This book presents recent advances in fault diagnosis strategies for complex dynamic systems. Its impetus derives from the need for an overview of the challenges of the fault diagnosis technique, especially for those demanding systems that require reliability, availability, maintainability and safety to ensure efficient operations. Moreover, the need for a high degree of tolerance with respect to possible faults represents a further key point, primarily for complex systems, as modeling and control are inherently challenging, and maintenance is both expensive and safety-critical.
Diagnosis and Fault-tolerant Control 1 also presents and compares different diagnosis schemes using established case studies that are widely used in related literature. The main features of this book regard the analysis, design and implementation of proper solutions for the problems of fault diagnosis in safety critical systems. The design of the considered solutions involves robust data-driven, model-based approaches.
1. Mathematical Modeling and Fault Description, Silvio Simani.
2. Structural Analysis, Mattias Krysander and Erik Frisk.
3. Set-based Fault Detection and Isolation, Ye Wang and Vicenç Puig.
4. Diagnosis of Stochastic Systems, Gregory Provan.
5. Data-Driven Methods for Fault Diagnosis, Silvio Simani.
6. The Artificial Intelligence Approach to Model-based Diagnosis, Belarmino Pulido, Carlos J. Alonso-Gonzalez and Anibal Bregon.
Vicenç Puig is Professor of Automatic Control at the Universitat Politècnica de Catalunya (UPC), Spain. He has published more than 80 journal articles and more than 350 articles in international conference/workshop proceedings related to diagnosis and fault-tolerant control.
Silvio Simani is Professor of Automatic Control in the Engineering Department of Ferrara University, Italy. He has published about 260 journal and conference papers, several book chapters and four monographs on fault diagnosis and sustainable control topics.
Table of Contents
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