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Markov Processes In Adaptive Control
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Author :Onesimo Hernandez-Lerma Publisher :Springer Science & Business Media ISBN 13 :1441987142 Total Pages :160 pages Book Rating :4.4/5 (419 download)
Book Synopsis Adaptive Markov Control Processes by : Onesimo Hernandez-Lerma
Download or read book Adaptive Markov Control Processes written by Onesimo Hernandez-Lerma and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is concerned with a class of discrete-time stochastic control processes known as controlled Markov processes (CMP's), also known as Markov decision processes or Markov dynamic programs. Starting in the mid-1950swith Richard Bellman, many contributions to CMP's have been made, and applications to engineering, statistics and operations research, among other areas, have also been developed. The purpose of this book is to present some recent developments on the theory of adaptive CMP's, i. e. , CMP's that depend on unknown parameters. Thus at each decision time, the controller or decision-maker must estimate the true parameter values, and then adapt the control actions to the estimated values. We do not intend to describe all aspects of stochastic adaptive control; rather, the selection of material reflects our own research interests. The prerequisite for this book is a knowledgeof real analysis and prob ability theory at the level of, say, Ash (1972) or Royden (1968), but no previous knowledge of control or decision processes is required. The pre sentation, on the other hand, is meant to beself-contained,in the sensethat whenever a result from analysisor probability is used, it is usually stated in full and references are supplied for further discussion, if necessary. Several appendices are provided for this purpose. The material is divided into six chapters. Chapter 1 contains the basic definitions about the stochastic control problems we are interested in; a brief description of some applications is also provided.
Book Synopsis Markov Processes in Adaptive Control by : D. Longley
Download or read book Markov Processes in Adaptive Control written by D. Longley and published by . This book was released on 1967 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Mathematical Theory of Adaptive Control by : Vladimir Grigor?evich Sragovich
Download or read book Mathematical Theory of Adaptive Control written by Vladimir Grigor?evich Sragovich and published by World Scientific. This book was released on 2006 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theory of adaptive control is concerned with construction of strategies so that the controlled system behaves in a desirable way, without assuming the complete knowledge of the system. The models considered in this comprehensive book are of Markovian type. Both partial observation and partial information cases are analyzed. While the book focuses on discrete time models, continuous time ones are considered in the final chapter. The book provides a novel perspective by summarizing results on adaptive control obtained in the Soviet Union, which are not well known in the West. Comments on the interplay between the Russian and Western methods are also included.
Download or read book Stochastic Systems written by P. R. Kumar and published by SIAM. This book was released on 2015-12-15 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics.?
Book Synopsis Adaptive Markov Control Processes by : Onésimo Hernández-Lerma
Download or read book Adaptive Markov Control Processes written by Onésimo Hernández-Lerma and published by . This book was released on 1989 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Controlled Markov processes on the infinite planning horizon by : Emmanuel Fernández-Gaucherand
Download or read book Controlled Markov processes on the infinite planning horizon written by Emmanuel Fernández-Gaucherand and published by . This book was released on 1991 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Self-Learning Control of Finite Markov Chains by : A.S. Poznyak
Download or read book Self-Learning Control of Finite Markov Chains written by A.S. Poznyak and published by CRC Press. This book was released on 2018-10-03 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a number of new and potentially useful self-learning (adaptive) control algorithms and theoretical as well as practical results for both unconstrained and constrained finite Markov chains-efficiently processing new information by adjusting the control strategies directly or indirectly.
Book Synopsis Adaptive Control Processes by : Richard E. Bellman
Download or read book Adaptive Control Processes written by Richard E. Bellman and published by Princeton University Press. This book was released on 2015-12-08 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this work is to present a unified approach to the modern field of control theory and to provide a technique for making problems involving deterministic, stochastic, and adaptive processes of both linear and nonlinear type amenable to machine solution. Mr. Bellman has used the theory of dynamic programming to formulate, analyze, and prepare these processes for numerical treatment by digital computers. The unique concept of the book is that of a single problem stretching from recognition and formulation to analytic treatment and computational solution. Due to the emphasis upon ideas and concepts, this book is equally suited for the pure and applied mathematician, and for control engineers in all fields. Originally published in 1961. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Book Synopsis Adaptive control of discrete state Markov processes by : John Spruce Riordon
Download or read book Adaptive control of discrete state Markov processes written by John Spruce Riordon and published by . This book was released on 1967 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Identification and Adaptive Control of Markov Chains by : Vivek Shripad Borkar
Download or read book Identification and Adaptive Control of Markov Chains written by Vivek Shripad Borkar and published by . This book was released on 1980 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Stochastic Adaptive Control Results and Simulations by : Alexis Aloneftis
Download or read book Stochastic Adaptive Control Results and Simulations written by Alexis Aloneftis and published by Springer. This book was released on 1987 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theme of this monograph is the adaptive control of systems in a stochastic environment and, more precisely, the study of the tracking problem for ARMAX SISO stochastic systems with time invariant and time varying parameters. Results of simultaneous tracking and parameter identification are included. The author has aimed to (1) provide a reasonably self-contained and up-to-date exposition of the tracking problem after having properly placed it amongst numerous ideas, approaches, and subproblems related to adaptive control, (2) display computer simulation results and discuss their comparative behaviour, (3) introduce a new approach to the stochastic adaptive control with promising results, and (4) qualitatively discuss the adaptive control problem in the hope of improving our understanding of it, stimulate the informed reader to come up with new ideas, and attract newcomers to its study. The reader is assumed to have studied control systems at the graduate level and to have a reasonably good grasp of basic probability theory. Apart from its educational value to the adaptive control student, it is hoped that the accumulation of scattered results and their computer simulation, as well as an extensive reference section will attract the active researcher in this field.
