System Identification and Adaptive Control

System Identification and Adaptive Control

Author: Yiannis Boutalis

Publisher: Springer Science & Business

Published: 2014-04-23

Total Pages: 316

ISBN-13: 3319063642

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Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.


Book Synopsis System Identification and Adaptive Control by : Yiannis Boutalis

Download or read book System Identification and Adaptive Control written by Yiannis Boutalis and published by Springer Science & Business. This book was released on 2014-04-23 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.

System Identification for Self-adaptive Control

System Identification for Self-adaptive Control

Author: W. D. T. Davies

Publisher: John Wiley & Sons

Published: 1970

Total Pages: 404

ISBN-13:

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Book Synopsis System Identification for Self-adaptive Control by : W. D. T. Davies

Download or read book System Identification for Self-adaptive Control written by W. D. T. Davies and published by John Wiley & Sons. This book was released on 1970 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt:

System Identification and Adaptive Control

System Identification and Adaptive Control

Author: Bahram Shafai

Publisher: Springer

Published: 2012-04-30

Total Pages: 500

ISBN-13: 9781461432029

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This book offers comprehensive coverage of identification and adaptive control while familiarizing graduate students and practicing engineers with computational software tools such as MATLAB and SIMULINK and describing the underlying theoretical concepts. Identification is the process of mathematically modeling a system based on measurement data that may be limited or uncertain. Adaptive control is the means whereby a system that is poorly modeled is controlled adequately. Therefore the topical coverage is divided into two parts: Part I describes fundamental topics of system identification independent of adaptive control and discusses nonparametric and parameteric estimation methods while emphasizing least squares techniques instrumental variables and prediction error methods. Part II describes various methods of adaptive control in which the materials discussed in Part I are essential for control purposes, including model reference, adaptive control and self-tuning regulators.


Book Synopsis System Identification and Adaptive Control by : Bahram Shafai

Download or read book System Identification and Adaptive Control written by Bahram Shafai and published by Springer. This book was released on 2012-04-30 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers comprehensive coverage of identification and adaptive control while familiarizing graduate students and practicing engineers with computational software tools such as MATLAB and SIMULINK and describing the underlying theoretical concepts. Identification is the process of mathematically modeling a system based on measurement data that may be limited or uncertain. Adaptive control is the means whereby a system that is poorly modeled is controlled adequately. Therefore the topical coverage is divided into two parts: Part I describes fundamental topics of system identification independent of adaptive control and discusses nonparametric and parameteric estimation methods while emphasizing least squares techniques instrumental variables and prediction error methods. Part II describes various methods of adaptive control in which the materials discussed in Part I are essential for control purposes, including model reference, adaptive control and self-tuning regulators.

Adaptive Nonlinear System Identification

Adaptive Nonlinear System Identification

Author: Tokunbo Ogunfunmi

Publisher: Springer Science & Business Media

Published: 2007-09-05

Total Pages: 238

ISBN-13: 0387686304

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Focuses on System Identification applications of the adaptive methods presented. but which can also be applied to other applications of adaptive nonlinear processes. Covers recent research results in the area of adaptive nonlinear system identification from the authors and other researchers in the field.


Book Synopsis Adaptive Nonlinear System Identification by : Tokunbo Ogunfunmi

Download or read book Adaptive Nonlinear System Identification written by Tokunbo Ogunfunmi and published by Springer Science & Business Media. This book was released on 2007-09-05 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on System Identification applications of the adaptive methods presented. but which can also be applied to other applications of adaptive nonlinear processes. Covers recent research results in the area of adaptive nonlinear system identification from the authors and other researchers in the field.

Identification and Stochastic Adaptive Control

Identification and Stochastic Adaptive Control

Author: Han-fu Chen

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 436

ISBN-13: 1461204291

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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 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.

Stochastic Systems

Stochastic Systems

Author: P. R. Kumar

Publisher: SIAM

Published: 2015-12-15

Total Pages: 371

ISBN-13: 1611974259

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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 Stochastic Systems by : P. R. Kumar

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.

