About the Book:

The present monograph offers a detailed and in-depth analysis of the topic of fault diagnosis for electric power systems and electric vehicles. It explores both model-based and model-free techniques for fault diagnosis and provides a solution for the problem of control of the marine-turbine and synchronous-generator unit and Fault diagnosis of the marine turbine and synchronous-generator unit. Additionally, it introduces innovative approaches for diagnosing faults in electricity microgrids and gas processing units. The new fault detection and isolation methods with statistical procedures for defining fault thresholds enable early fault diagnosis and reveal incipient changes in the parameters of the monitored systems.

 Key Features:

• Analyzes model-based fault detection and isolation methods. Known models about the dynamics of the monitored system are used by nonlinear state observers and Kalman Filters, which emulate the system’s fault-free condition. 
• Analyzes model-free fault detection and isolation methods. Raw data are processed by neural networks and nonlinear regressors to generate models that emulate the fault-free condition of the monitored system.
• Utilizes statistical tests based on residual processing, which compare outputs from the monitored system to those of a fault-free model, providing objective and highly reliable criteria for identifying failures.
• Enables early fault diagnosis through new detection and isolation methods that use statistical procedures for defining fault thresholds, effectively revealing incipient changes in the parameters of monitored systems.

Contents:

1. Fault diagnosis with model-based and model-free techniques

2. Fault diagnosis for SG-based renewable energy systems

3. Fault diagnosis for electricity microgrids and gas processing units

4. Fault diagnosis for gas and steam-turbine power generation units

About the Authors:

Dr. Gerasimos Rigatos obtained his diploma (1995) and his Ph.D. (2000) both from the Department of Electrical and Computer Engineering, of the National Technical University of Athens (NTUA), Greece. In 2001 he was a post-doctoral researcher at IRISA-INRIA, Rennes, France. He is currently a Research Director (Researcher Grade A’) at the Industrial Systems Institute, Greece. He is a Senior Member of IEEE, and a Member and CEng of IET. He has led several research cooperation agreements and projects which have given accredited results in the areas of nonlinear control, nonlinear filtering and control of distributed parameter systems. His results appear in 8 research monographs and in several journal articles. According to Elsevier Scopus his research comprising 135 journal articles where he is the first or sole author, has received more than 3000 citations with an H-index of 26. Since 2007, he has been awarded visiting professor positions at several academic institutions (University Paris XI, France, Harper-Adams University College, UK, University of Northumbria, UK, University of Salerno, Italy, Ecole Centrale de Nantes, France). He is an editor of the Journal of Advanced Robotic Systems and of the SAE Journal of Electrified Vehicles.

Dr. Masoud Abbaszadeh obtained a B.Sc and an M.Sc in Electrical Engineering from Amirkabir University of Technology and Sharif University of Technology, in Iran, respectively. Next, he received a Ph.D. degree in Electrical Engineering (Controls) in 2008 from the University of Alberta, Canada. From 2008 to 2011, he was with Maplesoft, Waterloo, Ontario, Canada, as a Research Engineer. He was the principal developer of MapleSim Control Design Toolbox and was a member of a research
team working on the Maplesoft-Toyota joint projects. From 2011 to 2013, he was a Senior Research Engineer at United Technologies Research Center, East Hartford, CT, USA, working on advanced control systems, and complex systems modeling and simulation. Currently he is a Principal Research Engineer at GE Research Center, Niskayuna, NY, USA. He has also held an Adjunct Professor position at Rensselaer Polytechnic Institute, NY, USA. He has over 150 peer-reviewed papers, 9 book chapters, and holds 39 issued US patents, with over 40 more patents pending. His research interests include estimation and detection theory, robust and nonlinear control, and machine learning with applications in diagnostics, cyber-physical resilience
and autonomous systems. He serves as an Associate Editor of IEEE Transactions on Control Systems Technology, and a member of IEEE CSS Conference Editorial Board.

Dr. Mohamed-Assaad Hamida was born in El Oued, Algeria, in 1985. He received the B.Sc . degree in electrical engineering from the University of Batna, Batna, Algeria, in 2009, the M.Sc. degree in automatic control from Ecole Nationale Superieure d’Ingenieurs de Poitiers (ENSIP), Poitiers, France, in 2010, and the Ph.D degree in automatic control and electrical engineering from Ecole centrale de Nantes, Nantes, France, in 2013. From 2013 to 2017, he was an Associate Professor of Electrical Engineering with the University of Ouargla, Algeria. In 2017, he joined the Ecole Centrale de Nantes and the Laboratory of Digital Sciences of Nantes (LS2N), as an Associate Professor. Dr. Hamida is the local coordinator of the European project EPiCo on Electric Vehicles Propulsion and Control at Ecole Centrale of Nantes and the head of the real-time systems unit in the same university. His research interests include robust nonlinear control (higher order sliding mode, backstepping, adaptive control, optimal control), theoretical aspects of nonlinear observer design, control and fault diagnosis of electrical systems and renewable energy applications. His current research interests include robust nonlinear control, theoretical aspects of nonlinear observer design, control, and fault diagnosis of electrical systems and renewable energy applications.