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| robust and optimal control zhou: Essentials of Robust Control Kemin Zhou, John Comstock Doyle, 1998 This text offers a streamlined approach to robust control that reflects topics and developments in the field. It features coverage of: gap metric; V-gap metric; model validation; and real mu. |
| robust and optimal control zhou: Robust Control Theory Bruce A. Francis, Pramod P. Khargonekar, 2012-12-06 Robust control originates with the need to cope with systems with modeling uncertainty. There have been several mathematical techniques developed for robust control system analysis. The articles in this volume cover all of the major research directions in the field. |
| robust and optimal control zhou: Robust Control Design with MATLAB® Da-Wei Gu, Petko H. Petkov, Mihail M Konstantinov, 2006-03-30 Shows readers how to exploit the capabilities of the MATLAB® Robust Control and Control Systems Toolboxes to the fullest using practical robust control examples. |
| robust and optimal control zhou: A Course in Robust Control Theory Geir E. Dullerud, Fernando Paganini, 2013-03-14 Research in robust control theory has been one of the most active areas of mainstream systems theory since the late 70s. This research activity has been at the confluence of dynamical systems theory, functional analysis, matrix analysis, numerical methods, complexity theory, and engineering applications. The discipline has involved interactions between diverse research groups including pure mathematicians, applied mathematicians, computer scientists and engineers. This research effort has produced a rather extensive set of approaches using a wide variety of mathematical techniques, and applications of robust control theory are spreading to areas as diverse as control of fluids, power networks, and the investigation of feddback mechanisms in biology. During the 90's the theory has seen major advances and achieved a new maturity, centered around the notion of convexity. The goal of this book is to give a graduate-level course on robust control theory that emphasizes these new developments, but at the same time conveys the main principles and ubiquitous tools at the heart of the subject. Its pedagogical objectives are to introduce a coherent and unified framework for studying robust control theory, to provide students with the control-theoretic background required to read and contribute to the research literature, and to present the main ideas and demonstrations of the major results of robust control theory. The book will be of value to mathematical researchers and computer scientists wishing to learn about robust control theory, graduate students planning to do research in the area, and engineering practitioners requiring advanced control techniques. |
| robust and optimal control zhou: Robust Optimization Aharon Ben-Tal, Laurent El Ghaoui, Arkadi Nemirovski, 2009-08-10 Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject. |
| robust and optimal control zhou: Calculus of Variations and Optimal Control Theory Daniel Liberzon, 2011-12-19 This textbook offers a concise yet rigorous introduction to calculus of variations and optimal control theory, and is a self-contained resource for graduate students in engineering, applied mathematics, and related subjects. Designed specifically for a one-semester course, the book begins with calculus of variations, preparing the ground for optimal control. It then gives a complete proof of the maximum principle and covers key topics such as the Hamilton-Jacobi-Bellman theory of dynamic programming and linear-quadratic optimal control. Calculus of Variations and Optimal Control Theory also traces the historical development of the subject and features numerous exercises, notes and references at the end of each chapter, and suggestions for further study. Offers a concise yet rigorous introduction Requires limited background in control theory or advanced mathematics Provides a complete proof of the maximum principle Uses consistent notation in the exposition of classical and modern topics Traces the historical development of the subject Solutions manual (available only to teachers) Leading universities that have adopted this book include: University of Illinois at Urbana-Champaign ECE 553: Optimum Control Systems Georgia Institute of Technology ECE 6553: Optimal Control and Optimization University of Pennsylvania ESE 680: Optimal Control Theory University of Notre Dame EE 60565: Optimal Control |
| robust and optimal control zhou: Essentials of Robust and Optimal Control Zhou, 1998-02-01 |
| robust and optimal control zhou: New Directions and Applications in Control Theory Wijesuriya P. Dayawansa, Anders Lindquist, Yishao Zhou, 2005-08-31 This volume contains a collection of papers in control theory and applications presented at a conference in honor of Clyde Martin on the occasion of his 60th birthday, held in Lubbock, Texas, November 14-15, 2003. |
