Description
Book Synopsis 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.
Trade ReviewFrom 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)
Table of ContentsI. Principles of Fault Diagnosis.- Analytical Techniques-Based FDI.- Soft Computing-Based FDI.- II. State and Parameter Estimation Strategies.- State Estimation Techniques for FDI.- Parameter Estimation-Based FDI.- III. Soft Computing Strategies.- Evolutionary Algorithms.- Neural Networks.- Conclusions and Future Research Directions.
