Relevant bibliographies by topics / Nonlinear optimal control / Dissertations / Theses
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Dissertations / Theses on the topic 'Nonlinear optimal control'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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1

Zhu, Jinghao. "Some results on nonlinear optimal control." Diss., This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-10042006-143910/.

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2

Zhang, Xiaohong. "Optimal feedback control for nonlinear discrete systems and applications to optimal control of nonlinear periodic ordinary differential equations." Diss., Virginia Tech, 1993. http://hdl.handle.net/10919/40185.

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3

Gavriel, Christos. "Higher order conditions in nonlinear optimal control." Thesis, Imperial College London, 2011. http://hdl.handle.net/10044/1/9042.

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The most widely used tool for the solution of optimal control problems is the Pontryagin Maximum Principle. But the Maximum Principle is, in general, only a necessary condition for optimality. It is therefore desirable to have supplementary conditions, for example second order sufficient conditions, which confirm optimality (at least locally) of an extremal arc, meaning one that satisfies the Maximum Principle. Standard second order sufficient conditions for optimality, when they apply, yield the information not only that the extremal is locally minimizing, but that it is also locally unique.
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4

Primbs, James A. Doyle John Comstock. "Nonlinear optimal control : a receding horizon approach /." Diss., Pasadena, Calif. : California Institute of Technology, 1999. http://resolver.caltech.edu/CaltechETD:etd-10172005-103315.

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5

Tigrek, Tuba. "Nonlinear adaptive optimal control of HVAC systems." Thesis, University of Iowa, 2001. https://ir.uiowa.edu/etd/3429.

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6

Chudoung, Jerawan. "Robust Control for Hybrid, Nonlinear Systems." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/26983.

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We develop the robust control theories of stopping-time nonlinear systems and switching-control nonlinear systems. We formulate a robust optimal stopping-time control problem for a state-space nonlinear system and give the connection between various notions of lower value function for the associated game (and storage function for the associated dissipative system) with solutions of the appropriate variational inequality (VI). We show that the stopping-time rule can be obtained by solving the VI in the viscosity sense. It also happens that a positive definite supersolution of the VI can be us
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7

Meum, Patrick. "Optimal Reservoir control using nonlinear MPC and ECLIPSE." Thesis, Norwegian University of Science and Technology, Department of Engineering Cybernetics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9610.

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<p>Recent years advances within well deployment and instrumentation technology offers huge potentials for increased oil recovery from reservoir production. Wells can now be equipped with controllable valves at reservoir depth, which may possibly alter the production profitability of the field completely, if the devices are used in an intelligent manner. This thesis investigates this potential by using model predictive control to maximize reservoir production performance and total oil production. The report describes an algorithm for nonlinear model predictive control, using a single shooting,
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8

Dong, Wenjie. "Self-organizing and optimal control for nonlinear systems." Diss., [Riverside, Calif.] : University of California, Riverside, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3359894.

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Thesis (Ph. D.)--University of California, Riverside, 2009.<br>Includes abstract. Title from first page of PDF file (viewed January 27, 2010). Includes bibliographical references (p. 82-87). Issued in print and online. Available via ProQuest Digital Dissertations.
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9

Blanchard, Eunice Anita. "Exact penalty methods for nonlinear optimal control problems." Thesis, Curtin University, 2014. http://hdl.handle.net/20.500.11937/1805.

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Research comprised of developing solution techniques to three classes of non-standard optimal control problems, namely: optimal control problems with discontinuous objective functions arising in aquaculture operations; impulsive optimal control problems with minimum subsystem durations; optimal control problems involving dual-mode hybrid systems with state-dependent switching conditions. The numerical algorithms developed involved an exact penalty approach to transform the constrained problem into an unconstrained problem which was readily solvable by a standard optimal control software.
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10

Jorge, Tiago R., João M. Lemos, and Miguel Barão. "Optimal Control for Vehicle Cruise Speed Transfer." Bachelor's thesis, ACTAPRESS, 2011. http://hdl.handle.net/10174/4513.

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The contribution of this paper consists in a procedure to solve the optimal cruise control problem that consists in transferring the car velocity between two specified values, in a fixed interval of time, with minimum fuel consumption. The solution is obtained by applying a recursive numerical algorithm that provides an approximation to the condition provided by Pontryagin’s Optimum Principle. This solution is compared with the one obtained by using a reduced complexity linear model for the car dynamics that allows an exact (“analytical”) solution of the corresponding optimal control problem.
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11

Sjöberg, Johan. "Optimal Control and Model Reduction of Nonlinear DAE Models." Doctoral thesis, Linköpings universitet, Reglerteknik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11345.

