A compendium of the authors’ recently published results, this book discusses sliding mode control of uncertain nonlinear systems, with a particular emphasis on advanced and optimization based algorithms. The authors survey classical sliding mode control theory and introduce four new methods of advanced sliding mode control. They analyze classical theory and advanced algorithms, with numerical results complementing the theoretical treatment. Case studies examine applications of the algorithms to complex robotics and power grid problems.
Advanced and Optimization Based Sliding Mode Control: Theory and Applications is the first book to systematize the theory of optimization based higher order sliding mode control and illustrate advanced algorithms and their applications to real problems. It presents systematic treatment of event-triggered and model based event-triggered sliding mode control schemes, including schemes in combination with model predictive control, and presents adaptive algorithms as well as algorithms capable of dealing with state and input constraints. Additionally, the book includes simulations and experimental results obtained by applying the presented control strategies to real complex systems.
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A. Ferrara is full professor of automatic control in the department of electrical, computer, and biomedical engineering (ECBE) at the University of Pavia. She has authored or co-authored more than 380 scientific papers and three scientific books, and she has contributed invited chapters to 23 edited volumes. She is associate editor of IEEE Control Systems Magazine, subject editor of International Journal of Robust and Nonlinear Control, and associate editor of Automatica. She is chair of the European Control Association (EUCA) Conference Editorial Board. Her research activities focus on sliding mode control and nonlinear control with applications to the automotive industry, robotics, power networks, process control, and vehicular traffic systems.
G. P. Incremona is assistant professor of automatic control at the Politecnico di Milano. He is a recipient of the 2018 Best Young Author Paper Award from the Italian chapter of the IEEE Control Systems Society and a member of the conference editorial boards of the IEEE Control Systems Society and the European Control Association. His research focuses on variable structure control, optimal control, and networked control with applications to robotics, power systems, and glycemia control in diabetic subjects.
M. Cucuzzella is a postdoctoral researcher at the University of Groningen. He received his PhD in electronics, computer science, and electrical engineering from the University of Pavia under the supervision of Professor Ferrara. He received the IEEE Italy Section Award for the best PhD thesis on new technological challenges in energy and industry and the SIDRA Award for the best PhD thesis in the field of systems and control engineering. He is an associate editor for the European Control Conference. His research focuses on nonlinear control with applications to power networks.
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Paperback. Condition: New. A compendium of the authors' recently published results, this book discusses sliding mode control of uncertain nonlinear systems, with a particular emphasis on advanced and optimization based algorithms. The authors survey classical sliding mode control theory and introduce four new methods of advanced sliding mode control. They analyze classical theory and advanced algorithms, with numerical results complementing the theoretical treatment. Case studies examine applications of the algorithms to complex robotics and power grid problems. Advanced and Optimization Based Sliding Mode Control: Theory and Applications is the first book to systematize the theory of optimization based higher order sliding mode control and illustrate advanced algorithms and their applications to real problems. It presents systematic treatment of event-triggered and model based event-triggered sliding mode control schemes, including schemes in combination with model predictive control, and presents adaptive algorithms as well as algorithms capable of dealing with state and input constraints. Additionally, the book includes simulations and experimental results obtained by applying the presented control strategies to real complex systems. Seller Inventory # LU-9781611975833
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