| robust and optimal control zhou: Robustness Lars Peter Hansen, Thomas J. Sargent, 2016-06-28 The standard theory of decision making under uncertainty advises the decision maker to form a statistical model linking outcomes to decisions and then to choose the optimal distribution of outcomes. This assumes that the decision maker trusts the model completely. But what should a decision maker do if the model cannot be trusted? Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics. Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes. |
| robust and optimal control zhou: Control Theory Tutorial Steven A. Frank, 2018-05-29 This open access Brief introduces the basic principles of control theory in a concise self-study guide. It complements the classic texts by emphasizing the simple conceptual unity of the subject. A novice can quickly see how and why the different parts fit together. The concepts build slowly and naturally one after another, until the reader soon has a view of the whole. Each concept is illustrated by detailed examples and graphics. The full software code for each example is available, providing the basis for experimenting with various assumptions, learning how to write programs for control analysis, and setting the stage for future research projects. The topics focus on robustness, design trade-offs, and optimality. Most of the book develops classical linear theory. The last part of the book considers robustness with respect to nonlinearity and explicitly nonlinear extensions, as well as advanced topics such as adaptive control and model predictive control. New students, as well as scientists from other backgrounds who want a concise and easy-to-grasp coverage of control theory, will benefit from the emphasis on concepts and broad understanding of the various approaches. Electronic codes for this title can be downloaded from https://extras.springer.com/?query=978-3-319-91707-8 |
| robust and optimal control zhou: Multivariable Feedback Control: Analysis and Design Sigurd Skogestad, 2014 |
| robust and optimal control zhou: Multivariable Feedback Design Jan Marian Maciejowski, 1989 Provides a view of modern multivariate feedback theory and design. Balancing techniques with theory, the objective throughout is to enable the feedback engineer to design real systems. |
| robust and optimal control zhou: Optimal Control Systems D. Subbaram Naidu, 2018-10-03 The theory of optimal control systems has grown and flourished since the 1960's. Many texts, written on varying levels of sophistication, have been published on the subject. Yet even those purportedly designed for beginners in the field are often riddled with complex theorems, and many treatments fail to include topics that are essential to a thorough grounding in the various aspects of and approaches to optimal control. Optimal Control Systems provides a comprehensive but accessible treatment of the subject with just the right degree of mathematical rigor to be complete but practical. It provides a solid bridge between traditional optimization using the calculus of variations and what is called modern optimal control. It also treats both continuous-time and discrete-time optimal control systems, giving students a firm grasp on both methods. Among this book's most outstanding features is a summary table that accompanies each topic or problem and includes a statement of the problem with a step-by-step solution. Students will also gain valuable experience in using industry-standard MATLAB and SIMULINK software, including the Control System and Symbolic Math Toolboxes. Diverse applications across fields from power engineering to medicine make a foundation in optimal control systems an essential part of an engineer's background. This clear, streamlined presentation is ideal for a graduate level course on control systems and as a quick reference for working engineers. |
| robust and optimal control zhou: Optimal Control Theory Suresh P. Sethi, Gerald L. Thompson, 2005-09-06 Optimal control methods are used to determine optimal ways to control a dynamic system. The theoretical work in this field serves as a foundation for the book, which the authors have applied to business management problems developed from their research and classroom instruction. Sethi and Thompson have provided management science and economics communities with a thoroughly revised edition of their classic text on Optimal Control Theory. The new edition has been completely refined with careful attention to the text and graphic material presentation. Chapters cover a range of topics including finance, production and inventory problems, marketing problems, machine maintenance and replacement, problems of optimal consumption of natural resources, and applications of control theory to economics. The book contains new results that were not available when the first edition was published, as well as an expansion of the material on stochastic optimal control theory. |
| robust and optimal control zhou: Robust Control Kang-Zhi Liu, Yu Yao, 2016-12-08 Comprehensive and up to date coverage of robust control theory and its application • Presented in a well-planned and logical way • Written by a respected leading author, with extensive experience in robust control • Accompanying website provides solutions manual and other supplementary material |
