Intelligent Control for Electric Power Systems and Electric Vehicles
Proposes new control methods that treat the control problem of the complex nonlinear dynamics of electric power systems and electric vehicles without the need for complicated state-space model transformations and changes of state variables. The proposed control schemes also foster the optimized exploitation of renewable energy sources and the reliable integration of renewable energy units in the power grid. It focuses on intelligent control techniques applicable to a wide range of electric motor systems and energy conversion units.
The manuscript is suitable for teaching nonlinear control, estimation and fault diagnosis topics with emphasis to electric power systems and to electric vehicle traction and propulsion systems both at late undergraduate and postgraduate levels.
Fault Diagnosis for Electric Power Systems and Electric Vehicles
Offers a detailed and in-depth analysis of the topic of fault diagnosis for electric power systems and electric vehicles. It develops new fault detection and isolation methods which are addressed to a wide class of nonlinear dynamic systems, with emphasis on electric power systems and electric vehicles. Model-free fault detection and isolation methods are analyzed, processing raw data with neural networks and nonlinear regressors to create fault-free models, while statistical tests on the residuals provide objective criteria for failures; these new methods, incorporating statistical procedures for defining fault thresholds, enable early diagnosis and reveal incipient changes in monitored system parameters.
Key Features:
- Offers timely and state-of-the-art insight on nonlinear control, nonlinear estimation and fault diagnosis for electric power systems and for electric traction and propulsion systems.
- Analyzes new methods of nonlinear control and offers valuable resources for researchers tackling control problems in these domains.
- Contains fault detection and isolation approaches that have been developed in the new monograph which can be used by researchers carrying out work on condition monitoring and fault diagnosis problems.
- Equips skilled technical personnel and engineers with advanced control and fault diagnosis methods, enabling them to optimize electric power systems and traction systems while addressing complex challenges in power electronics and propulsion systems.
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.
Dr. Pierluigi Siano received the M.Sc. degree in electronic engineering and the
Ph.D. degree in information and electrical engineering from the University of
Salerno, Salerno, Italy, in 2001 and 2006, respectively. He is Full Professor of Electrical
Power Systems and Scientific Director of the Smart Grids and Smart Cities
Laboratory with the Department ofManagement and Innovation Systems, University
of Salerno. Since 2021 he has been a Distinguished Visiting Professor in the Department
of Electrical and Electronic Engineering Science, University of Johannesburg.
His research activities are centered on demand response, energy management, the
integration of distributed energy resources in smart grids, electricity markets, and
planning and management of power systems. In these research fields, he has coauthored
more than 700 articles including more than 410 international journals that
received in Scopus more than 19200 citations with an H-index equal to 66. Since
2019 he has been awarded as a Highly Cited Researcher in Engineering by Web of
Science Group. He has been the Chair of the IES TC on Smart Grids. He is Editor for
the Power & Energy Society Section of IEEE Access, IEEE Transactions on Power
Systems, IEEE Transactions on Industrial Informatics, IEEE Transactions on Industrial
Electronics, and IEEE Systems.
