The major objective of this book is to introduce advanced design and (online) optimization methods for fault diagnosis and fault-tolerant control from different aspects. Under the aspect of system types, fault diagnosis and fault-tolerant issues are dealt with for linear time-invariant and time-varying systems as well as for nonlinear and distributed (including networked) systems. From the methodological point of view, both model-based and data-driven schemes are investigated.To allow for a self-contained study and enable an easy implementation in real applications, the necessary knowledge as well as tools in mathematics and control theory are included in this book. The main results with the fault diagnosis and fault-tolerant schemes are presented in form of algorithms and demonstrated by means of benchmark case studies. The intended audience of this book are process and control engineers, engineering students and researchers with control engineering background.

Prof. Dr.-Ing. Steven X. Ding is head of the institute Automatic Control and Complex Systems (AKS) at the University of Duisburg, Germany. He received the Ph.D. degree in electrical engineering from the University of Duisburg in 1992. Between 1992 and 1994, he worked with Rheinmetall GmbH, Germany. From 1995 to 2001, he was professor of control engineering at the University of Applied Science Lausitz in Senftenberg, Germany, and was the the vice president of this university during 1998 2000. Since 2001, he has been a full professor of control engineering at the University of Duisburg-Essen. Prof. Ding has published three books and over 350 book contributions, journal and conference papers in the areas of model-based and data-driven fault diagnosis, process monitoring and control as well as their applications to the automotive, process and renewable energy industries.
Detailed information is available at AKS-website: http://aks.uni-due.de/htm/index.php?lang=en

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.