|Program at a Glance|
|Thursday, March 9, 2023|
Room 1, P111, 10:30-12:10
New Applications of Control
Room 1, P111, 13:30-15:10
|Friday, March 10, 2023|
|ISCS Plenary Lecture
Distributed Coordination in Multi-agent Systems:
Algorithms and Applications
Prism Hall, 9:30-10:20
Computational Methods in Control
Room 1, P111, 10:40-12:20
Control of Robots and Mechanical Systems
Room 1, P111, 13:40-15:20
|Saturday, March 11, 2023|
Control for Energy Saving
Room 1, P111, 9:30-11:10
Kimura Award Commemorative Lecture
Control Theory for Generalized Coordination
of Multi-robot Systems
Prism Hall, 13:00-13:40
While autonomous systems that perform solo missions can yield significant benefits, greater efficiency and operational capability will be realized from teams of autonomous systems operating in a coordinated fashion. Potential applications for networked multiple autonomous systems include environmental monitoring, search and rescue, space-based interferometers, hazardous material handling, and combat, surveillance, and reconnaissance systems. Networked multi-agent systems place high demands on features such as low cost, high adaptivity and scalability, increased flexibility, great robustness, and easy maintenance. To meet these demands, the current trend is to design distributed algorithms that rely on only local information and local interaction to achieve global group behavior.
The purpose of this talk is to overview our recent research in distributed control, estimation and optimization in networked multi-agent systems. For distributed control, results on distributed synchronization for agents with various dynamics, distributed single-leader collective tracking with reduced interaction and partial measurements, and distributed multi-leader containment control with local interaction will be introduced. For distributed estimation, results on fully distributed information fusion with multiple networked sensors will be introduced, under very mild assumptions on local observability, communication graphs, and models. For distributed optimization, results on distributed convex optimization will be introduced, under realistic challenges such as non-identical constraints, fully distributed design, and time-varying cost functions. Application examples in multi-vehicle cooperative control will also be introduced.
Wei Ren is currently a Professor with the Department of Electrical and Computer Engineering, University of California, Riverside. He received the Ph.D. degree in Electrical Engineering from Brigham Young University, Provo, UT, in 2004. Prior to joining UC Riverside, he was a faculty member at Utah State University and a postdoctoral research associate at the University of Maryland, College Park. His research focuses on distributed control of multi-agent systems and autonomous control of unmanned vehicles. Dr. Ren was a recipient of the IEEE Control Systems Society Antonio Ruberti Young Researcher Prize in 2017 and the National Science Foundation CAREER Award in 2008. He is an IEEE Fellow and an IEEE Control Systems Society Distinguished Lecturer.
The ISCS Plenary Lecture is given on the Distinguished Lecturer Program of the IEEE Control Systems Society. IEEE members can attend the lecture free of charge irrespective of the participation in the ISCS.
Control methods for multi-robot systems have massive potential for practical applications, including autonomous vehicles, cluster satellites, and sensor networks. In many applications, cooperative coordination plays a central role. Various methods have been developed for coordination tasks, such as consensus, formation, coverage, and pursuit. Most developments of control methods have taken place for each task individually so far. This talk aims to provide a systematic method to design controllers applicable to a wide range of coordination tasks for multi-robot systems. To this end, we describe the coordination problem in a unified manner instead of handling various problems individually. Then, a complete solution to this problem is provided compactly using the tools of group and graph theories. This talk presents the core ideas of the control theory specific to multi-robot systems and shows practical examples of coordination tasks achievable through this theory.
Kazunori Sakurama received a Bachelor's degree in engineering, and Master's and Doctoral degrees in Informatics from Kyoto University, Kyoto, Japan, in 1999, 2001, and 2004, respectively. He was an Assistant Professor at the University of Electro-Communications, Tokyo, Japan, from 2004 to 2011 and an Associate Professor at the Graduate School of Engineering, Tottori University, Tottori, Japan, from 2011 to 2018. He is currently an Associate Professor at the Graduate School of Informatics, Kyoto University, Kyoto, Japan. His research interests include control of multi-agent systems, networked systems, and nonlinear systems. He received the Control Division Conference Awards in 2014 and 2015, and the Control Division Pioneer Award in 2017 from the Society of Instrument and Control Engineers (SICE). He is a member of IEEE, SICE, and the Institute of Systems, Control, and Information Engineers (ISCIE).