| robust and optimal control zhou: Robust and Optimal Control Mi-Ching Tsai, Da-Wei Gu, 2014-01-07 A Two-port Framework for Robust and Optimal Control introduces an alternative approach to robust and optimal controller synthesis procedures for linear, time-invariant systems, based on the two-port system widespread in electrical engineering. The novel use of the two-port system in this context allows straightforward engineering-oriented solution-finding procedures to be developed, requiring no mathematics beyond linear algebra. A chain-scattering description provides a unified framework for constructing the stabilizing controller set and for synthesizing H2 optimal and H∞ sub-optimal controllers. Simple yet illustrative examples explain each step. A Two-port Framework for Robust and Optimal Control features: · a hands-on, tutorial-style presentation giving the reader the opportunity to repeat the designs presented and easily to modify them for their own programs; · an abundance of examples illustrating the most important steps in robust and optimal design; and · end-of-chapter exercises. To further demonstrate the proposed approaches, in the last chapter an application case study is presented which demonstrates the use of the framework in a real-world control system design and helps the reader quickly move on with their own challenges. MATLAB® codes used in examples throughout the book and solutions to selected exercise questions are available for download. The text will have particular resonance for researchers in control with an electrical engineering background, who wish to avoid spending excessive time in learning complex mathematical, theoretical developments but need to know how to deal with robust and optimal control synthesis problems. Please see [http://km.emotors.ncku.edu.tw/class/hw1.html] for solutions to the exercises provided in this book. |
| robust and optimal control zhou: Practical Methods for Optimal Control and Estimation Using Nonlinear Programming John T. Betts, 2010-01-01 The book describes how sparse optimization methods can be combined with discretization techniques for differential-algebraic equations and used to solve optimal control and estimation problems. The interaction between optimization and integration is emphasized throughout the book. |
| robust and optimal control zhou: Essentials of Robust Control Kemin Zhou, John Comstock Doyle, 1998 Based upon the popular Robust and Optimal Control by Zhou, et al. (PH, 1995), this book offers a streamlined approach to robust control that reflects the most recent topics and developments in the field. It features coverage of state-of-the-art topics, including gap metric, v-gap metric, model validation, and real mu. |
| robust and optimal control zhou: Trends in Control Alberto Isidori, 2012-12-06 This book contains the text of the plenary lectures and the mini-courses of the European Control Conference (ECC 95) held in Rome, Italy, September 5-September 8, 1995. In particular, the book includes nine essays in which a selected number of prominent authorities present their views on some of the most recent developments in the theory and practice of control systems design and three self-contained sets of lecture notes. Some of the essays are focused on the topic of robust control. The article by J. Ackermann describes how to robustly control the rotational motions of a vehicle, to the purpose of simplifying the driver's task. The contribution by H. K wakernaak presents a detailed discussion of the requirements that performance and robustness impose on control systems design and of the symmetric roles of sensitivity and complementary sensitivity functions. The article by P. Boulet, B. A. Francis, P. C . Hughes and T. Hong describes an experimental testbed facility, called Daisy, whose dynamics emulate those of a real large flexible space structure and whose purpose is to test advanced identification and control design methods. The article of K. Glover discusses recent advances in uncertain system modeling, analysis and design, with ref erence to a flight control case study that has been test flown. The other essays describe advances in fundamental problems of control theory. The article by V. A. Yakubovich is a survey of certain new infinite horizon linear-quadratic optimization problems. The contribution by A. S. |
| robust and optimal control zhou: Adaptive Optimal Control Robert R. Bitmead, Michel Gevers, Vincent Wertz, 1990 Exploring connections between adaptive control theory and practice, this book treats the techniques of linear quadratic optimal control and estimation (Kalman filtering), recursive identification, linear systems theory and robust arguments. |
