical solution of these approximations.
Efficient algorithms for the laboratory discovery of optimal quantum controls.
Turinici, Gabriel; Le Bris, Claude; Rabitz, Herschel
2004-01-01
The laboratory closed-loop optimal control of quantum phenomena, expressed as minimizing a suitable cost functional, is currently implemented through an optimization algorithm coupled to the experimental apparatus. In practice, the most commonly used search algorithms are variants of genetic algorithms. As an alternative choice, a direct search deterministic algorithm is proposed in this paper. For the simple simulations studied here, it outperforms the existing approaches. An additional algorithm is introduced in order to reveal some properties of the cost functional landscape. PMID:15324201
Role of Parenting Style in Achieving Metabolic Control in Adolescents With Type 1 Diabetes
Shorer, Maayan; David, Ravit; Schoenberg-Taz, Michal; Levavi-Lavi, Ifat; Phillip, Moshe; Meyerovitch, Joseph
2011-01-01
OBJECTIVE To examine the role of parenting style in achieving metabolic control and treatment adherence in adolescents with type 1 diabetes. RESEARCH DESIGN AND METHODS Parents of 100 adolescents with type 1 diabetes completed assessments of their parenting style and sense of helplessness. Parents and patients rated patient adherence to the treatment regimen. Glycemic control was evaluated by HbA1c values. RESULTS An authoritative paternal parenting style predicted better glycemic control and adherence in the child; a permissive maternal parenting style predicted poor adherence. A higher sense of helplessness in both parents predicted worse glycemic control and lesser adherence to treatment. Parental sense of helplessness was a significant predictor of diabetes control after correcting for other confounders (patient age, sex, and treatment method). CONCLUSIONS An authoritative nonhelpless parenting style is associated with better diabetes control in adolescents. Paternal involvement is important in adolescent diabetes management. These results have implications for psychological interventions. PMID:21788643
Pojić, Milica; Rakić, Dušan; Lazić, Zivorad
2015-01-01
A chemometric approach was applied for the optimization of the robustness of the NIRS method for wheat quality control. Due to the high number of experimental (n=6) and response variables to be studied (n=7) the optimization experiment was divided into two stages: screening stage in order to evaluate which of the considered variables were significant, and optimization stage to optimize the identified factors in the previously selected experimental domain. The significant variables were identified by using fractional factorial experimental design, whilst Box-Wilson rotatable central composite design (CCRD) was run to obtain the optimal values for the significant variables. The measured responses included: moisture, protein and wet gluten content, Zeleny sedimentation value and deformation energy. In order to achieve the minimal variation in responses, the optimal factor settings were found by minimizing the propagation of error (POE). The simultaneous optimization of factors was conducted by desirability function. The highest desirability of 87.63% was accomplished by setting up experimental conditions as follows: 19.9°C for sample temperature, 19.3°C for ambient temperature and 240V for instrument voltage.
Pojić, Milica; Rakić, Dušan; Lazić, Zivorad
2015-01-01
A chemometric approach was applied for the optimization of the robustness of the NIRS method for wheat quality control. Due to the high number of experimental (n=6) and response variables to be studied (n=7) the optimization experiment was divided into two stages: screening stage in order to evaluate which of the considered variables were significant, and optimization stage to optimize the identified factors in the previously selected experimental domain. The significant variables were identified by using fractional factorial experimental design, whilst Box-Wilson rotatable central composite design (CCRD) was run to obtain the optimal values for the significant variables. The measured responses included: moisture, protein and wet gluten content, Zeleny sedimentation value and deformation energy. In order to achieve the minimal variation in responses, the optimal factor settings were found by minimizing the propagation of error (POE). The simultaneous optimization of factors was conducted by desirability function. The highest desirability of 87.63% was accomplished by setting up experimental conditions as follows: 19.9°C for sample temperature, 19.3°C for ambient temperature and 240V for instrument voltage. PMID:25281098
Multiobjective Optimization of Low-Energy Trajectories Using Optimal Control on Dynamical Channels
NASA Technical Reports Server (NTRS)
Coffee, Thomas M.; Anderson, Rodney L.; Lo, Martin W.
2011-01-01
We introduce a computational method to design efficient low-energy trajectories by extracting initial solutions from dynamical channels formed by invariant manifolds, and improving these solutions through variational optimal control. We consider trajectories connecting two unstable periodic orbits in the circular restricted 3-body problem (CR3BP). Our method leverages dynamical channels to generate a range of solutions, and approximates the areto front for impulse and time of flight through a multiobjective optimization of these solutions based on primer vector theory. We demonstrate the application of our method to a libration orbit transfer in the Earth-Moon system.
Optimal dynamic control of invasions: applying a systematic conservation approach.
Adams, Vanessa M; Setterfield, Samantha A
2015-06-01
The social, economic, and environmental impacts of invasive plants are well recognized. However, these variable impacts are rarely accounted for in the spatial prioritization of funding for weed management. We examine how current spatially explicit prioritization methods can be extended to identify optimal budget allocations to both eradication and control measures of invasive species to minimize the costs and likelihood of invasion. Our framework extends recent approaches to systematic prioritization of weed management to account for multiple values that are threatened by weed invasions with a multi-year dynamic prioritization approach. We apply our method to the northern portion of the Daly catchment in the Northern Territory, which has significant conservation values that are threatened by gamba grass (Andropogon gayanus), a highly invasive species recognized by the Australian government as a Weed of National Significance (WONS). We interface Marxan, a widely applied conservation planning tool, with a dynamic biophysical model of gamba grass to optimally allocate funds to eradication and control programs under two budget scenarios comparing maximizing gain (MaxGain) and minimizing loss (MinLoss) optimization approaches. The prioritizations support previous findings that a MinLoss approach is a better strategy when threats are more spatially variable than conservation values. Over a 10-year simulation period, we find that a MinLoss approach reduces future infestations by ~8% compared to MaxGain in the constrained budget scenarios and ~12% in the unlimited budget scenarios. We find that due to the extensive current invasion and rapid rate of spread, allocating the annual budget to control efforts is more efficient than funding eradication efforts when there is a constrained budget. Under a constrained budget, applying the most efficient optimization scenario (control, minloss) reduces spread by ~27% compared to no control. Conversely, if the budget is unlimited it
Object Correlation and Maneuver Detection Using Optimal Control Performance Metrics
NASA Astrophysics Data System (ADS)
Holzinger, M.; Scheeres, D.
