國立虎尾科技大學 |

Fuzzy System Identification and Adaptive Control

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Fuzzy System Identification and Adaptive Control/ by Ruiyun Qi, Gang Tao, Bin Jiang.
Author:	Qi, Ruiyun.
other author:	Tao, Gang.
Description:	XVII, 282 p. 63 illus., 56 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Control engineering. -
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. - 1st ed. 2019. - XVII, 282 p. 63 illus., 56 illus. in color.online resource. - 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:

1249728
Control engineering.

LC Class. No.: TJ212-225

Dewey Class. No.: 629.8

Fuzzy System Identification and Adaptive Control
LDR:03648nam a22004095i 4500 001 1010660
003 DE-He213
005 20200703075256.0
007 cr nn 008mamaa
008 210106s2019 gw | s |||| 0|eng d
020 $a 9783030198824 $9 978-3-030-19882-4
024 7 $a 10.1007/978-3-030-19882-4 $2 doi
035 $a 978-3-030-19882-4
050 4 $a TJ212-225
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
100 1 $a Qi, Ruiyun. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1228354
245 1 0 $a Fuzzy System Identification and Adaptive Control $h [electronic resource] / $c by Ruiyun Qi, Gang Tao, Bin Jiang.
250 $a 1st ed. 2019.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a XVII, 282 p. 63 illus., 56 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
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 Control engineering. $3 1249728
650 0 $a System theory. $3 566168
650 0 $a Artificial intelligence. $3 559380
650 0 $a Computational intelligence. $3 568984
650 0 $a Electrical engineering. $3 596380
650 1 4 $a Control and Systems Theory. $3 1211358
650 2 4 $a Systems Theory, Control. $3 669337
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Computational Intelligence. $3 768837
650 2 4 $a Communications Engineering, Networks. $3 669809
700 1 $a Tao, Gang. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 771664
700 1 $a Jiang, Bin. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1065846
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030198817
776 0 8 $i Printed edition: $z 9783030198831
776 0 8 $i Printed edition: $z 9783030198848
830 0 $a Communications and Control Engineering, $x 0178-5354 $3 1254247
856 4 0 $u https://doi.org/10.1007/978-3-030-19882-4
912 $a ZDB-2-INR
912 $a ZDB-2-SXIT
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)
950 $a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)