Advanced methods for fault diagnosis and fault-tolerant control
General Material Designation
[Book]
First Statement of Responsibility
/ Steven X. Ding
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (664 pages)
NOTES PERTAINING TO PUBLICATION, DISTRIBUTION, ETC.
Text of Note
Print
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index.
CONTENTS NOTE
Text of Note
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.