2010-09-01
Object correlation and maneuver detection are persistent problems in space surveillance and space object catalog maintenance. This paper demonstrates the utility of using quadratic trajectory control cost, an analog to the trajectory L2-norm in control, as a distance metric with which to both correlate object tracks and detect maneuvers using Uncorrelated Tracks (UCTs), real-time sensor measurement residuals, and prior state uncertainty. State and measurement uncertainty are incorporated into the computation, and distributions of optimal control usage are computed. Both UCT correlation as well as maneuver detection are demonstrated in several scenarios Potential avenues for future research and contributions are summarized.
Development of a digital adaptive optimal linear regulator flight controller
NASA Technical Reports Server (NTRS)
Berry, P.; Kaufman, H.
1975-01-01
Digital adaptive controllers have been proposed as a means for retaining uniform handling qualities over the flight envelope of a high-performance aircraft. Towards such an implementation, an explicit adaptive controller, which makes direct use of online parameter identification, has been developed and applied to the linearized lateral equations of motion for a typical fighter aircraft. The system is composed of an online weighted least-squares parameter identifier, a Kalman state filter, and a model following control law designed using optimal linear regulator theory. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for onboard implementation.
Control and optimization system and method for chemical looping processes
Lou, Xinsheng; Joshi, Abhinaya; Lei, Hao
2014-06-24
A control system for optimizing a chemical loop system includes one or more sensors for measuring one or more parameters in a chemical loop. The sensors are disposed on or in a conduit positioned in the chemical loop. The sensors generate one or more data signals representative of an amount of solids in the conduit. The control system includes a data acquisition system in communication with the sensors and a controller in communication with the data acquisition system. The data acquisition system receives the data signals and the controller generates the control signals. The controller is in communication with one or more valves positioned in the chemical loop. The valves are configured to regulate a flow of the solids through the chemical loop.
Control and optimization system and method for chemical looping processes
Lou, Xinsheng; Joshi, Abhinaya; Lei, Hao
2015-02-17
A control system for optimizing a chemical loop system includes one or more sensors for measuring one or more parameters in a chemical loop. The sensors are disposed on or in a conduit positioned in the chemical loop. The sensors generate one or more data signals representative of an amount of solids in the conduit. The control system includes a data acquisition system in communication with the sensors and a controller in communication with the data acquisition system. The data acquisition system receives the data signals and the controller generates the control signals. The controller is in communication with one or more valves positioned in the chemical loop. The valves are configured to regulate a flow of the solids through the chemical loop.
Optimal Control of Thermo--Fluid Phenomena in Variable Domains
NASA Astrophysics Data System (ADS)
Volkov, Oleg; Protas, Bartosz
2008-11-01
This presentation concerns our continued research on 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 variable boundaries. This problem is motivated by optimization of advanced welding techniques used in automotive manufacturing, where the goal is to determine an optimal heat input, so as to obtain a desired shape of the weld pool surface upon solidification. We argue that computation of sensitivities (gradients) in such free--boundary problems requires the use of the shape--differential calculus as a key ingredient. We also show that, with such tools available, the computational solution of the direct and inverse (optimization) problems can in fact be achieved in a similar manner and in a comparable computational time. Our presentation will address certain mathematical and computational aspects of the method. As an illustration we will consider the two--phase Stefan problem with contact point singularities where our approach allows us to obtain a thermodynamically consistent solution.
Optimal control of real ambient LED lighting powering
NASA Astrophysics Data System (ADS)
Marc, Gheorghe; Risteiu, Mircea; Ileana, Ioan; Olteanu, Emil
2015-02-01
The paper approaches the lighting optimization of industrial production areas, using the remote microcontroller command of lighting sources. The lighting of industrial production areas is stated by the Design and execution of building artificial lighting standard - NP 061- 02 that specifies the lighting level of working and of the neighbor area, in order to assure work comfortable condition and to avoid work accidents. As consequence, in production companies, particularly in those were the activity is in continuous flow, it is a great concern on an appropriate lighting but also on minimal energy consumption. The main achievement is the lighting optimization intending a uniform light flux over the working surface, with minimal energy consumption through the individual or group command of lighting sources, depending on the measurement of lighting level.
Control design variable linking for optimization of structural/control systems
NASA Technical Reports Server (NTRS)
Jin, Ik Min; Schmit, Lucien A.
1993-01-01
A method is presented to integrate the design space of structural/control system optimization problems in the case of linear state feedback control. Conventional structural sizing variables and elements of the feedback gain matrix are both treated as strictly independent design variables in optimization by extending design variable linking concepts to the control gains. Several approximation concepts including new control design variable linking schemes are used to formulate the integrated structural/control optimization problem as a sequence of explicit nonlinear mathematical programming problems. Examples which involve a variety of behavior constraints, including constraints on dynamic stability, damped frequencies, control effort, peak transient displacement, acceleration, and control force limits, are effectively solved by using the method presented.