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In this thesis, different topics for models that consist of both differential and algebraic equations are studied. The interest in such models, denoted DAE models, have increased substantially during the last years. One of the major reasons is that several modern object-oriented modeling tools used to model large physical systems yield models in this form. The DAE models will, at least locally, be assumed to be described by a decoupled set of ordinary differential equations and purely algebraic equations. In theory, this assumption is not very restrictive because index reduction techniques can
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12

Rosato, Andrea. "A Gaussian Process Learning Method for Nonlinear Optimal Control." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22463/.

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This thesis is focused on discrete-time nonlinear optimal control techniques enhanced via a supervised learning approach based on Gaussian Process regression. Since optimal control strategies are strongly model-based, a perfect knowledge of the real system is required in order to obtain the best performances; however, it is not always possible to satisfy these requirements, since model uncertainties due to, e.g., unavailable information or hard to model dynamical effects may be present leading to a suboptimal solution for the real problem. The basic idea is to exploit measurement data to reduc
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13

Sjöberg, Johan. "Some Results On Optimal Control for Nonlinear Descriptor Systems." Licentiate thesis, Linköping University, Linköping University, Automatic Control, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7489.

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<p>I denna avhandling studeras optimal återkopplad styrning av olinjära deskriptorsystem. Ett deskriptorsystem är en matematisk beskrivning som kan innehålla både differentialekvationer och algebraiska ekvationer. En av anledningarna till intresset för denna klass av system är att objekt-orienterade modelleringsverktyg ger systembeskrivningar på denna form. Här kommer det att antas att det, åtminstone lokalt, är möjligt att eliminera de algebraiska ekvationerna och få ett system på tillståndsform. Teoretiskt är detta inte så inskränkande för genom att använda någon indexreduktionsmetod kan gan
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14

Hein, Sabine. "MPC/LQG-Based Optimal Control of Nonlinear Parabolic PDEs." Doctoral thesis, Universitätsbibliothek Chemnitz, 2010. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-201000134.

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The topic of this thesis is the theoretical and numerical research of optimal control problems for uncertain nonlinear systems, described by semilinear parabolic differential equations with additive noise, where the state is not completely available. Based on a paper by Kazufumi Ito and Karl Kunisch, which was published in 2006 with the title "Receding Horizon Control with Incomplete Observations", we analyze a Model Predictive Control (MPC) approach where the resulting linear problems on small intervals are solved with a Linear Quadratic Gaussian (LQG) design. Further we define a performance
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15

San-Blas, Felipe. "A case study in nonlinear on-line optimal control." Thesis, Imperial College London, 2003. http://hdl.handle.net/10044/1/7344.

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16

Sjöberg, Johan. "Some results on optimal control for nonlinear descriptor systems /." Linköping : Univ, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7489.

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17

Sjöberg, Johan. "Optimal control and model reduction of nonlinear DAE models /." Linköping : Department of Electrical Engineering, Linköping University, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11345.

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18

Johnson, Miles J. "Inverse optimal control for deterministic continuous-time nonlinear systems." Thesis, University of Illinois at Urbana-Champaign, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3632073.

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<p> Inverse optimal control is the problem of computing a cost function with respect to which observed state input trajectories are optimal. We present a new method of inverse optimal control based on minimizing the extent to which observed trajectories violate first-order necessary conditions for optimality. We consider continuous-time deterministic optimal control systems with a cost function that is a linear combination of known basis functions. We compare our approach with three prior methods of inverse optimal control. We demonstrate the performance of these methods by performing simulati
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19

Garcia, Fermin N. (Fermin Noel). "A nonlinear control algorithm for fuel optimal attitude control using reaction jets." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/46267.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1998.<br>Includes bibliographical references (p. 159-161).<br>We present the analysis and design of a weighted nonlinear time-fuel optimal control algorithm for spacecraft attitude dynamics using on-off gas jets. In the development of a controller, we explore four control algorithms within a single-step control framework where the step is the fundamental update time of the digital controller. The benchmark controller is a basic pulse-width modulator (PWM) with a proportional derivative controller driving the
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20

Lin, Yiing-Yuh. "Nonlinear optimal control and near-optimal guidance strategies in spacecraft general attitude maneuvers." Diss., Virginia Polytechnic Institute and State University, 1988. http://hdl.handle.net/10919/53572.

