This monograph presents a variety of techniques that can be used for designing robust fault diagnosis schemes for non-linear systems. The introductory part of the book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. Subsequently, advanced robust observer structures are presented. Parameter estimation based techniques are discussed as well. A particular attention is drawn to experimental design for fault diagnosis. The book also presents a number of robust soft computing approaches utilizing evolutionary algorithms and neural networks. All approaches described in this book are illustrated by practical applications.
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From the reviews:
"The book treats a class of nonlinear discrete-time models for dynamical systems and presents further developments of the author's research on nonlinear system identification and fault detection ... . It is intended for researchers, engineers and advanced postgraduate students in control, computer science and related engineering fields." (Alexander V. Nazin, Mathematical Reviews, Issue 2008 d)
"The book treats a class of nonlinear discrete-time models for dynamical systems and presents further developments of the author's research on nonlinear system identification and fault detection ... . It is intended for researchers, engineers and advanced postgraduate students in control, computer science and related engineering fields." (Alexander V. Nazin, Mathematical Reviews, Issue 2008 d)