Norris, Jade Eloise; Castronovo, Julie
2016-01-01
Much research has investigated the relationship between the Approximate Number System (ANS) and mathematical achievement, with continued debate surrounding the existence of such a link. The use of different stimulus displays may account for discrepancies in the findings. Indeed, closer scrutiny of the literature suggests that studies supporting a link between ANS acuity and mathematical achievement in adults have mostly measured the ANS using spatially intermixed displays (e.g. of blue and yellow dots), whereas those failing to replicate a link have primarily used spatially separated dot displays. The current study directly compared ANS acuity when using intermixed or separate dots, investigating how such methodological variation mediated the relationship between ANS acuity and mathematical achievement. ANS acuity was poorer and less reliable when measured with intermixed displays, with performance during both conditions related to inhibitory control. Crucially, mathematical achievement was significantly related to ANS accuracy difference (accuracy on congruent trials minus accuracy on incongruent trials) when measured with intermixed displays, but not with separate displays. The findings indicate that methodological variation affects ANS acuity outcomes, as well as the apparent relationship between the ANS and mathematical achievement. Moreover, the current study highlights the problem of low reliabilities of ANS measures. Further research is required to construct ANS measures with improved reliability, and to understand which processes may be responsible for the increased likelihood of finding a correlation between the ANS and mathematical achievement when using intermixed displays. PMID:27195749
NASA Astrophysics Data System (ADS)
Wang, Gang; Chen, Changzheng; Yu, Shenbo
2016-09-01
In this paper, the static output-feedback control problem of active suspension systems with information structure constraints is investigated. In order to simultaneously improve the ride comfort and stability, a half car model is used. Other constraints such as suspension deflection, actuator saturation, and controller constrained information are also considered. A novel static output-feedback design method based on the variable substitution is employed in the controller design. A single-step linear matrix inequality (LMI) optimization problem is solved to derive the initial feasible solution with a sparsity constraint. The initial infeasibility issue of the static output-feedback is resolved by using state-feedback information. Specifically, an optimization algorithm is proposed to search for less conservative results based on the feasible controller gain matrix. Finally, the validity of the designed controller for different road profiles is illustrated through numerical examples. The simulation results indicate that the optimized static output-feedback controller can achieve better suspension performances when compared with the feasible static output-feedback controller.
Vision-based stereo ranging as an optimal control problem
NASA Technical Reports Server (NTRS)
Menon, P. K. A.; Sridhar, B.; Chatterji, G. B.
1992-01-01
The recent interest in the use of machine vision for flight vehicle guidance is motivated by the need to automate the nap-of-the-earth flight regime of helicopters. Vision-based stereo ranging problem is cast as an optimal control problem in this paper. A quadratic performance index consisting of the integral of the error between observed image irradiances and those predicted by a Pade approximation of the correspondence hypothesis is then used to define an optimization problem. The necessary conditions for optimality yield a set of linear two-point boundary-value problems. These two-point boundary-value problems are solved in feedback form using a version of the backward sweep method. Application of the ranging algorithm is illustrated using a laboratory image pair.
ERIC Educational Resources Information Center
Honken, Nora B.; Ralston, Patricia A. S.
2013-01-01
This study investigated the relationship among lack of self-control, academic ability, and academic performance for a cohort of freshman engineering students who were, with a few exceptions, extremely high achievers in high school. Structural equation modeling analysis led to the conclusion that lack of self-control in high school, as measured by…
An alternate method for achieving temperature control in the -130 C to 75 C range
NASA Technical Reports Server (NTRS)
Johnson, Kenneth R.; Anderson, Mark R.; Lane, Robert W.; Cortez, Maximo G.
1992-01-01
Thermal vacuum testing often requires temperature control of chamber shrouds and heat exchangers within the -130 C to 75 C range. There are two conventional methods which are normally employed to achieve control through this intermediate temperature range: (1) single-pass flow where control is achieved by alternately pulsing hot gaseous nitrogen (GN2) and cold LN2 into the feed line to yield the setpoint temperature; and (2) closed-loop circulation where control is achieved by either electrically heating or LN2 cooling the circulating GN2 to yield the setpoint temperature. A third method, using a mass flow ratio controller along with modulating control valves on GN2 and LN2 lines, provides excellent control but equipment for this method is expensive and cost-prohibitive for all but long-term continuous processes. The single-pass method provides marginal control and can result in unexpected overcooling of the test article from even a short pulse of LN2. The closed-loop circulation method provides excellent control but requires an expensive blower capable of operating at elevated pressures and cryogenic temperatures. Where precise control is needed (plus or minus 2 C), single-pass flow systems typically have not provided the precision required, primarily because of overcooling temperature excursions. Where several individual circuits are to be controlled at different temperatures, the use of expensive cryogenic blowers for each circuit is also cost-prohibitive, especially for short duration of one-of-a-kind tests. At JPL, a variant of the single-pass method was developed that was shown to provide precise temperature control in the -130 C to 75 C range while exhibiting minimal setpoint overshoot during temperature transitions. This alternate method uses a commercially available temperature controller along with a GN2/LN2 mixer to dampen the amplitude of cold temperature spikes caused by LN2 pulsing. The design of the GN2/LN2 mixer, the overall control system
NASA Astrophysics Data System (ADS)
Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu
2016-01-01
An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.
Vibrational computing: simulation of a full adder by optimal control.