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Solving the optimal open-loop control problems for spacecraft large-angle attitude maneuvers generally requires the use of numerical techniques whose reliability is strongly case dependent. The primary goal of this dissertation is to increase the solution reliability of the associated nonlinear two-point boundary-value problems as derived from Pontryagin’s Principle. Major emphasis is placed upon the formulation of the best possible starting or nominal solution. Constraint relationships among the state and costate variables are utilized. A hybrid approach which begins with the direct gradient
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21

李澤康 and Chak-hong Lee. "Nonlinear time-delay optimal control problem: optimality conditions and duality." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1995. http://hub.hku.hk/bib/B31212475.

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22

Lee, Chak-hong. "Nonlinear time-delay optimal control problem : optimality conditions and duality /." [Hong Kong] : University of Hong Kong, 1995. http://sunzi.lib.hku.hk/hkuto/record.jsp?B16391640.

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23

Sforni, Lorenzo. "A First-Order Closed-loop Methodology for Nonlinear Optimal Control." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21429/.

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This thesis is focused on state-of-art numerical optimization methods for nonlinear (discrete-time) optimal control. These challenging problems arise when dealing with complex tasks for autonomous systems (e.g. vehicles or robots) which require the generation of a trajectory that satisfies the system dynamics and, possibly, input and state constraints due to, e.g, actuator limits or safety region of operation. A general formulation is proposed that allows the implementation of different descent optimization algorithms on optimal control problems exploiting the beneficial effects of state f
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24

Petersson, Daniel. "A Nonlinear Optimization Approach to H2-Optimal Modeling and Control." Doctoral thesis, Linköpings universitet, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93324.

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Mathematical models of physical systems are pervasive in engineering. These models can be used to analyze properties of the system, to simulate the system, or synthesize controllers. However, many of these models are too complex or too large for standard analysis and synthesis methods to be applicable. Hence, there is a need to reduce the complexity of models. In this thesis, techniques for reducing complexity of large linear time-invariant (lti) state-space models and linear parameter-varying (lpv) models are presented. Additionally, a method for synthesizing controllers is also presented. Th
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25

Timmerman, Marc A. A. "Sub-optimal momentum managed control of 1-Dof nonlinear systems." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/17332.

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26

de, Villiers J. P. "Monte Carlo approaches to nonlinear optimal and model predictive control." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.598462.

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This work explores the novel use of advanced Monte Carlo techniques in the disciplines of nonlinear optimal and model predictive control. The interrelation between the subjects of estimation, random sampling and optimisation is exploited to expand the application of advanced numerical. Bayesian inference techniques to the control setting. Firstly, the deterministic optimal control problem is considered. Sophisticated inter-dimensional population Markov Chain Monte Carlo (MCMC) techniques are proposed to solve the nonlinear optimal control problem. The linear quadratic and Acrobot example probl
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27

Voisei, Mircea D. "First-Order Necessary Optimality Conditions for Nonlinear Optimal Control Problems." Ohio University / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1091111473.

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28

Abramova, Ekaterina. "Combining reinforcement learning and optimal control for the control of nonlinear dynamical systems." Thesis, Imperial College London, 2015. http://hdl.handle.net/10044/1/39968.

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This thesis presents a novel hierarchical learning framework, Reinforcement Learning Optimal Control, for controlling nonlinear dynamical systems with continuous states and actions. The adapted approach mimics the neural computations that allow our brain to bridge across the divide between symbolic action-selection and low-level actuation control by operating at two levels of abstraction. First, current findings demonstrate that at the level of limb coordination human behaviour is explained by linear optimal feedback control theory, where cost functions match energy and timing constraints of t
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29

Dinesh, K. "An approximation method for the finite-time optimal control for nonlinear systems." Thesis, University of Sheffield, 1999. http://etheses.whiterose.ac.uk/14781/.

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30

Wolek, Artur. "Optimal Paths in Gliding Flight." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/52783.