| robust and optimal control zhou: Robust Adaptive Dynamic Programming Yu Jiang, Zhong-Ping Jiang, 2017-04-25 A comprehensive look at state-of-the-art ADP theory and real-world applications This book fills a gap in the literature by providing a theoretical framework for integrating techniques from adaptive dynamic programming (ADP) and modern nonlinear control to address data-driven optimal control design challenges arising from both parametric and dynamic uncertainties. Traditional model-based approaches leave much to be desired when addressing the challenges posed by the ever-increasing complexity of real-world engineering systems. An alternative which has received much interest in recent years are biologically-inspired approaches, primarily RADP. Despite their growing popularity worldwide, until now books on ADP have focused nearly exclusively on analysis and design, with scant consideration given to how it can be applied to address robustness issues, a new challenge arising from dynamic uncertainties encountered in common engineering problems. Robust Adaptive Dynamic Programming zeros in on the practical concerns of engineers. The authors develop RADP theory from linear systems to partially-linear, large-scale, and completely nonlinear systems. They provide in-depth coverage of state-of-the-art applications in power systems, supplemented with numerous real-world examples implemented in MATLAB. They also explore fascinating reverse engineering topics, such how ADP theory can be applied to the study of the human brain and cognition. In addition, the book: Covers the latest developments in RADP theory and applications for solving a range of systems’ complexity problems Explores multiple real-world implementations in power systems with illustrative examples backed up by reusable MATLAB code and Simulink block sets Provides an overview of nonlinear control, machine learning, and dynamic control Features discussions of novel applications for RADP theory, including an entire chapter on how it can be used as a computational mechanism of human movement control Robust Adaptive Dynamic Programming is both a valuable working resource and an intriguing exploration of contemporary ADP theory and applications for practicing engineers and advanced students in systems theory, control engineering, computer science, and applied mathematics. |
| robust and optimal control zhou: First-order and Stochastic Optimization Methods for Machine Learning Guanghui Lan, 2020-05-15 This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning. |
| robust and optimal control zhou: Uncertainty and Feedback Glenn Vinnicombe, 2001 The principal reason for using feedback is to reduce the effect of uncertainties in the description of a system which is to be controlled. H[infinity] loop-shaping is emerging as a powerful but straightforward method for designing robust feedback controllers for complex systems. However, in order to use this, or other modern design techniques, it is first necessary to generate an accurate model of the system (thus appearing to remove the reason for needing feedback in the first place). The v-gap metric is an attempt to resolve this paradox - by indicating in what sense a model should be accurate if it is to be useful for feedback design. This book develops in detail the H[infinity] loop-shaping design method, the v-gap metric and the relationship between the two, showing how they can be used together for successful feedback design. |
| robust and optimal control zhou: Discrete-Time Markov Jump Linear Systems O.L.V. Costa, M.D. Fragoso, R.P. Marques, 2006-03-30 Safety critical and high-integrity systems, such as industrial plants and economic systems can be subject to abrupt changes - for instance due to component or interconnection failure, and sudden environment changes etc. Combining probability and operator theory, Discrete-Time Markov Jump Linear Systems provides a unified and rigorous treatment of recent results for the control theory of discrete jump linear systems, which are used in these areas of application. The book is designed for experts in linear systems with Markov jump parameters, but is also of interest for specialists in stochastic control since it presents stochastic control problems for which an explicit solution is possible - making the book suitable for course use. From the reviews: This text is very well written...it may prove valuable to those who work in the area, are at home with its mathematics, and are interested in stability of linear systems, optimal control, and filtering. Journal of the American Statistical Association, December 2005 |
| robust and optimal control zhou: Optimal Control Frank L. Lewis, Draguna Vrabie, Vassilis L. Syrmos, 2012-02-01 A NEW EDITION OF THE CLASSIC TEXT ON OPTIMAL CONTROL THEORY As a superb introductory text and an indispensable reference, this new edition of Optimal Control will serve the needs of both the professional engineer and the advanced student in mechanical, electrical, and aerospace engineering. Its coverage encompasses all the fundamental topics as well as the major changes that have occurred in recent years. An abundance of computer simulations using MATLAB and relevant Toolboxes is included to give the reader the actual experience of applying the theory to real-world situations. Major topics covered include: Static Optimization Optimal Control of Discrete-Time Systems Optimal Control of Continuous-Time Systems The Tracking Problem and Other LQR Extensions Final-Time-Free and Constrained Input Control Dynamic Programming Optimal Control for Polynomial Systems Output Feedback and Structured Control Robustness and Multivariable Frequency-Domain Techniques Differential Games Reinforcement Learning and Optimal Adaptive Control |