Bomble, L; Lauvergnat, D; Remacle, F; Desouter-Lecomte, M
2008-02-14
Within the context of vibrational molecular quantum computing, we investigate the implementation of a full addition of two binary digits and a carry that provides the sum and the carry out. Four qubits are necessary and they are encoded into four different normal vibrational modes of a molecule. We choose the bromoacetyl chloride molecule because it possesses four bright infrared active modes. The ground and first excited states of each mode form the one-qubit computational basis set. Two approaches are proposed for the realization of the full addition. In the first one, we optimize a pulse that implements directly the entire addition by a single unitary transformation. In the second one, we decompose the full addition in elementary quantum gates, following a scheme proposed by Vedral et al. [Phys. Rev. A 54, 147 (1996)]. Four elementary quantum gates are necessary, two two-qubit CNOT gates (controlled NOT) and two three-qubit TOFFOLI gates (controlled-controlled NOT). All the logic operations consist in one-qubit flip. The logic implementation is therefore quasiclassical and the readout is based on a population analysis of the vibrational modes that does not take the phases into account. The fields are optimized by the multitarget extension of the optimal control theory involving all the transformations among the 2(4) qubit states. A single cycle of addition without considering the preparation or the measure or copy of the result can be carried out in a very competitive time, on a picosecond time scale. PMID:18282031
Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System
Chen, Jilin; Wang, Li; Xu, Shiqing; Hou, Yuanlong
2013-01-01
Motion control of gun barrels is an ongoing topic for the development of gun control equipments possessing excellent performances. In this paper, a typical fractional order PID control strategy is employed for the gun control system. To obtain optimal parameters of the controller, a multiobjective optimization scheme is developed from the loop-shaping perspective. To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. To enhance the robustness of the algorithm for different problems, an adapting scheme of the mutation operation is further employed. With assistance of the evolutionary algorithm, the optimal solution for the specified problem is selected. The numerical simulation results show that the control system can rapidly follow the demand signal with high accuracy and high robustness, demonstrating the efficiency of the proposed controller parameter tuning method. PMID:23766721
Achieving the Framework Convention on Tobacco Control's potential by investing in national capacity
Wipfli, H; Stillman, F; Tamplin, S; da Costa, e Silva V L.; Yach, D; Samet, J
2004-01-01
May 2003 marked a critical achievement in efforts to stem the global tobacco epidemic, as the member states of the World Health Organization unanimously endorsed the Framework Convention on Tobacco Control (FCTC). However, the adoption of the FCTC signifies only the end of the beginning of effective global action to control tobacco. Over the next several years the utility of the FCTC process and the treaty itself will be tested as individual countries seek to ratify and implement the treaty's obligations. Significant barriers to the treaty's long term success exist in many countries. It is crucial that the international tobacco control community now refocuses its efforts on national capacity building and ensures that individual countries have the knowledge, tools, data, people, and organisations needed to implement the convention and develop sustained tobacco control programmes. This paper provides a model of national tobacco control capacity and offers a prioritised agenda for action. PMID:15564631
Scaling up interventions to achieve global tuberculosis control: progress and new developments.
Raviglione, Mario; Marais, Ben; Floyd, Katherine; Lönnroth, Knut; Getahun, Haileyesus; Migliori, Giovanni B; Harries, Anthony D; Nunn, Paul; Lienhardt, Christian; Graham, Steve; Chakaya, Jeremiah; Weyer, Karin; Cole, Stewart; Kaufmann, Stefan H E; Zumla, Alimuddin
2012-05-19
Tuberculosis is still one of the most important causes of death worldwide. The 2010 Lancet tuberculosis series provided a comprehensive overview of global control efforts and challenges. In this update we review recent progress. With improved control efforts, the world and most regions are on track to achieve the Millennium Development Goal of decreasing tuberculosis incidence by 2015, and the Stop TB Partnership target of halving 1990 mortality rates by 2015; the exception is Africa. Despite these advances, full scale-up of tuberculosis and HIV collaborative activities remains challenging and emerging drug-resistant tuberculosis is a major threat. Recognition of the effect that non-communicable diseases--such as smoking-related lung disease, diet-related diabetes mellitus, and alcohol and drug misuse--have on individual vulnerability, as well as the contribution of poor living conditions to community vulnerability, shows the need for multidisciplinary approaches. Several new diagnostic tests are being introduced in endemic countries and for the first time in 40 years a coordinated portfolio of promising new tuberculosis drugs exists. However, none of these advances offer easy solutions. Achievement of international tuberculosis control targets and maintenance of these gains needs optimum national health policies and services, with ongoing investment into new approaches and strategies. Despite growing funding in recent years, a serious shortfall persists. International and national financial uncertainty places gains at serious risk. Perseverance and renewed commitment are needed to achieve global control of tuberculosis, and ultimately, its elimination. PMID:22608339
Kiany, Gholam Reza; Shayestefar, Parvaneh
2011-09-01
BACKGROUND. Theories distinguish between student-initiated and teacher-initiated regulation of students' learning activities, or between strong, shared, or loose teacher control during the completion of learning tasks. Empirical validations for such distinctions are scarce, however. AIM. The present study aimed at (a) investigating students' perceptions of control behaviours exhibited by their English teachers; and (b) exploring the contribution of different types of teacher control behaviours to students' cognitive outcomes (English Achievement). SAMPLE. The sample comprised 732 English as a Foreign Language (EFL) students studying in three major fields of high school (Mathematics, Natural Science, and Humanities). The participants (16-17 years of age) were selected from third-grade classes of 27 EFL teachers working in 25 high schools of 6 main different geographical regions in the Isfahan province, Iran. METHOD. To obtain a comprehensive picture of different control types exhibited by Iranian EFL teachers, the control subscales of the two existing questionnaires, i.e., the Questionnaire on Instructional Behaviours (QIB), adapted by Den Brok et al. (2004) and the Questionnaire on Lesson Activities (QLA) used by Den Brok (2001) were merged to form the Questionnaire of Teacher Control (QTC). The development of this Persian instrument involved several steps: translation and back translation by the researchers, one expert translator, and two EFL teachers; piloting; and a final administration of the questionnaire to the student sample. With respect to the second aim of the study, data regarding students' performances on the Standardized National English Achievement Tests were gathered from local educational offices and schools. RESULTS AND CONCLUSION. Statistical analyses supported acceptable reliability and validity of the instrument. A main factor structure with three types of teacher control (strong/high, shared/mid, and loose/low) was found to underlie students