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Underwater gliders are robust and long endurance ocean sampling platforms that are increasingly being deployed in coastal regions. This new environment is characterized by shallow waters and significant currents that can challenge the mobility of these efficient (but traditionally slow moving) vehicles. This dissertation aims to improve the performance of shallow water underwater gliders through path planning. The path planning problem is formulated for a dynamic particle (or "kinematic car") model. The objective is to identify the path which satisfies specified boundary conditions and minim
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31

Okura, Yuki. "Trajectory Design Based on Robust Optimal Control and Path Following Control." Kyoto University, 2019. http://hdl.handle.net/2433/242499.

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付記する学位プログラム名: デザイン学大学院連携プログラム<br>Kyoto University (京都大学)<br>0048<br>新制・課程博士<br>博士(工学)<br>甲第21761号<br>工博第4578号<br>新制||工||1713(附属図書館)<br>京都大学大学院工学研究科航空宇宙工学専攻<br>(主査)教授 藤本 健治, 教授 泉田 啓, 教授 太田 快人<br>学位規則第4条第1項該当
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32

Aziz, Mohd Ismail bin Abd. "Development of hierarchical optimal control algorithms for interconnected nonlinear dynamical systems." Thesis, City University London, 1999. http://openaccess.city.ac.uk/7753/.

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The main concern of this thesis is to develop and advance the knowledge of new hierarchical algorithms for optimal control of interconnected nonlinear systems. To achieve this, four basic hierarchical structures are developed by taking into account the manner in which real process measurements taken from interaction inputs are incorporated and utilized in the model-based optimal control problem. The structures are iterative in nature, and are derived using the dynamic integrated system optimization and parameter estimation (DISOPE) technique to take into account model-reality differences that
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33

Torrey, David Allan. "Optimal-efficiency constant-speed control of nonlinear variable reluctance motor drives." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/14713.

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34

Hua, H. "Optimal and robust control for a class of nonlinear stochastic systems." Thesis, University of Liverpool, 2016. http://livrepository.liverpool.ac.uk/3001023/.

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This thesis focuses on theoretical research of optimal and robust control theory for a class of nonlinear stochastic systems. The nonlinearities that appear in the diffusion terms are of a square-root type. Under such systems the following problems are investigated: optimal stochastic control in both finite and infinite horizon; robust stabilization and robust H∞ control; H₂/H∞ control in both finite and infinite horizon; and risk-sensitive control. The importance of this work is that explicit optimal linear controls are obtained, which is a very rare case in the nonlinear system. This is rega
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35

Granzotto, Mathieu. "Near-optimal control of discrete-time nonlinear systems with stability guarantees." Electronic Thesis or Diss., Université de Lorraine, 2019. http://www.theses.fr/2019LORR0301.

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L’intelligence artificielle est riche en algorithmes de commande optimale. Il s’agit de générer des entrées de commande pour des systèmes dynamiques afin de minimiser une fonction de coût donnée décrivant l’énergie du système par exemple. Ces méthodes sont applicables à de larges classes de systèmes non-linéaires en temps discret et ont fait leurs preuves dans de nombreuses applications. Leur exploitation en automatique s’avère donc très prometteuse. Une question fondamentale reste néanmoins à élucider pour cela: celle de la stabilité. En effet, ces travaux se concentrent sur l’optimalité et i
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36

Alhejji, Ayman Khalid. "Dynamic Neural Network-based Adaptive Inverse Optimal Control Design." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/dissertations/891.

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This dissertation introduces a Dynamical Neural Network (DNN) model based adaptive inverse optimal control design for a class of nonlinear systems. A DNN structure is developed and stabilized based on a control Lyapunov function (CLF). The CLF must satisfy the partial Hamilton Jacobi-Bellman (HJB) equation to solve the cost function in order to prove the optimality. In other words, the control design is derived from the CLF and inversely achieves optimality when the given cost function variables are determined posterior. All the stability of the closed loop system is ensured using the Lyapunov
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37

Takahama, Morio, Noboru Sakamoto, and Yuhei Yamato. "Attitude Stabilization of an Aircraft via Nonlinear Optimal Control Based on Aerodynamic Data." Institute of Electrical and Electronics Engineers, 2009. http://hdl.handle.net/2237/14420.

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38

Basset, Gareth. "Virtual Motion Camouflage Based Nonlinear Constrained Optimal Trajectory Design Method." Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5116.