| robust and optimal control zhou: Calculus of Variations I Mariano Giaquinta, Stefan Hildebrandt, 2010-12-04 This two-volume treatise is a standard reference in the field. It pays special attention to the historical aspects and the origins partly in applied problems—such as those of geometric optics—of parts of the theory. It contains an introduction to each chapter, section, and subsection and an overview of the relevant literature in the footnotes and bibliography. It also includes an index of the examples used throughout the book. |
| robust and optimal control zhou: Model Predictive Control in the Process Industry Eduardo F. Camacho, Carlos A. Bordons, 2012-12-06 Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of posing the process control problem in the time domain. The Model Predictive Control formulation integrates optimal control, stochastic control, control of processes with dead time, multivariable control and future references. The finite control horizon makes it possible to handle constraints and non linear processes in general which are frequently found in industry. Focusing on implementation issues for Model Predictive Controllers in industry, it fills the gap between the empirical way practitioners use control algorithms and the sometimes abstractly formulated techniques developed by researchers. The text is firmly based on material from lectures given to senior undergraduate and graduate students and articles written by the authors. |
| robust and optimal control zhou: Disturbance Observer-Based Control Shihua Li, Jun Yang, Wen-Hua Chen, Xisong Chen, 2016-04-19 Due to its abilities to compensate disturbances and uncertainties, disturbance observer based control (DOBC) is regarded as one of the most promising approaches for disturbance-attenuation. One of the first books on DOBC, Disturbance Observer Based Control: Methods and Applications presents novel theory results as well as best practices for applica |
| robust and optimal control zhou: Robust and Optimal Control Kemin Zhou, John Comstock Doyle, Keith Glover, 1996 Class-tested at major institutions around the world, this work offers complete coverage of robust and H control. It features clear coverage of methodology, and provides detailed treatment of topics including Riccati equations, m theory, H loopshaping and controller reduction. |
| robust and optimal control zhou: Linear Systems Alok Sinha, 2007-01-31 Balancing rigorous theory with practical applications, Linear Systems: Optimal and Robust Control explains the concepts behind linear systems, optimal control, and robust control and illustrates these concepts with concrete examples and problems. Developed as a two-course book, this self-contained text first discusses linear systems, incl |
| robust and optimal control zhou: Robust and H_ Control Ben M. Chen, 2013-03-14 H-infinity control theory deals with the minimization of the H-infinity-norm of the transfer matrix from an exogenous disturbance to a pertinent controlled output of a given plant. Robust and H-infinity Control examines both the theoretical and practical aspects of H-infinity control from the angle of the structural properties of linear systems. Constructive algorithms are provided for finding solutions to: • general singular H-infinity control problems; • general H-infinity almost disturbance decoupling problems; • robust and perfect tracking problems. Theories are also applied to real-life problems with actual implementations. This book can be used for graduate courses in departments of aeronautics and astronautics, applied mathematics, chemical engineering, electrical engineering and mechanical engineering. It should also be of great value to engineers practising in industry. |
| robust and optimal control zhou: Elementary Classical Analysis Jerrold E. Marsden, Michael J. Hoffman, 1993-03-15 Designed for courses in advanced calculus and introductory real analysis, Elementary Classical Analysis strikes a careful balance between pure and applied mathematics with an emphasis on specific techniques important to classical analysis without vector calculus or complex analysis. Intended for students of engineering and physical science as well as of pure mathematics. |
| robust and optimal control zhou: Linear Matrix Inequalities in System and Control Theory Stephen Boyd, Laurent El Ghaoui, Eric Feron, Venkataramanan Balakrishnan, 1994-01-01 In this book the authors reduce a wide variety of problems arising in system and control theory to a handful of convex and quasiconvex optimization problems that involve linear matrix inequalities. These optimization problems can be solved using recently developed numerical algorithms that not only are polynomial-time but also work very well in practice; the reduction therefore can be considered a solution to the original problems. This book opens up an important new research area in which convex optimization is combined with system and control theory, resulting in the solution of a large number of previously unsolved problems. |
