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Distributed Model Predictive Control with Industrial Applications provides an overview of the latest advances in Distributed Model Predictive Controllers with special emphasis… Read more
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Distributed Model Predictive Control with Industrial Applications provides an overview of the latest advances in Distributed Model Predictive Controllers with special emphasis on Data and Iterative Learning Control (ILC), as well as emerging industrial applications in the security of cyber-physical systems. This book explores the most recent and modern approaches to the control of distributed systems on the framework of model predictive control while focusing on exploiting and controlling physical processes by means of data generated within the system and their interaction with the environments. The book begins with a general introduction of the subject material and subsequent chapters focus on main topics, while highlighting most recent contributions in the subject and open areas and research questions left unanswered. Algorithms related to the subject are explained concisely with some typical examples from literature to reinforce understanding.
Researchers, graduate and undergraduate students, engineers, and professionals in control systems engineering, electrical engineering, mechanical engineering, and mechatronics
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