Title 1: Distributed Control and Optimization with Applications to Power and Energy Systems
Title 2: A new overview of adaptive control
Professor Zhengtao Ding
University of Manchester, UK
April 13th, 2023, 15:00-17:00 PM, C317
Abstract
There are many challenges and opportunities, such as net zero, internet of things, big data, machine learning, smart grid, in the area of network-connected systems and control applications, in particular, in the areas relating to distributed learning, optimization, decision making and control. New energy resources are distributed in nature, and there are demands in distributed control and resource optimization for energy and power systems. Recent advances in distributed networks along with the development of complex and large-scale subsystems have significantly incentivized coordination and cooperation over multi-agent systems. Many distributed algorithms have been developed in the areas relating to distributed machine learning, optimization and differential games, which aim at making decisions and control in local level, and achieving certain global objectives through network communications. Certain control perspectives such as convergence, nonlinearity, adaptation and consensus are clearly essential in the design and analysis of the distributed algorithms. This talk will cover some recent activities in relation to distributed algorithms and applications carried out in the speaker’s group, including distributed optimization using algorithms based on multi-agents, cooperative and competitive machine learning over networks, applications of distributed optimization and machine learning algorithms to new energy and power systems, in particular, the applications in the areas of distributed power and energy storage resource management, load prediction and day ahead bidding, and distributed optimization and control for wind farm operations.
Bio-sketch
Zhengtao Ding received B.Eng. degree from Tsinghua University, Beijing, China, and M.Sc. degree in systems and control, and the Ph.D. degree in control systems from the University of Manchester Institute of Science and Technology, Manchester, U.K. After working in Singapore for ten years, he joined the University of Manchester in 2003, where he is currently Professor of Control Systems, and the Head of Control, Robotics and Communication Division. He is the author of the book: Nonlinear and Adaptive Control Systems (IET, 2013), and a co-author of two other books, and has published over 300 research articles. His research interests include nonlinear and adaptive control theory and their applications, more recently on distributed optimization and distributed machine learning, with applications to power systems and robotics. Prof. Ding has served as the Editor in Chief of Drones and Autonomous Vehicles, the Subject Chef Editor of Nonlinear Control for Frontiers, and Associate Editor for the IEEE Transactions on Automatic Control, IEEE Control Systems Letters, and several other journals. He is a member of IEEE Technical Committee on Nonlinear Systems and Control, IEEE Technical Committee on Intelligent Control, and IFAC Technical Committee on Adaptive and Learning Systems. He is a Fellow of Alan Turing Institute, the UK’s national institute for AI.
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