| robust and optimal control zhou: Inequalities: Theory of Majorization and Its Applications Albert W. Marshall, Ingram Olkin, Barry C. Arnold, 2010-11-25 This book’s first edition has been widely cited by researchers in diverse fields. The following are excerpts from reviews. “Inequalities: Theory of Majorization and its Applications” merits strong praise. It is innovative, coherent, well written and, most importantly, a pleasure to read. ... This work is a valuable resource!” (Mathematical Reviews). “The authors ... present an extremely rich collection of inequalities in a remarkably coherent and unified approach. The book is a major work on inequalities, rich in content and original in organization.” (Siam Review). “The appearance of ... Inequalities in 1979 had a great impact on the mathematical sciences. By showing how a single concept unified a staggering amount of material from widely diverse disciplines–probability, geometry, statistics, operations research, etc.–this work was a revelation to those of us who had been trying to make sense of his own corner of this material.” (Linear Algebra and its Applications). This greatly expanded new edition includes recent research on stochastic, multivariate and group majorization, Lorenz order, and applications in physics and chemistry, in economics and political science, in matrix inequalities, and in probability and statistics. The reference list has almost doubled. |
| robust and optimal control zhou: Variable Structure and Lyapunov Control Alan S. I. Zinober, 1994 |
| robust and optimal control zhou: Cooperative Control of Multi-Agent Systems Frank L. Lewis, Hongwei Zhang, Kristian Hengster-Movric, Abhijit Das, 2013-12-31 Cooperative Control of Multi-Agent Systems extends optimal control and adaptive control design methods to multi-agent systems on communication graphs. It develops Riccati design techniques for general linear dynamics for cooperative state feedback design, cooperative observer design, and cooperative dynamic output feedback design. Both continuous-time and discrete-time dynamical multi-agent systems are treated. Optimal cooperative control is introduced and neural adaptive design techniques for multi-agent nonlinear systems with unknown dynamics, which are rarely treated in literature are developed. Results spanning systems with first-, second- and on up to general high-order nonlinear dynamics are presented. Each control methodology proposed is developed by rigorous proofs. All algorithms are justified by simulation examples. The text is self-contained and will serve as an excellent comprehensive source of information for researchers and graduate students working with multi-agent systems. |
| robust and optimal control zhou: Robust Control Design with MATLAB® Da-Wei Gu, Petko H. Petkov, Mihail M Konstantinov, 2014-07-08 Robust Control Design with MATLAB® (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples from teaching-laboratory experiments, such as a two-wheeled, self-balancing robot, to complex systems like a flexible-link manipulator are given detailed presentation. All of these exercises are conducted using MATLAB® Robust Control Toolbox 3, Control System Toolbox and Simulink®. By sharing their experiences in industrial cases with minimum recourse to complicated theories and formulae, the authors convey essential ideas and useful insights into robust industrial control systems design using major H-infinity optimization and related methods allowing readers quickly to move on with their own challenges. The hands-on tutorial style of this text rests on an abundance of examples and features for the second edition: • rewritten and simplified presentation of theoretical and methodological material including original coverage of linear matrix inequalities; • new Part II forming a tutorial on Robust Control Toolbox 3; • fresh design problems including the control of a two-rotor dynamic system; and • end-of-chapter exercises. Electronic supplements to the written text that can be downloaded from extras.springer.com/isbn include: • M-files developed with MATLAB® help in understanding the essence of robust control system design portrayed in text-based examples; • MDL-files for simulation of open- and closed-loop systems in Simulink®; and • a solutions manual available free of charge to those adopting Robust Control Design with MATLAB® as a textbook for courses. Robust Control Design with MATLAB® is for graduate students and practising engineers who want to learn how to deal with robust control design problems without spending a lot of time in researching complex theoretical developments. |
| robust and optimal control zhou: Applications of Stochastic Optimal Control to Economics and Finance Salvatore Federico, Giorgio Ferrari, Luca Regis, 2020-06-23 In a world dominated by uncertainty, modeling and understanding the optimal behavior of agents is of the utmost importance. Many problems in economics, finance, and actuarial science naturally require decision makers to undertake choices in stochastic environments. Examples include optimal individual consumption and retirement choices, optimal management of portfolios and risk, hedging, optimal timing issues in pricing American options, and investment decisions. Stochastic control theory provides the methods and results to tackle all such problems. This book is a collection of the papers published in the Special Issue Applications of Stochastic Optimal Control to Economics and Finance, which appeared in the open access journal Risks in 2019. It contains seven peer-reviewed papers dealing with stochastic control models motivated by important questions in economics and finance. Each model is rigorously mathematically funded and treated, and the numerical methods are employed to derive the optimal solution. The topics of the book's chapters range from optimal public debt management to optimal reinsurance, real options in energy markets, and optimal portfolio choice in partial and complete information settings. From a mathematical point of view, techniques and arguments of dynamic programming theory, filtering theory, optimal stopping, one-dimensional diffusions and multi-dimensional jump processes are used. |