Book Synopsis Adaptive Control of Markov Chains by : Rodolfo Alberto Milito
Download or read book Adaptive Control of Markov Chains written by Rodolfo Alberto Milito and published by . This book was released on 1985 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimal Adaptive Control for Markov Chains and Auto Regressive Moving Average Processes by : Arthur H. Becker
Download or read book Optimal Adaptive Control for Markov Chains and Auto Regressive Moving Average Processes written by Arthur H. Becker and published by . This book was released on 1984 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Cont Markov Chains written by Borkar and published by CRC Press. This book was released on 1991-04-30 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a novel treatment of many problems in controlled Markov chains based on occupation measures and convex analysis. Includes a rederivation of many classical results, a general treatment of the ergodic control problems and an extensive study of the asymptotic behavior of the self-tuning adaptive controller and its variant, the Kumar-Becker-Lin scheme. Also includes a novel treatment of some multiobjective control problems, inaccessible to traditional methods. Annotation copyrighted by Book News, Inc., Portland, OR
Book Synopsis Stochastic Theory and Adaptive Control by : T. E. Duncan
Download or read book Stochastic Theory and Adaptive Control written by T. E. Duncan and published by Springer. This book was released on 1992 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: This workshop on stochastic theory and adaptive control assembled many of the leading researchers on stochastic control and stochastic adaptive control to increase scientific exchange and cooperative research between these two subfields of stochastic analysis. The papers included in the proceedings include survey and research. They describe both theoretical results and applications of adaptive control. There are theoretical results in identification, filtering, control, adaptive control and various other related topics. Some applications to manufacturing systems, queues, networks, medicine and other topics are gien.
Book Synopsis Identification and Stochastic Adaptive Control by : Han-fu Chen
Download or read book Identification and Stochastic Adaptive Control written by Han-fu Chen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Identifying the input-output relationship of a system or discovering the evolutionary law of a signal on the basis of observation data, and applying the constructed mathematical model to predicting, controlling or extracting other useful information constitute a problem that has been drawing a lot of attention from engineering and gaining more and more importance in econo metrics, biology, environmental science and other related areas. Over the last 30-odd years, research on this problem has rapidly developed in various areas under different terms, such as time series analysis, signal processing and system identification. Since the randomness almost always exists in real systems and in observation data, and since the random process is sometimes used to model the uncertainty in systems, it is reasonable to consider the object as a stochastic system. In some applications identification can be carried out off line, but in other cases this is impossible, for example, when the structure or the parameter of the system depends on the sample, or when the system is time-varying. In these cases we have to identify the system on line and to adjust the control in accordance with the model which is supposed to be approaching the true system during the process of identification. This is why there has been an increasing interest in identification and adaptive control for stochastic systems from both theorists and practitioners.
Book Synopsis Markov Processes and Controlled Markov Chains by : Zhenting Hou
Download or read book Markov Processes and Controlled Markov Chains written by Zhenting Hou and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: The general theory of stochastic processes and the more specialized theory of Markov processes evolved enormously in the second half of the last century. In parallel, the theory of controlled Markov chains (or Markov decision processes) was being pioneered by control engineers and operations researchers. Researchers in Markov processes and controlled Markov chains have been, for a long time, aware of the synergies between these two subject areas. However, this may be the first volume dedicated to highlighting these synergies and, almost certainly, it is the first volume that emphasizes the contributions of the vibrant and growing Chinese school of probability. The chapters that appear in this book reflect both the maturity and the vitality of modern day Markov processes and controlled Markov chains. They also will provide an opportunity to trace the connections that have emerged between the work done by members of the Chinese school of probability and the work done by the European, US, Central and South American and Asian scholars.
