Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems: From Analytical to Soft Computing Approaches (Lecture Notes in Control and Information Sciences)

 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.

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)