Kiany, Gholam Reza; Shayestefar, Parvaneh
2011-09-01
BACKGROUND. Theories distinguish between student-initiated and teacher-initiated regulation of students' learning activities, or between strong, shared, or loose teacher control during the completion of learning tasks. Empirical validations for such distinctions are scarce, however. AIM. The present study aimed at (a) investigating students' perceptions of control behaviours exhibited by their English teachers; and (b) exploring the contribution of different types of teacher control behaviours to students' cognitive outcomes (English Achievement). SAMPLE. The sample comprised 732 English as a Foreign Language (EFL) students studying in three major fields of high school (Mathematics, Natural Science, and Humanities). The participants (16-17 years of age) were selected from third-grade classes of 27 EFL teachers working in 25 high schools of 6 main different geographical regions in the Isfahan province, Iran. METHOD. To obtain a comprehensive picture of different control types exhibited by Iranian EFL teachers, the control subscales of the two existing questionnaires, i.e., the Questionnaire on Instructional Behaviours (QIB), adapted by Den Brok et al. (2004) and the Questionnaire on Lesson Activities (QLA) used by Den Brok (2001) were merged to form the Questionnaire of Teacher Control (QTC). The development of this Persian instrument involved several steps: translation and back translation by the researchers, one expert translator, and two EFL teachers; piloting; and a final administration of the questionnaire to the student sample. With respect to the second aim of the study, data regarding students' performances on the Standardized National English Achievement Tests were gathered from local educational offices and schools. RESULTS AND CONCLUSION. Statistical analyses supported acceptable reliability and validity of the instrument. A main factor structure with three types of teacher control (strong/high, shared/mid, and loose/low) was found to underlie students
Optimal Parametric Discrete Event Control: Problem and Solution
Griffin, Christopher H
2008-01-01
We present a novel optimization problem for discrete event control, similar in spirit to the optimal parametric control problem common in statistical process control. In our problem, we assume a known finite state machine plant model $G$ defined over an event alphabet $\\Sigma$ so that the plant model language $L = \\LanM(G)$ is prefix closed. We further assume the existence of a \\textit{base control structure} $M_K$, which may be either a finite state machine or a deterministic pushdown machine. If $K = \\LanM(M_K)$, we assume $K$ is prefix closed and that $K \\subseteq L$. We associate each controllable transition of $M_K$ with a binary variable $X_1,\\dots,X_n$ indicating whether the transition is enabled or not. This leads to a function $M_K(X_1,\\dots,X_n)$, that returns a new control specification depending upon the values of $X_1,\\dots,X_n$. We exhibit a branch-and-bound algorithm to solve the optimization problem $\\min_{X_1,\\dots,X_n}\\max_{w \\in K} C(w)$ such that $M_K(X_1,\\dots,X_n) \\models \\Pi$ and $\\LanM(M_K(X_1,\\dots,X_n)) \\in \\Con(L)$. Here $\\Pi$ is a set of logical assertions on the structure of $M_K(X_1,\\dots,X_n)$, and $M_K(X_1,\\dots,X_n) \\models \\Pi$ indicates that $M_K(X_1,\\dots,X_n)$ satisfies the logical assertions; and, $\\Con(L)$ is the set of controllable sublanguages of $L$.
Coordination and Control of Multiple Spacecraft using Convex Optimization Techniques
NASA Astrophysics Data System (ADS)
How, Jonathan P.
2002-06-01
Formation flying of multiple spacecraft is an enabling technology for many future space science missions. These future missions will, for example, use the highly coordinated, distributed array of vehicles for earth mapping interferometers and synthetic aperture radar. This thesis presents coordination and control algorithms designed for a fleet of spacecraft. These algorithms are embedded in a hierarchical fleet archi- tecture that includes a high-level coordinator for the fleet maneuvers used to form, re-size, or re-target the formation configuration and low-level controllers to generate and implement the individual control inputs for each vehicle. The trajectory and control problems are posed as linear programming (LP) optimizations to solve for the minimum fuel maneuvers. The combined result of the high-level coordination and low-level controllers is a very flexible optimization framework that can be used off-line to analyze aspects of a mission design and in real-time as part of an on-board autonomous formation flying control system. This thesis also investigates several crit- ical issues associated with the implementation of this formation flying approach. In particular, modifications to the LP algorithms are presented to: include robustness to sensor noise, include actuator constraints, ensure that the optimization solutions are always feasible, and reduce the LP solution times. Furthermore, the dynamics for the control problem are analyzed in terms of two key issues: 1) what dynamics model should be used to specify the desired state to maintain a passive aperture; and 2) what dynamics model should be used in the LP to represent the motion about this state. Several linearized models of the relative dynamics are considered in this analysis, including Hill's equations for circular orbits, modified linear dynamics that partially account for the J2 effects, and Lawden's equations for eccentric orbits.
NASA Technical Reports Server (NTRS)
Armand, J. P.
1972-01-01
An extension of classical methods of optimal control theory for systems described by ordinary differential equations to distributed-parameter systems described by partial differential equations is presented. An application is given involving the minimum-mass design of a simply-supported shear plate with a fixed fundamental frequency of vibration. An optimal plate thickness distribution in analytical form is found. The case of a minimum-mass design of an elastic sandwich plate whose fundamental frequency of free vibration is fixed. Under the most general conditions, the optimization problem reduces to the solution of two simultaneous partial differential equations involving the optimal thickness distribution and the modal displacement. One equation is the uniform energy distribution expression which was found by Ashley and McIntosh for the optimal design of one-dimensional structures with frequency constraints, and by Prager and Taylor for various design criteria in one and two dimensions. The second equation requires dynamic equilibrium at the preassigned vibration frequency.
Human energy - optimal control of disturbance rejection during constrained standing.
Mihelj, M; Munih, M; Ponikvar, M
2003-01-01
An optimal control system that enables a subject to stand without hand support in the sagittal plane was designed. The subject was considered as a double inverted pendulum structure with a voluntarily controlled degree of freedom in the upper trunk and artificially controlled degree of freedom in the ankle joints. The control system design was based on a minimization of cost function that estimated the effort of the ankle joint muscles through observation of the ground reaction force position relative to the ankle joint axis. By maintaining the centre of pressure close to the ankle joint axis the objective of the upright stance is fulfilled with minimal ankle muscle energy cost. The performance of the developed controller was evaluated in a simulation-based study. The results were compared with the responses of an unimpaired subject to different disturbances in the sagittal plane. The proposed cost function was shown to produce a reasonable approximation of human natural behaviour. PMID:12936049
Human energy - optimal control of disturbance rejection during constrained standing.
