語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Advanced methods for fault diagnosis...
~
X. Ding, Steven.
Advanced methods for fault diagnosis and fault-tolerant control
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Advanced methods for fault diagnosis and fault-tolerant control/ by Steven X. Ding.
作者:
X. Ding, Steven.
面頁冊數:
XXIII, 658 p. 28 illus.online resource. :
Contained By:
Springer Nature eBook
標題:
Industrial Chemistry/Chemical Engineering. -
電子資源:
https://doi.org/10.1007/978-3-662-62004-5
ISBN:
9783662620045
Advanced methods for fault diagnosis and fault-tolerant control
X. Ding, Steven.
Advanced methods for fault diagnosis and fault-tolerant control
[electronic resource] /by Steven X. Ding. - 1st ed. 2021. - XXIII, 658 p. 28 illus.online resource.
Basic requirements on fault detection and estimation -- Basic methods for fault detection and estimation in static and dynamic processes -- Feedback control, observer, and residual generation -- Fault detection and estimation for linear time-varying systems -- Detection and isolation of multiplicative faults in uncertain systems -- Analysis, parameterisation and optimal design of nonlinear observer-based fault detection systems -- Data-driven fault detection methods for large-scale and distributed systems -- Alternative test statistics and data-driven fault detection methods -- Application of randomised algorithms to assessment and design of fault diagnosis systems -- Performance-based fault-tolerant control -- Performance degradation monitoring and recovering -- Data-driven fault-tolerant control schemes.
After the first two books have been dedicated to model-based and data-driven fault diagnosis respectively, this book addresses topics in both model-based and data-driven thematic fields with considerable focuses on fault-tolerant control issues and application of machine learning methods. The major objective of the book is to study basic fault diagnosis and fault-tolerant control problems and to build a framework for long-term research efforts in the fault diagnosis and fault-tolerant control domain. In this framework, possibly unified solutions and methods can be developed for general classes of systems. The book is composed of six parts. Besides Part I serving as a common basis for the subsequent studies, Parts II - VI are dedicated to five different thematic areas, including model-based fault diagnosis methods for linear time-varying systems, nonlinear systems and systems with model uncertainties, statistical and data-driven fault diagnosis methods, assessment of fault diagnosis systems, as well as fault-tolerant control with a strong focus on performance degradation monitoring and recovering. These parts are self-contained and so structured that they can also be used for self-study on the concerned topics. The content Basic requirements on fault detection and estimation – Basic methods for fault detection and estimation in static and dynamic processes – Feedback control, observer, and residual generation – Fault detection and estimation for linear time-varying systems – Detection and isolation of multiplicative faults in uncertain systems – Analysis, parameterisation and optimal design of nonlinear observer-based fault detection systems – Data-driven fault detection methods for large-scale and distributed systems – Alternative test statistics and data-driven fault detection methods – Application of randomised algorithms to assessment and design of fault diagnosis systems – Performance-based fault-tolerant control – Performance degradation monitoring and recovering – Data-driven fault-tolerant control schemes The target groups This book would be valuable for graduate and PhD students as well as for researchers and engineers in the field. The author Prof. Dr.-Ing. Steven X. Ding is a professor and the head of the Institute for Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Germany. His research interests are model-based and data-driven fault diagnosis, control and fault-tolerant systems as well as their applications in industry with a focus on automotive systems, chemical processes and renewable energy systems.
ISBN: 9783662620045
Standard No.: 10.1007/978-3-662-62004-5doiSubjects--Topical Terms:
671153
Industrial Chemistry/Chemical Engineering.
LC Class. No.: TJ212-225
Dewey Class. No.: 629.8
Advanced methods for fault diagnosis and fault-tolerant control
LDR
:04760nam a22003855i 4500
001
1049209
003
DE-He213
005
20210623063805.0
007
cr nn 008mamaa
008
220103s2021 gw | s |||| 0|eng d
020
$a
9783662620045
$9
978-3-662-62004-5
024
7
$a
10.1007/978-3-662-62004-5
$2
doi
035
$a
978-3-662-62004-5
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
X. Ding, Steven.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1353274
245
1 0
$a
Advanced methods for fault diagnosis and fault-tolerant control
$h
[electronic resource] /
$c
by Steven X. Ding.
250
$a
1st ed. 2021.
264
1
$a
Berlin, Heidelberg :
$b
Springer Berlin Heidelberg :
$b
Imprint: Springer,
$c
2021.
300
$a
XXIII, 658 p. 28 illus.
$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
505
0
$a
Basic requirements on fault detection and estimation -- Basic methods for fault detection and estimation in static and dynamic processes -- Feedback control, observer, and residual generation -- Fault detection and estimation for linear time-varying systems -- Detection and isolation of multiplicative faults in uncertain systems -- Analysis, parameterisation and optimal design of nonlinear observer-based fault detection systems -- Data-driven fault detection methods for large-scale and distributed systems -- Alternative test statistics and data-driven fault detection methods -- Application of randomised algorithms to assessment and design of fault diagnosis systems -- Performance-based fault-tolerant control -- Performance degradation monitoring and recovering -- Data-driven fault-tolerant control schemes.
520
$a
After the first two books have been dedicated to model-based and data-driven fault diagnosis respectively, this book addresses topics in both model-based and data-driven thematic fields with considerable focuses on fault-tolerant control issues and application of machine learning methods. The major objective of the book is to study basic fault diagnosis and fault-tolerant control problems and to build a framework for long-term research efforts in the fault diagnosis and fault-tolerant control domain. In this framework, possibly unified solutions and methods can be developed for general classes of systems. The book is composed of six parts. Besides Part I serving as a common basis for the subsequent studies, Parts II - VI are dedicated to five different thematic areas, including model-based fault diagnosis methods for linear time-varying systems, nonlinear systems and systems with model uncertainties, statistical and data-driven fault diagnosis methods, assessment of fault diagnosis systems, as well as fault-tolerant control with a strong focus on performance degradation monitoring and recovering. These parts are self-contained and so structured that they can also be used for self-study on the concerned topics. The content Basic requirements on fault detection and estimation – Basic methods for fault detection and estimation in static and dynamic processes – Feedback control, observer, and residual generation – Fault detection and estimation for linear time-varying systems – Detection and isolation of multiplicative faults in uncertain systems – Analysis, parameterisation and optimal design of nonlinear observer-based fault detection systems – Data-driven fault detection methods for large-scale and distributed systems – Alternative test statistics and data-driven fault detection methods – Application of randomised algorithms to assessment and design of fault diagnosis systems – Performance-based fault-tolerant control – Performance degradation monitoring and recovering – Data-driven fault-tolerant control schemes The target groups This book would be valuable for graduate and PhD students as well as for researchers and engineers in the field. The author Prof. Dr.-Ing. Steven X. Ding is a professor and the head of the Institute for Automatic Control and Complex Systems (AKS), University of Duisburg-Essen, Germany. His research interests are model-based and data-driven fault diagnosis, control and fault-tolerant systems as well as their applications in industry with a focus on automotive systems, chemical processes and renewable energy systems.
650
2 4
$a
Industrial Chemistry/Chemical Engineering.
$3
671153
650
1 4
$a
Control and Systems Theory.
$3
1211358
650
0
$a
Chemical engineering.
$3
555952
650
0
$a
Mechatronics.
$3
559133
650
0
$a
Control engineering.
$3
1249728
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783662620038
776
0 8
$i
Printed edition:
$z
9783662620052
856
4 0
$u
https://doi.org/10.1007/978-3-662-62004-5
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)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入