
Distributed Event-triggered Control
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Bin Cheng received his B.S. degree in mechanical engineering and automation from the School of Mechanical Engineering, University of Science & Technology Beijing, China, in 2015 and his Ph.D. in dynamical systems and control from the Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing, China, in 2020. He is currently an Assistant Professor at the Department of Control Science and Engineering, College of Electronics and Information Engineering, Tongji University, Shanghai, China, and at the Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, China. His current research interests include cooperative control of multi-agent systems, adaptive control, and event-triggered control. He won the Best Student Paper Finalist Award at the IEEE ICCA 2019. He was selected for the Sailing Program (Science and Technology Innovation Action Plan of Shanghai) in 2021.
Weihao Song received his B.S. degree in flight vehicle design and engineering and his Ph.D. degree in aeronautical and astronautical science and technology from the Beijing Institute of Technology, Beijing, China, in 2016 and 2021, respectively. From May 2019 to May 2020, he was a Visiting Scholar with the Department of Computer Science, Brunel University London, London, United Kingdom. He is currently a Postdoctoral Researcher with the College of Engineering, Peking University, Beijing, China. His research interests include Bayesian state estimation, distributed state estimation, nonlinear filtering, and networked control systems. He received the Beijing Excellent Doctoral Dissertation Award in 2022.
Shiqi Zhang received his B.S. degree and Ph.D. in mechanical engineering from the Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing, China, in 2017 and 2022, respectively.His current research interests include cooperative control of multi-agent systems, distributed robust and optimal control, distributed optimization and reinforcement learning.Content
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