Mihelj, M; Munih, M; Ponikvar, M
2003-01-01
An optimal control system that enables a subject to stand without hand support in the sagittal plane was designed. The subject was considered as a double inverted pendulum structure with a voluntarily controlled degree of freedom in the upper trunk and artificially controlled degree of freedom in the ankle joints. The control system design was based on a minimization of cost function that estimated the effort of the ankle joint muscles through observation of the ground reaction force position relative to the ankle joint axis. By maintaining the centre of pressure close to the ankle joint axis the objective of the upright stance is fulfilled with minimal ankle muscle energy cost. The performance of the developed controller was evaluated in a simulation-based study. The results were compared with the responses of an unimpaired subject to different disturbances in the sagittal plane. The proposed cost function was shown to produce a reasonable approximation of human natural behaviour.
NASA Technical Reports Server (NTRS)
Burcham, Frank W., Jr.; Gilyard, Glenn B.; Myers, Lawrence P.
1990-01-01
Integration of propulsion and flight control systems and their optimization offers significant performance improvements. Research programs were conducted which have developed new propulsion and flight control integration concepts, implemented designs on high-performance airplanes, demonstrated these designs in flight, and measured the performance improvements. These programs, first on the YF-12 airplane, and later on the F-15, demonstrated increased thrust, reduced fuel consumption, increased engine life, and improved airplane performance; with improvements in the 5 to 10 percent range achieved with integration and with no changes to hardware. The design, software and hardware developments, and testing requirements were shown to be practical.
High-Dynamic-Range Imaging of Nanoscale Magnetic Fields Using Optimal Control of a Single Qubit
NASA Astrophysics Data System (ADS)
Häberle, T.; Schmid-Lorch, D.; Karrai, K.; Reinhard, F.; Wrachtrup, J.
2013-10-01
We present a novel spectroscopy protocol based on optimal control of a single quantum system. It enables measurements with quantum-limited sensitivity (ηω∝(1/T2*), T2* denoting the system’s coherence time) but has an orders of magnitude larger dynamic range than pulsed spectroscopy methods previously employed for this task. We employ this protocol to image nanoscale magnetic fields with a single scanning nitrogen-vacancy center in diamond. Here, our scheme enables quantitative imaging of a strongly inhomogeneous field in a single scan without closed-loop control, which has previously been necessary to achieve this goal.
Discrete-valued-pulse optimal control algorithms: Application to spin systems
NASA Astrophysics Data System (ADS)
Dridi, G.; Lapert, M.; Salomon, J.; Glaser, S. J.; Sugny, D.
2015-10-01
This article is aimed at extending the framework of optimal control techniques to the situation where the control field values are restricted to a finite set. We propose generalizations of the standard GRAPE algorithm suited to this constraint. We test the validity and the efficiency of this approach for the inversion of an inhomogeneous ensemble of spin systems with different offset frequencies. It is shown that a remarkable efficiency can be achieved even for a very limited number of discrete values. Some applications in nuclear magnetic resonance are discussed.
NASA Astrophysics Data System (ADS)
Lapert, M.; Tehini, R.; Turinici, G.; Sugny, D.
2008-08-01
We consider the optimal control of quantum systems interacting nonlinearly with an electromagnetic field. We propose monotonically convergent algorithms to solve the optimal equations. The monotonic behavior of the algorithm is ensured by a nonstandard choice of the cost, which is not quadratic in the field. These algorithms can be constructed for pure- and mixed-state quantum systems. The efficiency of the method is shown numerically for molecular orientation with a nonlinearity of order 3 in the field. Discretizing the amplitude and the phase of the Fourier transform of the optimal field, we show that the optimal solution can be well approximated by pulses that could be implemented experimentally.
Robust adaptive feedforward control and achievable tracking for systems with time delays
NASA Astrophysics Data System (ADS)
Buehner, Michael R.; Young, Peter M.
2015-04-01
A feedback/feedforward controller architecture is developed that characterises the achievable reference tracking of real time inputs for both minimum phase and non-minimum phase systems with time delays, when there are no modelling errors or external disturbances. This characterisation is obtained by factoring the plant into its minimum phase, non-minimum phase, and time delay components, which are used to design two feedforward controllers that inject signals into two points of the feedback loop. Design constraints are provided that determine both the types of signals that may be achieved, and the feedforward controllers that will generate that output. Of course, in practice, both modelling errors and external disturbances will be present. In this case, we develop robust analysis tools that both guide the feedback controller design process, and provide rigorous robust tracking performance that guarantees for the overall resulting closed-loop system. Robust methods for designing the feedforward controllers are presented, and numerical examples are provided. The performance of this architecture depends strongly on the choice of design parameters, and the accuracy of the plant model used. Hence, the use of adaptation methods is also considered, and it is shown that they can readily be employed to improve the performance of this control methodology.
Application of constrained optimization to active control of aeroelastic response
NASA Technical Reports Server (NTRS)
Newsom, J. R.; Mukhopadhyay, V.
1981-01-01
Active control of aeroelastic response is a complex in which the designer usually tries to satisfy many criteria which are often conflicting. To further complicate the design problem, the state space equations describing this type of control problem are usually of high order, involving a large number of states to represent the flexible structure and unsteady aerodynamics. Control laws based on the standard Linear-Quadratic-Gaussian (LQG) method are of the same high order as the aeroelastic plant. To overcome this disadvantage of the LQG mode, an approach developed for designing low order optimal control laws which uses a nonlinear programming algorithm to search for the values of the control law variables that minimize a composite performance index, was extended to the constrained optimization problem. The method involves searching for the values of the control law variables that minimize a basic performance index while satisfying several inequality constraints that describe the design criteria. The method is applied to gust load alleviation of a drone aircraft.
A model for HIV/AIDS pandemic with optimal control
NASA Astrophysics Data System (ADS)
Sule, Amiru; Abdullah, Farah Aini
2015-05-01
Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is pandemic. It has affected nearly 60 million people since the detection of the disease in 1981 to date. In this paper basic deterministic HIV/AIDS model with mass action incidence function are developed. Stability analysis is carried out. And the disease free equilibrium of the basic model was found to be locally asymptotically stable whenever the threshold parameter (RO) value is less than one, and unstable otherwise. The model is extended by introducing two optimal control strategies namely, CD4 counts and treatment for the infective using optimal control theory. Numerical simulation was carried out in order to illustrate the analytic results.
