國立虎尾科技大學 |

Robust and Fault-Tolerant Control = Neural-Network-Based Solutions /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Robust and Fault-Tolerant Control/ by Krzysztof Patan.
Reminder of title:	Neural-Network-Based Solutions /
Author:	Patan, Krzysztof.
Description:	XXVIII, 209 p. 118 illus., 25 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Control engineering. -
Online resource:	https://doi.org/10.1007/978-3-030-11869-3
ISBN:	9783030118693

Robust and Fault-Tolerant Control = Neural-Network-Based Solutions /
Patan, Krzysztof.

Robust and Fault-Tolerant ControlNeural-Network-Based Solutions /[electronic resource] :by Krzysztof Patan. - 1st ed. 2019. - XXVIII, 209 p. 118 illus., 25 illus. in color.online resource. - Studies in Systems, Decision and Control,1972198-4182 ;. - Studies in Systems, Decision and Control,27.

Introduction -- Neural Networks -- Robust and Fault-Tolerant Control -- Model Predictive Control -- Control Reconfiguration -- Iterative Learning Control -- Concluding Remarks and Further Research Directions.

Robust and Fault-Tolerant Control proposes novel automatic control strategies for nonlinear systems developed by means of artificial neural networks and pays special attention to robust and fault-tolerant approaches. The book discusses robustness and fault tolerance in the context of model predictive control, fault accommodation and reconfiguration, and iterative learning control strategies. Expanding on its theoretical deliberations the monograph includes many case studies demonstrating how the proposed approaches work in practice. The most important features of the book include: a comprehensive review of neural network architectures with possible applications in system modelling and control; a concise introduction to robust and fault-tolerant control; step-by-step presentation of the control approaches proposed; an abundance of case studies illustrating the important steps in designing robust and fault-tolerant control; and a large number of figures and tables facilitating the performance analysis of the control approaches described. The material presented in this book will be useful for researchers and engineers who wish to avoid spending excessive time in searching neural-network-based control solutions. It is written for electrical, computer science and automatic control engineers interested in control theory and their applications. This monograph will also interest postgraduate students engaged in self-study of nonlinear robust and fault-tolerant control.

ISBN: 9783030118693

Standard No.: 10.1007/978-3-030-11869-3doiSubjects--Topical Terms:

1249728
Control engineering.

LC Class. No.: TJ212-225

Dewey Class. No.: 629.8

Robust and Fault-Tolerant Control = Neural-Network-Based Solutions /
LDR:03125nam a22003975i 4500 001 1014812
003 DE-He213
005 20200702060050.0
007 cr nn 008mamaa
008 210106s2019 gw | s |||| 0|eng d
020 $a 9783030118693 $9 978-3-030-11869-3
024 7 $a 10.1007/978-3-030-11869-3 $2 doi
035 $a 978-3-030-11869-3
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 Patan, Krzysztof. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 681162
245 1 0 $a Robust and Fault-Tolerant Control $h [electronic resource] : $b Neural-Network-Based Solutions / $c by Krzysztof Patan.
250 $a 1st ed. 2019.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a XXVIII, 209 p. 118 illus., 25 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 Studies in Systems, Decision and Control, $x 2198-4182 ; $v 197
505 0 $a Introduction -- Neural Networks -- Robust and Fault-Tolerant Control -- Model Predictive Control -- Control Reconfiguration -- Iterative Learning Control -- Concluding Remarks and Further Research Directions.
520 $a Robust and Fault-Tolerant Control proposes novel automatic control strategies for nonlinear systems developed by means of artificial neural networks and pays special attention to robust and fault-tolerant approaches. The book discusses robustness and fault tolerance in the context of model predictive control, fault accommodation and reconfiguration, and iterative learning control strategies. Expanding on its theoretical deliberations the monograph includes many case studies demonstrating how the proposed approaches work in practice. The most important features of the book include: a comprehensive review of neural network architectures with possible applications in system modelling and control; a concise introduction to robust and fault-tolerant control; step-by-step presentation of the control approaches proposed; an abundance of case studies illustrating the important steps in designing robust and fault-tolerant control; and a large number of figures and tables facilitating the performance analysis of the control approaches described. The material presented in this book will be useful for researchers and engineers who wish to avoid spending excessive time in searching neural-network-based control solutions. It is written for electrical, computer science and automatic control engineers interested in control theory and their applications. This monograph will also interest postgraduate students engaged in self-study of nonlinear robust and fault-tolerant control.
650 0 $a Control engineering. $3 1249728
650 0 $a Artificial intelligence. $3 559380
650 0 $a Chemical engineering. $3 555952
650 0 $a Automotive engineering. $3 1104081
650 0 $a Aerospace engineering. $3 686400
650 0 $a Astronautics. $3 646219
650 1 4 $a Control and Systems Theory. $3 1211358
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Industrial Chemistry/Chemical Engineering. $3 671153
650 2 4 $a Automotive Engineering. $3 683772
650 2 4 $a Aerospace Technology and Astronautics. $3 683885
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030118686
776 0 8 $i Printed edition: $z 9783030118709
830 0 $a Studies in Systems, Decision and Control, $x 2198-4182 ; $v 27 $3 1254124
856 4 0 $u https://doi.org/10.1007/978-3-030-11869-3
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)