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Nonlinear constrained optimal trajectory control is an important and fundamental area of research that continues to advance in numerous fields. Many attempts have been made to present new methods that can solve for optimal trajectories more efficiently or to improve the overall performance of existing techniques. This research presents a recently developed bio-inspired method called the Virtual Motion Camouflage (VMC) method that offers a means of quickly finding, within a defined but varying search space, the optimal trajectory that is equal or close to the optimal solution. The research sta
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39

Voisei, Mircea Dan. "First-order necessary optimality conditions for nonlinar optimal control problems." Ohio : Ohio University, 2004. http://www.ohiolink.edu/etd/view.cgi?ohiou1091111473.

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40

CALVIA, ALESSANDRO. "Optimal control of pure jump Markov processes with noise-free partial observation." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2018. http://hdl.handle.net/10281/199013.

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La presente tesi tratta un problema di controllo ottimo su orizzonte temporale infinito per un processo di puro salto Markoviano e con osservazione parziale di tipo noise-free. È definita una coppia di processi stocastici, detti processo non osservato o segnale e processo osservato o dei dati. Il segnale è un processo di puro salto Markoviano a tempo continuo, a valori in uno spazio metrico completo e separabile, di cui è nota la misura controllata dei tassi di transizione. Il processo osservato prende valori in un ulteriore spazio metrico completo e separabile ed è di tipo noise-free. Con que
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41

Foley, Dawn Christine. "Short horizon optimal control of nonlinear systems via discrete state space realization." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/16803.

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42

Woon, Siew Fang. "Global algorithms for nonlinear discrete optimization and discrete-valued optimal control problems." Thesis, Curtin University, 2009. http://hdl.handle.net/20.500.11937/538.

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Optimal control problems arise in many applications, such as in economics, finance, process engineering, and robotics. Some optimal control problems involve a control which takes values from a discrete set. These problems are known as discrete-valued optimal control problems. Most practical discrete-valued optimal control problems have multiple local minima and thus require global optimization methods to generate practically useful solutions. Due to the high complexity of these problems, metaheuristic based global optimization techniques are usually required.One of the more recent global optim
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43

Cimen, Tayfun. "Global optimal feedback control of nonlinear systems and viscosity solutions of Hamilton-Jacobi-Bellman equations." Thesis, University of Sheffield, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289660.

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44

Fawcett, Randall Tyler. "Real-Time Planning and Nonlinear Control for Robust Quadrupedal Locomotion with Tails." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/104201.

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This thesis aims to address the real-time planning and nonlinear control of quadrupedal locomotion such that the resulting gaits are robust to various kinds of disturbances. Specifically, this work addresses two scenarios. Namely, a quasi-static formulation in which an inertial appendage (i.e., a tail) is used to assist the quadruped in negating external push disturbances, and an agile formulation which is derived in a manner such that an appendage could easily be added in future work to examine the affect of tails on agile and high-speed motions. Initially, this work presents a unified method
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45

Reig, Bernad Alberto. "Optimal Control for Automotive Powertrain Applications." Doctoral thesis, Universitat Politècnica de València, 2017. http://hdl.handle.net/10251/90624.

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Optimal Control (OC) is essentially a mathematical extremal problem. The procedure consists on the definition of a criterion to minimize (or maximize), some constraints that must be fulfilled and boundary conditions or disturbances affecting to the system behavior. The OC theory supplies methods to derive a control trajectory that minimizes (or maximizes) that criterion. This dissertation addresses the application of OC to automotive control problems at the powertrain level, with emphasis on the internal combustion engine. The necessary tools are an optimization method and a mathematical repr
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46

Jennings, Alan Lance. "Autonomous Motion Learning for Near Optimal Control." University of Dayton / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1344016631.

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47

Boonnithivorakul, Nattapong. "Recursive on-line strategy for optimal control of a class of nonlinear systems /." Available to subscribers only, 2006. http://proquest.umi.com/pqdweb?did=1136091921&sid=7&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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48

Rungger, Matthias [Verfasser]. "On the Numerical Solution of Nonlinear and Hybrid Optimal Control Problems / Matthias Rungger." Kassel : Kassel University Press, 2012. http://d-nb.info/1036916677/34.

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49

Medagam, Peda Vasanta Reddy. "Online optimal control for a class of nonlinear system using RBF neural networks /." Available to subscribers only, 2008. http://proquest.umi.com/pqdweb?did=1650508351&sid=19&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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50

Umemura, Yoshio, Noboru Sakamoto, and Yuto Yuasa. "Optimal Control Designs for Systems with Input Saturations and Rate Limiters." IEEE, 2010. http://hdl.handle.net/2237/14447.

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