报告人：施阳教授（IEEE Fellow, ASME Fellow,加拿大维多利亚大学教授）
报告题目:Model Predictive Control (MPC) for Autonomous Vehicles: Theory and Applications
报告人介绍:Yang SHIreceived the B.Sc. degree and Ph.D. degree both in the School of Marine Engineering at Northwestern Polytechnical University, Xi’an, in 1994 and 1998, respectively. He then received the Ph.D. degree in electrical and computer engineering from the University of Alberta, Edmonton, AB, Canada, in 2005. From 2005 to 2009, he was an Assistant Professor and Associate Professor in the Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. In 2009, he joined the University of Victoria, and now he is a Professor in the Department of Mechanical Engineering, University of Victoria, Victoria, British Columbia, Canada. His current research interests include networked and distributed systems, model predictive control (MPC), cyber-physical systems (CPS), robotics and mechatronics, navigation and control of autonomous systems (AUV and UAV), and energy system applications.
Dr. Shi received the University of Saskatchewan Student Union Teaching Excellence Award in 2007. At the University of Victoria, he received the Faculty of Engineering Teaching Excellence in 2012, and the Craigdarroch Silver Medal for Excellence in Research in 2015. He received the JSPS Invitation Fellowship (short-term) in 2013 and the Humboldt Research Fellowship for Experienced Researchers in 2017. His co-authored paper was awarded the 2017IEEE Transactions on Fuzzy SystemsOutstanding Paper Award. He is the founding Vice Chair of IEEE IES Technical Committee on Industrial Cyber-Physical Systems. Currently, he serves as Co-Editor-in-Chief ofIEEETrans. Industrial Electronics; he is Associate Editor forAutomatica, IEEE Trans. Control Systems Technology,IEEE/ASME Trans. Mechatrnonic, IEEE Trans. Cybernetics. He is a Fellow of IEEE, ASME and CSME, and a registered Professional Engineer in British Columbia, Canada.
报告内容:Research and development of autonomous vehicles (AUV, UAV, etc)have received great attention in the control and robotics communities due to their wide application areas.Model predictive control (MPC) is a promising paradigm for high-performance and cost-effective control of such dynamic systems, especially when some practical constraints need to be satisfied. This talk will firstly introduce an integrated path planning and tracking control for an autonomous underwater vehicle. Secondly, an event-based rendezvous control strategy for asynchronous multi-agent systems and experimental results will be presented.Finally, some future works will be discussed.