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Author : C. Striebel
Publisher : Springer
ISBN 13 : 3642454704
Total Pages : 215 pages
Book Rating : 4.6/5 (424 download)
Download or read book Optimal Control of Discrete Time Stochastic Systems written by C. Striebel and published by Springer. This book was released on 2013-12-21 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Torsten Söderström
Publisher : Springer Science & Business Media
ISBN 13 : 9781852336493
Total Pages : 410 pages
Book Rating : 4.3/5 (364 download)
Download or read book Discrete-time Stochastic Systems written by Torsten Söderström and published by Springer Science & Business Media. This book was released on 2002-07-26 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Charlotte Striebel
Publisher : Springer
ISBN 13 : 9780387071817
Total Pages : 0 pages
Book Rating : 4.0/5 (718 download)
Download or read book Optimal Control of Discrete Time Stochastic Systems written by Charlotte Striebel and published by Springer. This book was released on 1975 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Vasile Dragan
Publisher : Springer Science & Business Media
ISBN 13 : 1441906304
Total Pages : 349 pages
Book Rating : 4.4/5 (419 download)
Download or read book Mathematical Methods in Robust Control of Discrete-Time Linear Stochastic Systems written by Vasile Dragan and published by Springer Science & Business Media. This book was released on 2009-11-10 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Atle Seierstad
Publisher : Springer Science & Business Media
ISBN 13 : 0387766170
Total Pages : 299 pages
Book Rating : 4.3/5 (877 download)
Download or read book Stochastic Control in Discrete and Continuous Time written by Atle Seierstad and published by Springer Science & Business Media. This book was released on 2010-07-03 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains an introduction to three topics in stochastic control: discrete time stochastic control, i. e. , stochastic dynamic programming (Chapter 1), piecewise - terministic control problems (Chapter 3), and control of Ito diffusions (Chapter 4). The chapters include treatments of optimal stopping problems. An Appendix - calls material from elementary probability theory and gives heuristic explanations of certain more advanced tools in probability theory. The book will hopefully be of interest to students in several ?elds: economics, engineering, operations research, ?nance, business, mathematics. In economics and business administration, graduate students should readily be able to read it, and the mathematical level can be suitable for advanced undergraduates in mathem- ics and science. The prerequisites for reading the book are only a calculus course and a course in elementary probability. (Certain technical comments may demand a slightly better background. ) As this book perhaps (and hopefully) will be read by readers with widely diff- ing backgrounds, some general advice may be useful: Don’t be put off if paragraphs, comments, or remarks contain material of a seemingly more technical nature that you don’t understand. Just skip such material and continue reading, it will surely not be needed in order to understand the main ideas and results. The presentation avoids the use of measure theory.
Author : Dimitri P. Bertsekas
Publisher :
ISBN 13 : 9780120932603
Total Pages : 323 pages
Book Rating : 4.9/5 (326 download)
Download or read book Stochastic Optimal Control written by Dimitri P. Bertsekas and published by . This book was released on 1961 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jan H. van Schuppen
Publisher : Springer Nature
ISBN 13 : 3030669521
Total Pages : 940 pages
Book Rating : 4.0/5 (36 download)
Download or read book Control and System Theory of Discrete-Time Stochastic Systems written by Jan H. van Schuppen and published by Springer Nature. This book was released on 2021-08-02 with total page 940 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Goong Chen
Publisher : CRC Press
ISBN 13 : 9780849380754
Total Pages : 404 pages
Book Rating : 4.3/5 (87 download)
Download or read book Linear Stochastic Control Systems written by Goong Chen and published by CRC Press. This book was released on 1995-07-12 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Masanao Aoki
Publisher : Elsevier
ISBN 13 : 1483224058
Total Pages : 372 pages
Book Rating : 4.4/5 (832 download)
Download or read book Optimization of Stochastic Systems written by Masanao Aoki and published by Elsevier. This book was released on 2016-06-03 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization of Stochastic Systems
Author : Dimitri P. Bertsekas
Publisher :
ISBN 13 : 9781886529267
Total Pages : 543 pages
Book Rating : 4.5/5 (292 download)
Download or read book Dynamic Programming and Optimal Control written by Dimitri P. Bertsekas and published by . This book was released on 2005 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The leading and most up-to-date textbook on the far-ranging algorithmic methododogy of Dynamic Programming, which can be used for optimal control, Markovian decision problems, planning and sequential decision making under uncertainty, and discrete/combinatorial optimization. The treatment focuses on basic unifying themes, and conceptual foundations. It illustrates the versatility, power, and generality of the method with many examples and applications from engineering, operations research, and other fields. It also addresses extensively the practical application of the methodology, possibly through the use of approximations, and provides an extensive treatment of the far-reaching methodology of Neuro-Dynamic Programming/Reinforcement Learning. The first volume is oriented towards modeling, conceptualization, and finite-horizon problems, but also includes a substantive introduction to infinite horizon problems that is suitable for classroom use. The second volume is oriented towards mathematical analysis and computation, treats infinite horizon problems extensively, and provides an up-to-date account of approximate large-scale dynamic programming and reinforcement learning. The text contains many illustrations, worked-out examples, and exercises."--Publisher's website.
