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Intelligent control, filtering and model reduction analysis for fuzzy-model-based systems

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Intelligent control, filtering and model reduction analysis for fuzzy-model-based systemsby Xiaojie Su ... [et al.].
其他作者:	Su, Xiaojie.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	xxi, 313 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Fuzzy systems.
電子資源:	https://doi.org/10.1007/978-3-030-81214-0
ISBN:	9783030812140$q(electronic bk.)

Intelligent control, filtering and model reduction analysis for fuzzy-model-based systems
Intelligent control, filtering and model reduction analysis for fuzzy-model-based systems[electronic resource] /by Xiaojie Su ... [et al.]. - Cham :Springer International Publishing :2022. - xxi, 313 p. :ill. (some col.), digital ;24 cm. - Studies in systems, decision and control,v. 3852198-4190 ;. - Studies in systems, decision and control ;v.3..

Introduction -- Stabilization Synthesis of T-S Fuzzy Delayed Systems -- Output Feedback Control of Fuzzy Stochastic Systems -- Output Feedback Control of Fuzzy Switching Systems -- Dissipative Filtering of Fuzzy Switched Systems -- Fault Detection for Switched Stochastic Systems -- Reliable Filtering for T-S Fuzzy Time-Delay Systems -- Reduced-Order Model Approximation of Switched Systems -- Model Reduction of Time-Varying Delay Fuzzy Systems -- Model Approximation of Fuzzy Switched Systems -- Reduced-Order Filter Design of Fuzzy Stochastic Systems -- Dissipative Event-Triggered Fuzzy Control of Truck-Trailer Systems -- Event-Triggered Fuzzy Control of Inverted Pendulum Systems -- Conclusion and Further Work.

This book aims to introduce the state-of-the-art research of stability/performance analysis and optimal synthesis methods for fuzzy-model-based systems. A series of problems are solved with new approaches of design, analysis and synthesis of fuzzy systems, including stabilization control and stability analysis, dynamic output feedback control, fault detection filter design, and reduced-order model approximation. Some efficient techniques, such as Lyapunov stability theory, linear matrix inequality, reciprocally convex approach, and cone complementary linearization method, are utilized in the approaches. This book is a comprehensive reference for researchers and practitioners working on intelligent control, model reduction, and fault detection of fuzzy systems, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts and methodologies with theoretical and practical significance in system analysis and control synthesis.

ISBN: 9783030812140$q(electronic bk.)

Standard No.: 10.1007/978-3-030-81214-0doiSubjects--Topical Terms:

182084
Fuzzy systems.

LC Class. No.: TA168

Dewey Class. No.: 620.001171

Intelligent control, filtering and model reduction analysis for fuzzy-model-based systems
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505 0 $a Introduction -- Stabilization Synthesis of T-S Fuzzy Delayed Systems -- Output Feedback Control of Fuzzy Stochastic Systems -- Output Feedback Control of Fuzzy Switching Systems -- Dissipative Filtering of Fuzzy Switched Systems -- Fault Detection for Switched Stochastic Systems -- Reliable Filtering for T-S Fuzzy Time-Delay Systems -- Reduced-Order Model Approximation of Switched Systems -- Model Reduction of Time-Varying Delay Fuzzy Systems -- Model Approximation of Fuzzy Switched Systems -- Reduced-Order Filter Design of Fuzzy Stochastic Systems -- Dissipative Event-Triggered Fuzzy Control of Truck-Trailer Systems -- Event-Triggered Fuzzy Control of Inverted Pendulum Systems -- Conclusion and Further Work.
520 $a This book aims to introduce the state-of-the-art research of stability/performance analysis and optimal synthesis methods for fuzzy-model-based systems. A series of problems are solved with new approaches of design, analysis and synthesis of fuzzy systems, including stabilization control and stability analysis, dynamic output feedback control, fault detection filter design, and reduced-order model approximation. Some efficient techniques, such as Lyapunov stability theory, linear matrix inequality, reciprocally convex approach, and cone complementary linearization method, are utilized in the approaches. This book is a comprehensive reference for researchers and practitioners working on intelligent control, model reduction, and fault detection of fuzzy systems, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts and methodologies with theoretical and practical significance in system analysis and control synthesis.
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