Fault Diagnosis of Hybrid Dynamic and Complex Systems

Moamar Sayed-Mouchaweh received his PhD from the University of Reims-France. He was working as Associated Professor in Computer Science, Control and Signal processing at the University of Reims-France in the Research Center in Sciences and Technology of the Information and the Communication. In December 2008, he obtained the Habilitation to Direct Researches (HDR) in Computer science, Control and Signal processing. Since September 2011, he is working as a Full Professor in the High National Engineering School of Mines Department of Computer Science and Automatic Control. He edited the Springer book ‘Learning in Non-Stationary Environments: Methods and Applications‘, in April 2012 and wrote two SpringerBriefs ‘Discrete Event Systems: Diagnosis and Diagnosability’, and ‘Learning from Data Streams in Dynamic Environments’. He was a guest editor of several special issues of international journals. He was IPC Chair of conference Chair of several international workshops and conferences (IEEE International Conference on Machine Learning and Applications IEEE International Conference on Evolving and Adaptive Intelligent Systems). He is working as a member of the Editorial Board of Elsevier Journal “Applied Soft Computing” and Springer Journals “Evolving systems” and “Intelligent Industrial Systems”.

• Prologue.- Motor Fault Detection and Diagnosis Based on Meta-cognitive Random Vector Functional Link Network.- Optimal Adaptive Threshold and Mode Fault Detection for Model-based Fault Diagnosis of Hybrid Dynamical Systems.- Diagnosing Hybrid Dynamical Systems using Max-Plus Algebraic Methods.- Monitoring of Hybrid Dynamic Systems: Application to Chemical Process.- Hybrid Bond-Graph Possible Conflicts for Hybrid Systems Fault Diagnosis.- Hybrid System Model based Fault Diagnosis of Automotive Engines.- Diagnosis of Hybrid Systems Using Structural Model Decomposition.- Diagnosis of Hybrid Systems Using Hybrid Particle Petri Nets: Theory and Application on a Planetary Rover.- Diagnosis of Hybrid Dynamic Systems based on the Behavior Automaton Abstraction.- Index.