Author : O.L.V. Costa
Publisher : Springer Science & Business Media
ISBN 13 : 1846280826
Total Pages : 287 pages
Book Rating : 4.8/5 (462 download)
Download or read book Discrete-Time Markov Jump Linear Systems written by O.L.V. Costa and published by Springer Science & Business Media. This book was released on 2006-03-30 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: This will be the most up-to-date book in the area (the closest competition was published in 1990) This book takes a new slant and is in discrete rather than continuous time
Author : Torsten Söderström
Publisher : Springer Science & Business Media
ISBN 13 : 1447101014
Total Pages : 376 pages
Book Rating : 4.4/5 (471 download)
Download or read book Discrete-time Stochastic Systems written by Torsten Söderström and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Joseph L. Midler
Publisher :
ISBN 13 :
Total Pages : 462 pages
Book Rating : 4.F/5 ( download)
Download or read book Optimal Control of a Discrete Time Stochastic System Linear in the State written by Joseph L. Midler and published by . This book was released on 1968 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Y. Murata
Publisher : Springer Science & Business Media
ISBN 13 : 1461257379
Total Pages : 210 pages
Book Rating : 4.4/5 (612 download)
Download or read book Optimal Control Methods for Linear Discrete-Time Economic Systems written by Y. Murata and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: As our title reveals, we focus on optimal control methods and applications relevant to linear dynamic economic systems in discrete-time variables. We deal only with discrete cases simply because economic data are available in discrete forms, hence realistic economic policies should be established in discrete-time structures. Though many books have been written on optimal control in engineering, we see few on discrete-type optimal control. More over, since economic models take slightly different forms than do engineer ing ones, we need a comprehensive, self-contained treatment of linear optimal control applicable to discrete-time economic systems. The present work is intended to fill this need from the standpoint of contemporary macroeconomic stabilization. The work is organized as follows. In Chapter 1 we demonstrate instru ment instability in an economic stabilization problem and thereby establish the motivation for our departure into the optimal control world. Chapter 2 provides fundamental concepts and propositions for controlling linear deterministic discrete-time systems, together with some economic applica tions and numerical methods. Our optimal control rules are in the form of feedback from known state variables of the preceding period. When state variables are not observable or are accessible only with observation errors, we must obtain appropriate proxies for these variables, which are called "observers" in deterministic cases or "filters" in stochastic circumstances. In Chapters 3 and 4, respectively, Luenberger observers and Kalman filters are discussed, developed, and applied in various directions. Noticing that a separation principle lies between observer (or filter) and controller (cf.
Author : Joël Blot
Publisher : Springer Science & Business Media
ISBN 13 : 1461490383
Total Pages : 130 pages
Book Rating : 4.4/5 (614 download)
Download or read book Infinite-Horizon Optimal Control in the Discrete-Time Framework written by Joël Blot and published by Springer Science & Business Media. This book was released on 2013-11-08 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book the authors take a rigorous look at the infinite-horizon discrete-time optimal control theory from the viewpoint of Pontryagin’s principles. Several Pontryagin principles are described which govern systems and various criteria which define the notions of optimality, along with a detailed analysis of how each Pontryagin principle relate to each other. The Pontryagin principle is examined in a stochastic setting and results are given which generalize Pontryagin’s principles to multi-criteria problems. Infinite-Horizon Optimal Control in the Discrete-Time Framework is aimed toward researchers and PhD students in various scientific fields such as mathematics, applied mathematics, economics, management, sustainable development (such as, of fisheries and of forests), and Bio-medical sciences who are drawn to infinite-horizon discrete-time optimal control problems.
Author : Pierre Carpentier
Publisher : Springer
ISBN 13 : 3319181386
Total Pages : 362 pages
Book Rating : 4.3/5 (191 download)
Download or read book Stochastic Multi-Stage Optimization written by Pierre Carpentier and published by Springer. This book was released on 2015-05-05 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the related discretization issues. There is a growing need to tackle uncertainty in applications of optimization. For example the massive introduction of renewable energies in power systems challenges traditional ways to manage them. This book lays out basic and advanced tools to handle and numerically solve such problems and thereby is building a bridge between Stochastic Programming and Stochastic Control. It is intended for graduates readers and scholars in optimization or stochastic control, as well as engineers with a background in applied mathematics.
Author : Daniel Hernández-Hernández
Publisher : Springer Science & Business Media
ISBN 13 : 0817683372
Total Pages : 331 pages
Book Rating : 4.8/5 (176 download)
Download or read book Optimization, Control, and Applications of Stochastic Systems written by Daniel Hernández-Hernández and published by Springer Science & Business Media. This book was released on 2012-08-15 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a general overview of discrete- and continuous-time Markov control processes and stochastic games, along with a look at the range of applications of stochastic control and some of its recent theoretical developments. These topics include various aspects of dynamic programming, approximation algorithms, and infinite-dimensional linear programming. In all, the work comprises 18 carefully selected papers written by experts in their respective fields. Optimization, Control, and Applications of Stochastic Systems will be a valuable resource for all practitioners, researchers, and professionals in applied mathematics and operations research who work in the areas of stochastic control, mathematical finance, queueing theory, and inventory systems. It may also serve as a supplemental text for graduate courses in optimal control and dynamic games.