Nonlinear singularly perturbed optimal control problems with singular arcs
NASA Technical Reports Server (NTRS)
Ardema, M. D.
1977-01-01
A third order, nonlinear, singularly perturbed optimal control problem is considered under assumptions which assure that the full problem is singular and the reduced problem is nonsingular. The separation between the singular arc of the full problem and the optimal control law of the reduced one, both of which are hypersurfaces in state space, is of the same order as the small parameter of the problem. Boundary layer solutions are constructed which are stable and reach the outer solution in a finite time. A uniformly valid composite solution is then formed from the reduced and boundary layer solutions. The value of the approximate solution is that it is relatively easy to obtain and does not involve singular arcs. To illustrate the utility of the results, the technique is used to obtain an approximate solution of a simplified version of the aircraft minimum time-to-climb problem. A numerical example is included.
Yoo, Sung Jin; Jeong, Dong Hwi; Kim, Jung Hun; Lee, Jong Min
2016-08-01
To maximize biomass and lipid concentrations, various optimization methods were investigated in microalgal photobioreactor systems under mixotrophic conditions. Lipid concentration was estimated using unscented Kalman filter (UKF) with other measurable sources and subsequently used as lipid data for performing model predictive control (MPC). In addition, the maximized biomass and lipid trajectory obtained by open-loop optimization were used as target trajectory for tracking by MPC. Simulation studies and experimental validation were performed and significant improvements in biomass and lipid productivity were achieved in the case where MPC was applied. However, occurence of a lag phase was observed while manipulating the feed flow rates, which is induced by large amount of inputs. This is an important phenomenon that can lead to model-plant mismatch and requires further study for the optimization of microalgal photobioreactors. PMID:27094678
Grob, Koni
2005-01-01
The most important initiatives taken in Switzerland to reduce exposure of consumers to acrylamide are the separate sale of potatoes low in reducing sugars for roasting and frying, the optimization of the raw material and preparation of french fries, and campaigns to implement suitable preparation methods in the gastronomy and homes. Industry works on improving a range of other products. Although these measures can reduce high exposures by some 80%, they have little effect on the background exposure resulting from coffee, bread, and numerous other products for which no substantial improvement is in sight. At this stage, improvements should be achieved by supporting voluntary activity rather than legal limits. Committed and consistent risk communication is key, and the support of improvements presupposes innovative approaches.
An optimized quantum information splitting scheme with multiple controllers
NASA Astrophysics Data System (ADS)
Jiang, Min
2016-09-01
We propose an efficient scheme for splitting multi-qudit information with cooperative control of multiple agents. Each controller is assigned one controlling qudit, and he can monitor the state sharing of all multi-qudit information. Compared with the existing schemes, our scheme requires less resource consumption and approaches higher communication efficiency. In addition, our proposal involves only generalized Bell-state measurement, single-qudit measurement, one-qudit gates and a unitary-reduction operation, which makes it flexible and achievable for physical implementation.
Application of Newton's optimal power flow in voltage/reactive power control
Bjelogrlic, M.; Babic, B.S. ); Calovic, M.S. ); Ristanovic, P. )
1990-11-01
This paper considers an application of Newton's optimal power flow to the solution of the secondary voltage/reactive power control in transmission networks. An efficient computer program based on the latest achievements in the sparse matrix/vector techniques has been developed for this purpose. It is characterized by good robustness, accuracy and speed. A combined objective function appropriate for various system load levels with suitable constraints, for treatment of the power system security and economy is also proposed. For the real-time voltage/reactive power control, a suboptimal power flow procedure has been derived by using the reduced set of control variables. This procedure is based on the sensitivity theory applied to the determination of zones for the secondary voltage/reactive power control and corresponding reduced set of regulating sources, whose reactive outputs represent control variables in the optimal power flow program. As a result, the optimal power flow program output becomes a schedule to be used by operators in the process of the real-time voltage/reactive power control in both normal and emergency operating states.
Professional training in the workplace: the role of achievement motivation and locus of control.
Suárez-Álvarez, Javier; Campillo-Álvarez, Angela; Fonseca-Pedrero, Eduardo; García-Cueto, Eduardo; Muñiz, José
2013-01-01
The core objective of the present work is to explore the reasons why workers from different employment sectors join training courses to improve their job. To this end we assessed achievement motivation, locus of control and professional qualifications according to the participants' employment sector. The final sample consisted of 1460 active Spanish workers from four different employment sectors: services, catering, metal construction, and others. Of the sample, 40.1% were male and 59.9% female, with a mean age of 33.3 years (SD = 9.7). The results show that the new scale developed to assess achievement motivation, locus of control and workers' qualifications presents adequate psychometric characteristics. Statistically significant differences were found in relation to employment sector. The areas studied showed satisfactory levels of workers' effort and achievement motivation to perform their jobs, though their attitudes toward the training courses as a basis for improving their employability are varied. Workers in the catering sector had higher levels of external attribution and the lowest interest in training. Those in the service sector had higher levels of achievement motivation and effort at work. Future research should develop a joint program covering the public and private sectors for the modification of these beliefs, attitudes and attributions.
How do different components of Effortful Control contribute to children’s mathematics achievement?
