東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Fuzzy system identification and adap...

Qi, Ruiyun.

Linked to FindBook

Google Book

Amazon

博客來

Fuzzy system identification and adaptive control

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fuzzy system identification and adaptive control/ by Ruiyun Qi, Gang Tao, Bin Jiang.
Author:	Qi, Ruiyun.
other author:	Tao, Gang.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xvii, 282 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Adaptive control systems. -
Online resource:	https://doi.org/10.1007/978-3-030-19882-4
ISBN:	9783030198824

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

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

533905
Adaptive control systems.

LC Class. No.: TJ217 / .Q785 2019

Dewey Class. No.: 629.8

Fuzzy system identification and adaptive control
LDR:03202nmm a2200337 a 4500 001 2192192
003 DE-He213
005 20190619120240.0
006 m d
007 cr nn 008maaau
008 200506s2019 gw s 0 eng d
020 $a 9783030198824 $q (electronic bk.)
020 $a 9783030198817 $q (paper)
024 7 $a 10.1007/978-3-030-19882-4 $2 doi
035 $a 978-3-030-19882-4
040 $a GP $c GP
041 0 $a eng
050 4 $a TJ217 $b .Q785 2019
072 7 $a TJFM $2 bicssc
072 7 $a TEC004000 $2 bisacsh
072 7 $a TJFM $2 thema
082 0 4 $a 629.8 $2 23
090 $a TJ217 $b .Q1 2019
100 1 $a Qi, Ruiyun. $3 3412287
245 1 0 $a Fuzzy system identification and adaptive control $h [electronic resource] / $c by Ruiyun Qi, Gang Tao, Bin Jiang.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xvii, 282 p. : $b ill., digital ; $c 24 cm.
490 1 $a Communications and control engineering, $x 0178-5354
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.
650 0 $a Adaptive control systems. $3 533905
650 0 $a Fuzzy systems. $3 535881
650 1 4 $a Control and Systems Theory. $3 3381515
650 2 4 $a Systems Theory, Control. $3 893834
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Communications Engineering, Networks. $3 891094
700 1 $a Tao, Gang. $3 712266
700 1 $a Jiang, Bin. $3 1066715
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Communications and control engineering. $3 1566566
856 4 0 $u https://doi.org/10.1007/978-3-030-19882-4
950 $a Intelligent Technologies and Robotics (Springer-42732)