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Advanced methods for fault diagnosis and fault-tolerant control

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Advanced methods for fault diagnosis and fault-tolerant control/ by Steven X. Ding.
Author:	X. Ding, Steven.
Description:	XXIII, 658 p. 28 illus.online resource. :
Contained By:	Springer Nature eBook
Subject:	Control engineering. -
Online resource:	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:

1249728
Control engineering.

LC Class. No.: TJ212-225

Dewey Class. No.: 629.8

Advanced methods for fault diagnosis and fault-tolerant control
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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.
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