Fuzzy System Identification and Adaptive Control

Fuzzy System Identification and Adaptive Control

Author: Ruiyun Qi

Publisher:

Published: 2019

Total Pages: 282

ISBN-13: 9783030198831

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This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi-Sugeno (T-S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T-S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also: introduces basic concepts of fuzzy sets, logic and inference system; discusses important properties of T-S fuzzy systems; develops offline and online identification algorithms for T-S fuzzy systems; investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T-S fuzzy systems; develops adaptive control algorithms for discrete-time input-output form T-S fuzzy systems with much relaxed design conditions, and discrete-time state-space T-S fuzzy systems; and designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T-S fuzzy systems. The authors address adaptive fault compensation problems for T-S fuzzy systems subject to actuator faults. They cover a broad spectrum of related technical topics and to develop a substantial set of adaptive nonlinear system control tools. Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.


Book Synopsis Fuzzy System Identification and Adaptive Control by : Ruiyun Qi

Download or read book Fuzzy System Identification and Adaptive Control written by Ruiyun Qi and published by . This book was released on 2019 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi-Sugeno (T-S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T-S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also: introduces basic concepts of fuzzy sets, logic and inference system; discusses important properties of T-S fuzzy systems; develops offline and online identification algorithms for T-S fuzzy systems; investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T-S fuzzy systems; develops adaptive control algorithms for discrete-time input-output form T-S fuzzy systems with much relaxed design conditions, and discrete-time state-space T-S fuzzy systems; and designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T-S fuzzy systems. The authors address adaptive fault compensation problems for T-S fuzzy systems subject to actuator faults. They cover a broad spectrum of related technical topics and to develop a substantial set of adaptive nonlinear system control tools. Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.

Fuzzy System Identification and Adaptive Control

Fuzzy System Identification and Adaptive Control

Author: Ruiyun Qi

Publisher: Springer

Published: 2020-06-10

Total Pages: 0

ISBN-13: 9783030198848

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This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi–Sugeno (T–S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T–S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also: introduces basic concepts of fuzzy sets, logic and inference system; discusses important properties of T–S fuzzy systems; develops offline and online identification algorithms for T–S fuzzy systems; investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T–S fuzzy systems; develops adaptive control algorithms for discrete-time input–output form T–S fuzzy systems with much relaxed design conditions, and discrete-time state-space T–S fuzzy systems; and designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T–S fuzzy systems. The authors address adaptive fault compensation problems for T–S fuzzy systems subject to actuator faults. They cover a broad spectrum of related technical topics and to develop a substantial set of adaptive nonlinear system control tools. Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.


Book Synopsis Fuzzy System Identification and Adaptive Control by : Ruiyun Qi

Download or read book Fuzzy System Identification and Adaptive Control written by Ruiyun Qi and published by Springer. This book was released on 2020-06-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi–Sugeno (T–S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T–S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also: introduces basic concepts of fuzzy sets, logic and inference system; discusses important properties of T–S fuzzy systems; develops offline and online identification algorithms for T–S fuzzy systems; investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T–S fuzzy systems; develops adaptive control algorithms for discrete-time input–output form T–S fuzzy systems with much relaxed design conditions, and discrete-time state-space T–S fuzzy systems; and designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T–S fuzzy systems. The authors address adaptive fault compensation problems for T–S fuzzy systems subject to actuator faults. They cover a broad spectrum of related technical topics and to develop a substantial set of adaptive nonlinear system control tools. Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.

