Stochastic Theory And Adaptive Control
Download Stochastic Theory And Adaptive Control full books in PDF, epub, and Kindle. Read online free Stochastic Theory And Adaptive Control ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Han-fu Chen |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 436 |
| Release | : 2012-12-06 |
| Genre | : Science |
| ISBN | : 1461204291 |
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.
| Author | : P. R. Kumar |
| Publisher | : SIAM |
| Total Pages | : 371 |
| Release | : 2015-12-15 |
| Genre | : Mathematics |
| ISBN | : 1611974259 |
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.
| Author | : Vladimir G. Sragovich |
| Publisher | : World Scientific |
| Total Pages | : 490 |
| Release | : 2006 |
| Genre | : Mathematics |
| ISBN | : 9812701036 |
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.
| Author | : Karl J. Åström |
| Publisher | : Courier Corporation |
| Total Pages | : 596 |
| Release | : 2013-04-26 |
| Genre | : Technology & Engineering |
| ISBN | : 0486319148 |
Suitable for advanced undergraduates and graduate students, this overview introduces theoretical and practical aspects of adaptive control, with emphasis on deterministic and stochastic viewpoints. 1995 edition.
| Author | : Graham C Goodwin |
| Publisher | : Courier Corporation |
| Total Pages | : 562 |
| Release | : 2014-05-05 |
| Genre | : Technology & Engineering |
| ISBN | : 0486137724 |
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.
| Author | : Petros Ioannou |
| Publisher | : Courier Corporation |
| Total Pages | : 850 |
| Release | : 2013-09-26 |
| Genre | : Technology & Engineering |
| ISBN | : 0486320723 |
Presented in a tutorial style, this comprehensive treatment unifies, simplifies, and explains most of the techniques for designing and analyzing adaptive control systems. Numerous examples clarify procedures and methods. 1995 edition.
| Author | : Vladimir Grigor?evich Sragovich |
| Publisher | : World Scientific |
| Total Pages | : 490 |
| Release | : 2006 |
| Genre | : Technology & Engineering |
| ISBN | : 9812563717 |
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.
| Author | : T.E. Duncan |
| Publisher | : Springer |
| Total Pages | : 506 |
| Release | : 1992-11-27 |
| Genre | : Technology & Engineering |
| ISBN | : 9783540559627 |
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.
| Author | : Albert Benveniste |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 373 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 3642758940 |
Adaptive systems are widely encountered in many applications ranging through adaptive filtering and more generally adaptive signal processing, systems identification and adaptive control, to pattern recognition and machine intelligence: adaptation is now recognised as keystone of "intelligence" within computerised systems. These diverse areas echo the classes of models which conveniently describe each corresponding system. Thus although there can hardly be a "general theory of adaptive systems" encompassing both the modelling task and the design of the adaptation procedure, nevertheless, these diverse issues have a major common component: namely the use of adaptive algorithms, also known as stochastic approximations in the mathematical statistics literature, that is to say the adaptation procedure (once all modelling problems have been resolved). The juxtaposition of these two expressions in the title reflects the ambition of the authors to produce a reference work, both for engineers who use these adaptive algorithms and for probabilists or statisticians who would like to study stochastic approximations in terms of problems arising from real applications. Hence the book is organised in two parts, the first one user-oriented, and the second providing the mathematical foundations to support the practice described in the first part. The book covers the topcis of convergence, convergence rate, permanent adaptation and tracking, change detection, and is illustrated by various realistic applications originating from these areas of applications.
| Author | : Hong Wang |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 196 |
| Release | : 2000-02-25 |
| Genre | : Technology & Engineering |
| ISBN | : 9781852331870 |
Over the past decades, although stochastic system control has been studied intensively within the field of control engineering, all the modelling and control strategies developed so far have concentrated on the performance of one or two output properties of the system. such as minimum variance control and mean value control. The general assumption used in the formulation of modelling and control strategies is that the distribution of the random signals involved is Gaussian. In this book, a set of new approaches for the control of the output probability density function of stochastic dynamic systems (those subjected to any bounded random inputs), has been developed. In this context, the purpose of control system design becomes the selection of a control signal that makes the shape of the system outputs p.d.f. as close as possible to a given distribution. The book contains material on the subjects of: - Control of single-input single-output and multiple-input multiple-output stochastic systems; - Stable adaptive control of stochastic distributions; - Model reference adaptive control; - Control of nonlinear dynamic stochastic systems; - Condition monitoring of bounded stochastic distributions; - Control algorithm design; - Singular stochastic systems. A new representation of dynamic stochastic systems is produced by using B-spline functions to descripe the output p.d.f. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