Sánchez-Pérez, Noelia; Fuentes, Luis J.; Pina, Violeta; López-López, Jose A.; González-Salinas, Carmen
2015-01-01
This work sought to investigate the specific contribution of two different components of Effortful Control (EC) -attentional focusing (AF) and inhibitory control- to children’s mathematics achievement. The sample was composed of 142 children aged 9–12 year-old. EC components were measured through the Temperament in Middle Childhood Questionnaire (TMCQ; parent’s report); math achievement was measured via teacher’s report and through the standard Woodcock–Johnson test. Additionally, the contribution of other cognitive and socio-emotional processes was taken into account. Our results showed that only AF significantly contributed to the variance of children’s mathematics achievement; interestingly, mediational models showed that the relationship between effortful attentional self-regulation and mathematics achievement was mediated by academic peer popularity, as well as by intelligence and study skills. Results are discussed in the light of the current theories on the role of children’s self-regulation abilities in the context of school. PMID:26441758
Implicit methods for efficient musculoskeletal simulation and optimal control
van den Bogert, Antonie J.; Blana, Dimitra; Heinrich, Dieter
2011-01-01
The ordinary differential equations for musculoskeletal dynamics are often numerically stiff and highly nonlinear. Consequently, simulations require small time steps, and optimal control problems are slow to solve and have poor convergence. In this paper, we present an implicit formulation of musculoskeletal dynamics, which leads to new numerical methods for simulation and optimal control, with the expectation that we can mitigate some of these problems. A first order Rosenbrock method was developed for solving forward dynamic problems using the implicit formulation. It was used to perform real-time dynamic simulation of a complex shoulder arm system with extreme dynamic stiffness. Simulations had an RMS error of only 0.11 degrees in joint angles when running at real-time speed. For optimal control of musculoskeletal systems, a direct collocation method was developed for implicitly formulated models. The method was applied to predict gait with a prosthetic foot and ankle. Solutions were obtained in well under one hour of computation time and demonstrated how patients may adapt their gait to compensate for limitations of a specific prosthetic limb design. The optimal control method was also applied to a state estimation problem in sports biomechanics, where forces during skiing were estimated from noisy and incomplete kinematic data. Using a full musculoskeletal dynamics model for state estimation had the additional advantage that forward dynamic simulations, could be done with the same implicitly formulated model to simulate injuries and perturbation responses. While these methods are powerful and allow solution of previously intractable problems, there are still considerable numerical challenges, especially related to the convergence of gradient-based solvers. PMID:22102983
Implicit methods for efficient musculoskeletal simulation and optimal control.
van den Bogert, Antonie J; Blana, Dimitra; Heinrich, Dieter
2011-01-01
The ordinary differential equations for musculoskeletal dynamics are often numerically stiff and highly nonlinear. Consequently, simulations require small time steps, and optimal control problems are slow to solve and have poor convergence. In this paper, we present an implicit formulation of musculoskeletal dynamics, which leads to new numerical methods for simulation and optimal control, with the expectation that we can mitigate some of these problems. A first order Rosenbrock method was developed for solving forward dynamic problems using the implicit formulation. It was used to perform real-time dynamic simulation of a complex shoulder arm system with extreme dynamic stiffness. Simulations had an RMS error of only 0.11 degrees in joint angles when running at real-time speed. For optimal control of musculoskeletal systems, a direct collocation method was developed for implicitly formulated models. The method was applied to predict gait with a prosthetic foot and ankle. Solutions were obtained in well under one hour of computation time and demonstrated how patients may adapt their gait to compensate for limitations of a specific prosthetic limb design. The optimal control method was also applied to a state estimation problem in sports biomechanics, where forces during skiing were estimated from noisy and incomplete kinematic data. Using a full musculoskeletal dynamics model for state estimation had the additional advantage that forward dynamic simulations, could be done with the same implicitly formulated model to simulate injuries and perturbation responses. While these methods are powerful and allow solution of previously intractable problems, there are still considerable numerical challenges, especially related to the convergence of gradient-based solvers.
Optimal feedback control infinite dimensional parabolic evolution systems: Approximation techniques
NASA Technical Reports Server (NTRS)
Banks, H. T.; Wang, C.
1989-01-01
A general approximation framework is discussed for computation of optimal feedback controls in linear quadratic regular problems for nonautonomous parabolic distributed parameter systems. This is done in the context of a theoretical framework using general evolution systems in infinite dimensional Hilbert spaces. Conditions are discussed for preservation under approximation of stabilizability and detectability hypotheses on the infinite dimensional system. The special case of periodic systems is also treated.
Characterizations of Overtaking Optimality for Controlled Diffusion Processes
Jasso-Fuentes, Hector Hernandez-Lerma, Onesimo
2008-06-15
In this paper we give conditions for (the existence and) several characterizations of overtaking optimal policies for a general class of controlled diffusion processes. Our characterization results are of a lexicographical type; namely, first we identify the class of so-called canonical policies, and then within this class we search for policies with some special feature-for instance, canonical policies that in addition maximize the bias.
A general weight matrix formulation using optimal control
NASA Technical Reports Server (NTRS)
Farotimi, Oluseyi; Dembo, Amir; Kailath, Thomas
1991-01-01
Classical methods from optimal control theory are used in deriving general forms for neural network weights. The network learning or application task is encoded in a performance index of a general structure. Consequently, different instances of this performance index lead to special cases of weight rules, including some well-known forms. Comparisons are made with the outer product rule, spectral methods, and recurrent back-propagation. Simulation results and comparisons are presented.
Optimal control in microgrid using multi-agent reinforcement learning.
Li, Fu-Dong; Wu, Min; He, Yong; Chen, Xin
2012-11-01
This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode.
Optimal control in microgrid using multi-agent reinforcement learning.
Li, Fu-Dong; Wu, Min; He, Yong; Chen, Xin
2012-11-01
This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode. PMID:22824135
Optimal cooperative control synthesis applied to a control-configured aircraft
NASA Technical Reports Server (NTRS)
Schmidt, D. K.; Innocenti, M.
1984-01-01
A multivariable control augmentation synthesis method is presented that is intended to enable the designer to directly optimize pilot opinion rating of the augmented system. The approach involves the simultaneous solution for the augmentation and predicted pilot's compensation via optimal control techniques. The methodology is applied to the control law synthesis for a vehicle similar to the AFTI F16 control-configured aircraft. The resulting dynamics, expressed in terms of eigenstructure and time/frequency responses, are presented with analytical predictions of closed loop tracking performance, pilot compensation, and other predictors of pilot acceptance.