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Fuzzy system identification and adap...

Jiang, Bin.

Fuzzy system identification and adaptive control

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Fuzzy system identification and adaptive controlby Ruiyun Qi, Gang Tao, Bin Jiang.
作者:	Qi, Ruiyun.
其他作者:	Tao, Gang.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xvii, 282 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Adaptive control systems.
電子資源:	https://doi.org/10.1007/978-3-030-19882-4
ISBN:	9783030198824$q(electronic bk.)

Fuzzy system identification and adaptive control
Qi, Ruiyun.

Fuzzy system identification and adaptive control[electronic resource] /by Ruiyun Qi, Gang Tao, Bin Jiang. - Cham :Springer International Publishing :2019. - xvii, 282 p. :ill., digital ;24 cm. - Communications and control engineering,0178-5354. - Communications and control engineering..

Introduction -- T-S Fuzzy Systems -- Adaptive Control -- T-S Fuzzy System Identification -- Adaptive T-S Fuzzy State Tracking Control Using State Feedback -- Adaptive T-S Fuzzy Output Tracking Control Using State Feedback -- Adaptive T-S Fuzzy Control Using Output Feedback: SISO Case -- Adaptive T-S Fuzzy Control Using Output Feedback: MIMO Case -- Adaptive T-S Fuzzy Control with Unknown Membership Functions -- Adaptive T-S Fuzzy Control Systems For Fault Compensation -- Conclusions.

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.

ISBN: 9783030198824$q(electronic bk.)

Standard No.: 10.1007/978-3-030-19882-4doiSubjects--Topical Terms:

182317
Adaptive control systems.

LC Class. No.: TJ217 / .Q785 2019

Dewey Class. No.: 629.8

Fuzzy system identification and adaptive control
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505 0 $a Introduction -- T-S Fuzzy Systems -- Adaptive Control -- T-S Fuzzy System Identification -- Adaptive T-S Fuzzy State Tracking Control Using State Feedback -- Adaptive T-S Fuzzy Output Tracking Control Using State Feedback -- Adaptive T-S Fuzzy Control Using Output Feedback: SISO Case -- Adaptive T-S Fuzzy Control Using Output Feedback: MIMO Case -- Adaptive T-S Fuzzy Control with Unknown Membership Functions -- Adaptive T-S Fuzzy Control Systems For Fault Compensation -- Conclusions.
520 $a 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.
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