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NEXT > B. Badrzadeh - Power System Dynamic Modelling and Analysis in Evolving Networks P. Schavemaker - Electrical Power System Essentials A. von Meier - Electric Power Systems: A Conceptual Introduction G. Rogers - Power System Oscillations G. Rigatos - Intelligent Control for Electric Power Systems and Electric Vehicles R. Castro - Engineering of Power Systems Economics M. Rahmani-Andebili - Power System Analysis: Comprehensive Lessons M.G. Simões - Power Electronic Converters and Systems: Converters and machine drives M.G. Simões - Power Electronic Converters and Systems: Applications G.B. Gharehpetian - Future Power System Elements, Challenges, and Solutions
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G. Rigatos - Intelligent Control for Electric Power Systems and Electric Vehicles Intelligent Control for Electric Power Systems and Electric Vehicles 1st Edition by G. Rigatos (Author), M. Abbaszadeh (Author), M Hamida (Author), P. Siano (Author) Publisher : CRC Press Publication date : October 30, 2024 Edition : 1st Language : English Print length : 576 pages  The present monograph offers a detailed and in-depth analysis of the topic of Intelligent Control for Electric Power Systems and Electric Vehicles. The monograph provides a comprehensive analysis of various control methods, including nonlinear optimal control, Lie algebra-based control, and differential flatness theory. It addresses the control of electric motors, VSI-fed PMSMs, and energy conversion chains based on PMSMs and induction machines. The work also explores multi-phase machines in gas processing, spherical permanent magnet synchronous motors, traction systems in electric and hybrid vehicles, and renewable power units alongside heat management systems. Key Features: Proposes new control methods meant to 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. Contains modular and scalable control schemes which can be applied to a large class of dynamic models of electric power systems and electric vehicles. They have a clear and easy-to- implement algorithmic part, while they also exhibit a moderate computational load. Fosters the optimized exploitation of renewable energy sources and the reliable integration of renewable energy units in the power grid. 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. About the Author 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. TABLE OF CONTENTS chapter 1|36 pages Nonlinear optimal control and Lie algebra-based control chapter 2|27 pages Differential flatness theory and flatness-based control methods chapter 3|51 pages Control of DC and PMBLDC electric motors chapter 4|51 pages Control of VSI-fed three-phase and multi-phase PMSMs chapter 5|81 pages Control of energy conversion chains based on distributed PMSMs chapter 6|55 pages Control of energy conversion chains based on Induction Machines chapter 7|52 pages Control of multi-phase machines in gas processing and power units chapter 8|60 pages Control of spherical PM motors and switched reluctance motors chapter 9|50 pages Control of traction and powertrains in EVs and HEVs chapter 10|53 pages Control of renewable power units and heat management units chapter|2 pages Epilogue 
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