Distributed Model Predictive Control with Industrial Applications
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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.
- Provides modern, concise, and precise explanations of theoretical concepts with industrial case studies
- Highlights the most recent contributions in the area of distributed model predictive controllers
- Explains algorithms related to the subject typical examples from literature to reinforce understanding
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Magdi S. Mahmoud is a distinguished professor at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. He has been faculty member at different universities worldwide including Egypt (CU, AUC), Kuwait (KU), UAE (UAEU), UK (UMIST), USA (Pitt, Case Western), Singapore (Nanyang), and Australia (Adelaide). He lectured in Venezuela (Caracas), Germany (Hanover), UK (Kent), USA (UoSA), Canada (Montreal) and China (BIT, Yanshan). He is the principal author of 51 books, inclusive book-chapters, and author/co-author of more than 610 peer-reviewed papers. He is a fellow of the IEE and a senior member of the IEEE, the CEI (UK). He is currently actively engaged in teaching and research in the development of modern methodologies to distributed control and filtering, networked control systems, fault-tolerant systems, cyberphysical systems, and information technology.
Mojeed Oyedeji is presently a post-doctoral candidate at the Control & Instrumentation Engineering (CIE) Department, King Fahd University of Petroleum and Minerals (KFUPM). He obtained his PhD and MSc Degrees in Systems and Control Engineering from KFUPM in 2020 and 2017 respectively. His research interests are in the fields of renewable energy, distributed and model predictive control, and artificial intelligence.