Robust and Adaptive Control

Robust and Adaptive Control

Author: Eugene Lavretsky

Publisher: Springer Nature

Published: 2023

Total Pages: 718

ISBN-13: 3031383141

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Zusammenfassung: Robust and Adaptive Control (second edition) shows readers how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications, the focus of the book is primarily on continuous-time dynamical systems. The two-part text begins with robust and optimal linear control methods and moves on to a self-contained presentation of the design and analysis of model reference adaptive control for nonlinear uncertain dynamical systems. Features of the second edition include: sufficient conditions for closed-loop stability under output feedback observer-based loop-transfer recovery (OBLTR) with adaptive augmentation; OBLTR applications to aerospace systems; case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; realistic examples and simulation data illustrating key features of the methods described; and problem solutions for instructors and MATLAB® code provided electronically. The theory and practical applications address real-life aerospace problems, being based on numerous transitions of control-theoretic results into operational systems and airborne vehicles drawn from the authors' extensive professional experience with The Boeing Company. The systems covered are challenging--often open-loop unstable with uncertainties in their dynamics--and thus require both persistently reliable control and the ability to track commands either from a pilot or a guidance computer. Readers should have a basic understanding of root locus, Bode diagrams, and Nyquist plots, as well as linear algebra, ordinary differential equations, and the use of state-space methods in analysis and modeling of dynamical systems. The second edition contains a background summary of linear systems and control systems and an introduction to state observers and output feedback control, helping to make it self-contained. Robust and Adaptive Control teaches senior undergraduate and graduate students how to construct stable and predictable control algorithms for realistic industrial applications. Practicing engineers and academic researchers will also find the book of great instructional value


Book Synopsis Robust and Adaptive Control by : Eugene Lavretsky

Download or read book Robust and Adaptive Control written by Eugene Lavretsky and published by Springer Nature. This book was released on 2023 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: Zusammenfassung: Robust and Adaptive Control (second edition) shows readers how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications, the focus of the book is primarily on continuous-time dynamical systems. The two-part text begins with robust and optimal linear control methods and moves on to a self-contained presentation of the design and analysis of model reference adaptive control for nonlinear uncertain dynamical systems. Features of the second edition include: sufficient conditions for closed-loop stability under output feedback observer-based loop-transfer recovery (OBLTR) with adaptive augmentation; OBLTR applications to aerospace systems; case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; realistic examples and simulation data illustrating key features of the methods described; and problem solutions for instructors and MATLAB® code provided electronically. The theory and practical applications address real-life aerospace problems, being based on numerous transitions of control-theoretic results into operational systems and airborne vehicles drawn from the authors' extensive professional experience with The Boeing Company. The systems covered are challenging--often open-loop unstable with uncertainties in their dynamics--and thus require both persistently reliable control and the ability to track commands either from a pilot or a guidance computer. Readers should have a basic understanding of root locus, Bode diagrams, and Nyquist plots, as well as linear algebra, ordinary differential equations, and the use of state-space methods in analysis and modeling of dynamical systems. The second edition contains a background summary of linear systems and control systems and an introduction to state observers and output feedback control, helping to make it self-contained. Robust and Adaptive Control teaches senior undergraduate and graduate students how to construct stable and predictable control algorithms for realistic industrial applications. Practicing engineers and academic researchers will also find the book of great instructional value

Adaptive Control

Adaptive Control

Author: Shankar Sastry

Publisher: Courier Corporation

Published: 2011-01-01

Total Pages: 402

ISBN-13: 0486482022

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This volume surveys the major results and techniques of analysis in the field of adaptive control. Focusing on linear, continuous time, single-input, single-output systems, the authors offer a clear, conceptual presentation of adaptive methods, enabling a critical evaluation of these techniques and suggesting avenues of further development. 1989 edition.


Book Synopsis Adaptive Control by : Shankar Sastry

Download or read book Adaptive Control written by Shankar Sastry and published by Courier Corporation. This book was released on 2011-01-01 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume surveys the major results and techniques of analysis in the field of adaptive control. Focusing on linear, continuous time, single-input, single-output systems, the authors offer a clear, conceptual presentation of adaptive methods, enabling a critical evaluation of these techniques and suggesting avenues of further development. 1989 edition.