Optimal Control Of Discrete Time Stochastic Systems
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Optimal Control Of Discrete Time Stochastic Systems
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Author : C. Striebel
language : en
Publisher: Springer
Release Date : 2012-02-29
Optimal Control Of Discrete Time Stochastic Systems written by C. Striebel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-29 with Business & Economics categories.
Optimal Control Of Discrete Time Stochastic Systems
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Author : Charlotte Striebel
language : en
Publisher: Springer
Release Date : 1975
Optimal Control Of Discrete Time Stochastic Systems written by Charlotte Striebel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1975 with Commande, Théorie de la categories.
Control And System Theory Of Discrete Time Stochastic Systems
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Author : Jan H. van Schuppen
language : en
Publisher: Springer Nature
Release Date : 2021-08-02
Control And System Theory Of Discrete Time Stochastic Systems written by Jan H. van Schuppen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-02 with Technology & Engineering categories.
This book helps students, researchers, and practicing engineers to understand the theoretical framework of control and system theory for discrete-time stochastic systems so that they can then apply its principles to their own stochastic control systems and to the solution of control, filtering, and realization problems for such systems. Applications of the theory in the book include the control of ships, shock absorbers, traffic and communications networks, and power systems with fluctuating power flows. The focus of the book is a stochastic control system defined for a spectrum of probability distributions including Bernoulli, finite, Poisson, beta, gamma, and Gaussian distributions. The concepts of observability and controllability of a stochastic control system are defined and characterized. Each output process considered is, with respect to conditions, represented by a stochastic system called a stochastic realization. The existence of a control law is related to stochastic controllability while the existence of a filter system is related to stochastic observability. Stochastic control with partial observations is based on the existence of a stochastic realization of the filtration of the observed process.
Discrete Time Stochastic Systems
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Author : Torsten Söderström
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-07-26
Discrete Time Stochastic Systems written by Torsten Söderström and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-07-26 with Mathematics categories.
This comprehensive introduction to the estimation and control of dynamic stochastic systems provides complete derivations of key results. The second edition includes improved and updated material, and a new presentation of polynomial control and new derivation of linear-quadratic-Gaussian control.
Linear Stochastic Control Systems
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Author : Goong Chen
language : en
Publisher: CRC Press
Release Date : 1995-07-12
Linear Stochastic Control Systems written by Goong Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-07-12 with Business & Economics categories.
Linear Stochastic Control Systems presents a thorough description of the mathematical theory and fundamental principles of linear stochastic control systems. Both continuous-time and discrete-time systems are thoroughly covered. Reviews of the modern probability and random processes theories and the Itô stochastic differential equations are provided. Discrete-time stochastic systems theory, optimal estimation and Kalman filtering, and optimal stochastic control theory are studied in detail. A modern treatment of these same topics for continuous-time stochastic control systems is included. The text is written in an easy-to-understand style, and the reader needs only to have a background of elementary real analysis and linear deterministic systems theory to comprehend the subject matter. This graduate textbook is also suitable for self-study, professional training, and as a handy research reference. Linear Stochastic Control Systems is self-contained and provides a step-by-step development of the theory, with many illustrative examples, exercises, and engineering applications.
Discrete Time Stochastic Systems
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Author : Torsten Söderström
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Discrete Time Stochastic Systems written by Torsten Söderström and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
This comprehensive introduction to the estimation and control of dynamic stochastic systems provides complete derivations of key results. The second edition includes improved and updated material, and a new presentation of polynomial control and new derivation of linear-quadratic-Gaussian control.
Optimization Of Stochastic Systems
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Author : Masanao Aoki
language : en
Publisher: Elsevier
Release Date : 2016-06-03
Optimization Of Stochastic Systems written by Masanao Aoki and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-03 with Technology & Engineering categories.
Optimization of Stochastic Systems
Optimal Control Of A Discrete Time Stochastic System Linear In The State
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Author : Joseph L. Midler
language : en
Publisher:
Release Date : 1968
Optimal Control Of A Discrete Time Stochastic System Linear In The State written by Joseph L. Midler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1968 with Decision making categories.
Considered is a discrete-time stochastic control problem whose dynamic equations and loss function are linear in the state vector with random coefficients, but which may vary in a nonlinear, random manner with the control variables. The controls are constrained to lie in a given set. For this system it is shown that the optimal control or policy is independent of the value of the state. The result follows from a simple dynamic programming argument. Under suitable restrictions on the functions, the dynamic programming approach leads to efficient computational methods for obtaining the controls via a sequence of mathematical programming problems in fewer variables than the number of controls in the entire process. The result provides another instance of certainty equivalence for a sequential stochastic decision problem. The expectations of the random variables play the role of certainty equivalents in the sense that the optimal control can be found by solving a deterministic problem in which expectations replace the random quantities.
An Introduction To Optimal Control Theory
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Author : Onésimo Hernández-Lerma
language : en
Publisher: Springer Nature
Release Date : 2023-02-21
An Introduction To Optimal Control Theory written by Onésimo Hernández-Lerma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-21 with Mathematics categories.
This book introduces optimal control problems for large families of deterministic and stochastic systems with discrete or continuous time parameter. These families include most of the systems studied in many disciplines, including Economics, Engineering, Operations Research, and Management Science, among many others. The main objective is to give a concise, systematic, and reasonably self contained presentation of some key topics in optimal control theory. To this end, most of the analyses are based on the dynamic programming (DP) technique. This technique is applicable to almost all control problems that appear in theory and applications. They include, for instance, finite and infinite horizon control problems in which the underlying dynamic system follows either a deterministic or stochastic difference or differential equation. In the infinite horizon case, it also uses DP to study undiscounted problems, such as the ergodic or long-run average cost. After a general introduction to control problems, the book covers the topic dividing into four parts with different dynamical systems: control of discrete-time deterministic systems, discrete-time stochastic systems, ordinary differential equations, and finally a general continuous-time MCP with applications for stochastic differential equations. The first and second part should be accessible to undergraduate students with some knowledge of elementary calculus, linear algebra, and some concepts from probability theory (random variables, expectations, and so forth). Whereas the third and fourth part would be appropriate for advanced undergraduates or graduate students who have a working knowledge of mathematical analysis (derivatives, integrals, ...) and stochastic processes.
Mathematical Methods In Robust Control Of Discrete Time Linear Stochastic Systems
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Author : Vasile Dragan
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-11-10
Mathematical Methods In Robust Control Of Discrete Time Linear Stochastic Systems written by Vasile Dragan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-11-10 with Mathematics categories.
In this monograph the authors develop a theory for the robust control of discrete-time stochastic systems, subjected to both independent random perturbations and to Markov chains. Such systems are widely used to provide mathematical models for real processes in fields such as aerospace engineering, communications, manufacturing, finance and economy. The theory is a continuation of the authors’ work presented in their previous book entitled "Mathematical Methods in Robust Control of Linear Stochastic Systems" published by Springer in 2006. Key features: - Provides a common unifying framework for discrete-time stochastic systems corrupted with both independent random perturbations and with Markovian jumps which are usually treated separately in the control literature; - Covers preliminary material on probability theory, independent random variables, conditional expectation and Markov chains; - Proposes new numerical algorithms to solve coupled matrix algebraic Riccati equations; - Leads the reader in a natural way to the original results through a systematic presentation; - Presents new theoretical results with detailed numerical examples. The monograph is geared to researchers and graduate students in advanced control engineering, applied mathematics, mathematical systems theory and finance. It is also accessible to undergraduate students with a fundamental knowledge in the theory of stochastic systems.