Identification and Stochastic Adaptive Control

Identification and Stochastic Adaptive Control PDF Author: Han-fu Chen
Publisher: Springer Science & Business Media
ISBN: 1461204291
Category : Science
Languages : en
Pages : 436

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Book Description
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.

Identification and Stochastic Adaptive Control

Identification and Stochastic Adaptive Control PDF Author: Han-fu Chen
Publisher: Springer Science & Business Media
ISBN: 1461204291
Category : Science
Languages : en
Pages : 436

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Book Description
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.

Stochastic Systems

Stochastic Systems PDF Author: P. R. Kumar
Publisher: SIAM
ISBN: 1611974267
Category : Mathematics
Languages : en
Pages : 371

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Book Description
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.?

Identification and Stochastic Adaptive Control

Identification and Stochastic Adaptive Control PDF Author: Hanfu Chen
Publisher:
ISBN: 9783764335977
Category : Adaptive control systems
Languages : en
Pages : 435

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Book Description


Stochastic Systems: Estimation Identification and Adaptive Control

Stochastic Systems: Estimation Identification and Adaptive Control PDF Author: Kumar P R
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description


Adaptive Control

Adaptive Control PDF Author: Karl J. Åström
Publisher: Courier Corporation
ISBN: 0486319148
Category : Technology & Engineering
Languages : en
Pages : 596

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Book Description
Suitable for advanced undergraduates and graduate students, this text introduces theoretical and practical aspects of adaptive control. It offers an excellent perspective on techniques as well as an active knowledge of key approaches. Readers will acquire a well-developed sense of when to use adaptive techniques and when other methods are more appropriate. Starting with a broad overview, the text explores real-time estimation, self-tuning regulators and model-reference adaptive systems, stochastic adaptive control, and automatic tuning of regulators. Additional topics include gain scheduling, robust high-gain control and self-oscillating controllers, and suggestions for implementing adaptive controllers. Concluding chapters feature a summary of applications and a brief review of additional areas closely related to adaptive control. Both authors are Professors at the Lund Institute of Technology in Sweden, and this text has evolved from their many years of research and teaching. Their insights into properties, design procedures, and implementation of adaptive controllers are complemented by the numerous examples, simulations, and problems that appear throughout the book.

Topics in Stochastic Systems: Modelling, Estimation and Adaptive Control

Topics in Stochastic Systems: Modelling, Estimation and Adaptive Control PDF Author: L. Gerencser
Publisher: Springer
ISBN: 9783540541332
Category : Technology & Engineering
Languages : en
Pages : 405

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Book Description
This book contains a collection of survey papers in the areas of modelling, estimation and adaptive control of stochastic systems describing recent efforts to develop a systematic and elegant theory of identification and adaptive control. It is meant to provide a fast introduction to some of the recent achievements. The book is intended for graduate students and researchers interested in statistical problems of control in general. Students in robotics and communication will also find it valuable. Readers are expected to be familiar with the fundamentals of probability theory and stochastic processes.

Stochastic Theory and Adaptive Control

Stochastic Theory and Adaptive Control PDF Author: T.E. Duncan
Publisher: Springer
ISBN: 9783540559627
Category : Technology & Engineering
Languages : en
Pages : 506

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Book Description
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.

Linear Stochastic Systems

Linear Stochastic Systems PDF Author: Peter E. Caines
Publisher: SIAM
ISBN: 1611974704
Category : Mathematics
Languages : en
Pages : 892

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Book Description
Linear Stochastic Systems, originally published in 1988, is today as comprehensive a reference to the theory of linear discrete-time-parameter systems as ever. Its most outstanding feature is the unified presentation, including both input-output and state space representations of stochastic linear systems, together with their interrelationships. The author first covers the foundations of linear stochastic systems and then continues through to more sophisticated topics including the fundamentals of stochastic processes and the construction of stochastic systems; an integrated exposition of the theories of prediction, realization (modeling), parameter estimation, and control; and a presentation of stochastic adaptive control theory. Written in a clear, concise manner and accessible to graduate students, researchers, and teachers, this classic volume also includes background material to make it self-contained and has complete proofs for all the principal results of the book. Furthermore, this edition includes many corrections of errata collected over the years.

Adaptive Filtering Prediction and Control

Adaptive Filtering Prediction and Control PDF Author: Graham C Goodwin
Publisher: Courier Corporation
ISBN: 0486137724
Category : Technology & Engineering
Languages : en
Pages : 562

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Book Description
This unified survey focuses on linear discrete-time systems and explores natural extensions to nonlinear systems. It emphasizes discrete-time systems, summarizing theoretical and practical aspects of a large class of adaptive algorithms. 1984 edition.

Stochastic Adaptive Control Results and Simulations

Stochastic Adaptive Control Results and Simulations PDF Author: Alexis Aloneftis
Publisher: Springer
ISBN: 9783662177983
Category : Technology & Engineering
Languages : en
Pages : 125

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Book Description
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.