Title: Centralized, Distributed, and Coalitional Model Predictive Control
Speaker: Prof. J. M. Maestre, University of Seville
Abstract: Model predictive control (MPC) has become of the most popular control techniques due its flexibility. Issues such as constraints on the control problem variables, delays in the system dynamics, and multiple objectives can be handled explicitly in the MPC framework. The evolution of computer, information and communication technologies has motivated the application of MPC to problems beyond its scope years ago and the development multiple noncentralized MPC approaches. The goal of this talk is to present a coherent and easily accessible overview regarding model predictive control and some of the latest developments regarding its application to large-scale cyber physical systems, including topics such as coalitional control and human in the loop.
Biography: J.M. Maestre received the Ph.D. degree in automation and robotics from the University of Seville, where he works as associate professor. He has also worked in LTH at Lund University, TU Delft, and Tokyo Institute of Technology, where he is currently funded by the Japanese Society for the Promotion of Science. Besides his PhD, which was awarded with the extraordinary prize of the University of Seville, he also has master degrees in intelligent buildings and economics. His main research interests are the control of distributed systems and the integration of service robots in the smart home. He has authored and coauthored more than one hundred publications regarding these topics. He is also editor
of the books “Service robotics within the Digital Home: Applications and Future Prospects” (Springer, 2011), “Distributed Model Predictive Control Made Easy” (Springer, 2014), and “Domotica para Ingenieros” (Paraninfo, 2015). Finally, he is one of the founders of the technological firms Idener and Eskesso.
Blog: 9月5日に University of Sevilleの J. M. Maestre先生が来塾されて、「Centralized, Distributed, and Coalitional Model Predictive Control」のセミナーを開催しました。モデル予測制御の基礎から様々な応用展開の話を分かりやすく解説して頂きました。