Table of Contents
Part I. Control and estimation of robotized vehicles’ dynamics and kinematics1. Nonlinear optimal control and Lie algebra-based control
2. Flatness-based control in successive loops for complex nonlinear dynamical systems
3. Nonlinear optimal control for car-like front-wheel steered autonomous ground vehicles
4. Nonlinear optimal control for skid-steered autonomous ground vehicles
5. Flatness-based control in successive loops for 3-DOF unmanned surface vessels
6. Flatness-based control in successive loops for 3-DOF autonomous underwater vessels
7. Flatness-based control in successive loops for 6-DOF autonomous underwater vessels
8. Flatness-based control in successive loops for 6-DOF autonomous quadrotors
9. Flatness-based control in successive loops for 6-DOF autonomous octocopters
10. Nonlinear optimal control for 6-DOF tilt rotor autonomous quadrotors
11. Flatness-based adaptive neurofuzzy control of the four-wheel autonomous ground vehicles
12. H-infinity adaptive neurofuzzy control of the four-wheel autonomous ground vehicles
13. Fault diagnosis for four-wheel autonomous ground vehicles
Part II. Control and estimation of electric autonomous vehicles’ traction
14. Flatness-based control in successive loops for VSI-fed three-phase permanent magnet synchronous motors
15. Flatness-based control in successive loops for VSI-fed three-phase induction motors
16. Flatness-based control in successive loops and nonlinear optimal control for five-phase permanent magnet synchronous motors
17. Flatness-based control in successive loops for VSI-fed six-phase asynchronous motors
18. Flatness-based control in successive lops for nine-phase permanent magnet synchronous motors
19. Flatness-based control in successive loops of a vehicle’s clutch with actuation for permanent magnet linear synchronous motors
20. Flatness-based control in successive loops for electrohydraulic actuators
21. Flatness-based control in successive loops for electropneumatic actuators
22. Flatness-based adaptive neurofuzzy control of three-phase permanent magnet synchronous motors
23. H-infinity adaptive neurofuzzy control of three-phase permanent magnet synchronous motors
24. Fault diagnosis of a hybrid electric vehicle’s powertrain
Authors
Gerasimos Rigatos Research Director, Unit of Industrial Automation, Industrial Systems Institute, Rion Patras, Greece. Dr. Rigatos is Research Director at the Industrial Systems Institute, Greece. He has led research cooperation projects in the areas of nonlinear control, nonlinear filtering, and control of distributed parameter systems. His results have appeared in well-received research monographs. Since 2007, he has been awarded visiting professor positions at several academic institutes (Universit� Paris XI, France; Harper-Adams University College, UK; University of Northumbria, UK; University of Salerno, Italy; �cole Centrale de Nantes, France). He is a Senior Member of IEEE and a Member and CEng of the IET. He holds an Editor's position for the International Journal of Advanced Robotic Systems (SAGE) and for the Journal of Electrified Vehicles (SAE International). He received a PhD from the Department of Electrical and Computer Engineering of the National Technical University of Athens (NTUA), Greece, in 2000. Masoud Abbaszadeh Principal Research Engineer, GE Global Research, Niskayuna, NY, USA.Masoud Abbaszadeh received a PhD in Electrical and Computer Engineering from the University of Alberta in 2008. From 2008 to 2011, he was with Maplesoft, Ontario, Canada, as a Research Engineer. He was the principal developer of the MapleSim Control Design Toolbox and a member of a Maplesoft-Toyota joint research team. From 2011 to 2013, he was a Senior Research Engineer at United Technologies Research Center, CT, USA, working on advanced control systems, and complex systems modeling and simulation. Since 2013, he has been with GE Research Center, NY, USA, where he is currently a Principal Research Engineer and technical leader of the cyber-physical security and resilience portfolio. His research interests include estimation and detection theory, robust and nonlinear control, and machine learning with applications in cyber-physical resilience. He is an Associate Editor of IEEE Transactions on Control Systems Technology, a member of the IEEE CSS Conference Editorial Board, and has over 60 patents credited to his name.
Pierluigi Siano Professor, Department of Management and Innovation Systems, University of Salerno, Fisciano, Italy.Dr. Siano received a PhD in Information and Electrical Engineering from the University of Salerno, Salerno, Italy, in 2006. He is a Professor and the Scientific Director of the Smart Grids and Smart Cities Laboratory with the Department of Management and Innovation Systems of the University of Salerno. Since 2021, he has been a Distinguished Visiting Professor in the Department of Electrical and Electronic Engineering Science at the University of Johannesburg, South Africa. His research activities are focused on demand response, energy management, the integration of distributed energy resources in smart grids, electricity markets, and planning and management of power systems. He is a prolific author and, in 2019, 2020, and 2021, was awarded as a Highly Cited Researcher in Engineering by the ISI Web of Science Group. He is Editor for several IEEE journals, including 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.
Patrice Wira Professor, Institut de Recherche en Informatique, Math�matiques, Automatique et Signal, Universit� de Haute Alsace; Director, Institut Universitaire de Technologie de Mulhouse, Mulhouse, France. Dr. Wira received a PhD in Electrical Engineering from Universit� de Haute Alsace in 2002. He has published several journal papers, book chapters, and conference papers. He has also chaired and co-chaired numerous sessions and special sessions on intelligent control and machine learning issues. His current research interests focus on artificial neural networks, adaptive control systems, neuro-control, and especially their applicability to robotics and active power filtering. He has been a senior member of IEEE since 2013. He has served as an associate editor for the Energy section of the Heliyon Journal (Cell Press) since 2022.