| robust and optimal control zhou: Model Predictive Control James Blake Rawlings, 2024 |
| robust and optimal control zhou: Perspectives in Control Dorothee Normand-Cyrot, 2011-10-21 Perspectives in Control comprises twenty-one essays by leading experts in the field of control. Most of these were presented as plenary lectures at the colloquium erspectives in Control held at Paris, June 1998, and organised by the GdR-Automatique to mark the occasion of the sixtieth birthday of its founder, Ioan Dori Landau. The book provides a unique opportunity to report the views of the world-renowned authorities on some of the directions in which control disciplines might evolve in various areas at the threshold of the twenty-first century. The variety of essays, which includes advanced methodological contributions and overview tutorials as well as more philosophical reflections, contributes to the richness of the book. Many aspects of the field are discussed , including: - adaptive control; - passivity concepts; - nonlinear control; - system identification; - supervisory control; - diagnosis; - emerging applied fields such as mechatronics, air traffic control, power plants, and educational devices. Many of the pioneering aspects of Professor Landau's work are covered. The book will be of interest to scientists as a guide to challenging research subjects, and of value to applied researchers as a survey of the current state of the art and potential of the field. |
ROBUST Definition & Meaning - Merriam-Webster
The meaning of ROBUST is having or exhibiting strength or vigorous health. How to use robust in a sentence. Synonym Discussion of Robust.
ROBUST | English meaning - Cambridge Dictionary
ROBUST definition: 1. (of a person or animal) strong and healthy, or (of an object or system) strong and unlikely to…. Learn more.
ROBUST Definition & Meaning | Dictionary.com
Robust definition: strong and healthy; hardy; vigorous.. See examples of ROBUST used in a sentence.
Robust - definition of robust by The Free Dictionary
Powerfully built; sturdy: a robust body. 3. Requiring or characterized by much strength or energy: a robust workout. 4. a. Active or dynamic: a robust debate; a robust economy. b. Working in an effective way; effective or …
robust adjective - Definition, pictures, pronunciation and usag…
Definition of robust adjective from the Oxford Advanced Learner's Dictionary. strong and healthy. She was almost 90, but still very robust. He seems to be in robust (good) health. Want to learn more? strong; able to …
ROBUST Definition & Meaning - Merriam-Webster
The meaning of ROBUST is having or exhibiting strength or vigorous health. How to use robust in a sentence. Synonym Discussion of Robust.
ROBUST | English meaning - Cambridge Dictionary
ROBUST definition: 1. (of a person or animal) strong and healthy, or (of an object or system) strong and unlikely to…. Learn more.
ROBUST Definition & Meaning | Dictionary.com
Robust definition: strong and healthy; hardy; vigorous.. See examples of ROBUST used in a sentence.
Robust - definition of robust by The Free Dictionary
Powerfully built; sturdy: a robust body. 3. Requiring or characterized by much strength or energy: a robust workout. 4. a. Active or dynamic: a robust debate; a robust economy. b. Working in an …
robust adjective - Definition, pictures, pronunciation and usage …
Definition of robust adjective from the Oxford Advanced Learner's Dictionary. strong and healthy. She was almost 90, but still very robust. He seems to be in robust (good) health. Want to learn …
ROBUST definition and meaning | Collins English Dictionary
Someone or something that is robust is very strong or healthy. More women than men go to the doctor. Perhaps men are more robust or worry less? We've always specialised in making very …
What does robust mean? - Definitions.net
Robust generally refers to the strength, health, or ability of something to withstand adverse conditions or rough handling. In a broader context, it can also refer to the capacity of a system …
Robust - Definition, Meaning & Synonyms - Vocabulary.com
Use robust to describe a person or thing that is healthy and strong, or strongly built. This adjective also commonly describes food or drink: a robust wine has a rich, strong flavor.
ROBUST Synonyms: 194 Similar and Opposite Words - Merriam-Webster
Synonyms for ROBUST: healthy, sturdy, well, strong, whole, wholesome, fit, hale; Antonyms of ROBUST: weak, feeble, sick, unhealthy, unfit, ill, unsound, diseased
Meaning of robust – Learner’s Dictionary - Cambridge Dictionary
ROBUST definition: strong and healthy: . Learn more.
