ZOOM（会议ID：983 3576 8192，密码：201127）
报 告 人：韩清龙，斯威本科技大学教授
报告题目：Multi-Agent Systems Based Distributed Control and Optimization in Smart Grids
内容简介：With the widespread integration of renewable distributed energy sources such as wind generation, photovoltaic and solar panels, a traditional electrical network has been experiencing a huge revolution towards a smart grid in various terms of generation, transmission, distribution and usage, and so on. Such a revolution poses new theoretical and technical challenges in operation and management of smart grids. To address these challenges, a multi-agent system based strategy is developed to address control and optimization issues in smart grids, showcasing its strong ability in improving efficiency, reliability and scalability. In this talk, some backgrounds on smart grids from the perspective of multi-agent systems are introduced. Second, a distributed secondary control scheme with an event-triggered communication mechanism is presented to ensure frequency regulation and active power sharing of AC islanded microgrids while significantly reducing the utilization of communication resources. Third, a multi-objective distributed optimization method is provided to address current sharing and voltage regulation in DC microgrids. Furthermore, a distributed energy management issue of smart grids maximizing the total social welfare that balances generation-side expanses, user-side payments, and transmission line costs is addressed. Finally, some challenging issues are discussed for future investigation.
报告人简介：韩清龙教授，电气电子工程师协会会士，澳大利亚工程师协会会士，现为澳大利亚墨尔本斯威本科技大学副校长和杰出教授。在IEEE Transactions on Automatic Control, Automatica, IEEE Transactions on Cybernetics, IEEE Transactions on Signal Processing, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Circuit Systems I: Regular Papers等国际重要期刊上发表了308篇论文，其中IEEE Transactions和Automatica论文190篇。被国际学者SCI引用19820余次，SCI他引17530余次，SCI h-指数（h-index）: 77, 引用国家30余个。于2014年，2015年, 2016年, 2018年，2019年及2020年入选Clarivate Analytics (formerly Thomson Reuters）“高被引科学家”。获得2019年及2020年澳大利亚科研终身成就奖（《澳大利亚人报》评选），是工程与计算机类奖项的5名获奖人之一。 获得2020年IEEE系统、人与控制论学会Andrew P. Sage最佳论文奖（Best Transactions Paper Award），2020年IEEE工业电子学会IEEE Transactions on Industrial Informatics杰出论文奖（Outstanding Paper Award）, 2019年IEEE系统、人与控制论学会Andrew P. Sage最佳论文奖（Best Transactions Paper Award）。曾担任IEEE工业电子学会网络控制系统及应用专委会主席（2014-2017）。目前担任（曾担任）IEEE Transactions on Cybernetics, IEEE Transactions on Industrial Informatics, IEEE Industrial Electronics Magazine, IEEE/CAA Journal of Automatica Sinica, Control Engineering Practice，Information Sciences及International Journal of Automation and Computing等12种期刊的编委。
报 告 人：谢旻，香港城市大学教授
报告题目：Safety and Reliability of AI Systems–Some Challenging Issues
内容简介：There are plenty of research and development going on in the field Artificial intelligence (AI), and one example is the development of autonomous vehicle that will impact our daily life and travel pattern. However, although there are many product and service examples that demonstrates the potential of AI, there are serious and challenging problems with AI applications. How to evaluate the reliability of a product incorporating AI is a difficult question that we should raise at the beginning. In this talk, we will share some thoughts and experience from systems engineering perspective and discuss some of these issues. Some of the research related to software reliability, hardware reliability and combined systems can be strongly linked to this. AI applications also rely on the availability of large amount of data that may have other issues such as data uncertainty and integration.
报告人简介：Min Xie entered University of Science and Technology of China in 1978. He had a chance to go to Sweden in 1979 to continue his undergraduate study, and graduated from Royal Institute of Technology, Stockholm. He then received his PhD in 1987 from Linkoping University, Sweden, specializing in reliability and maintenance engineering. Dr Xie joined the National University of Singapore in 1991 as one of the first recipients of the prestigious Lee Kuan Yew Research Fellowship. After 20 years there, he moved to City University of Hong Kong as Chair Prof of Industrial Engineering in 2011. Prof Xie serves an editor, associate editor and on the editorial board of 20 established international journals. He has authored 8 books and over 300 SCI journal papers. Prof Xie has supervised over 50 PhD students and they hold regular position in banking, industry and academia in different continents. Prof Xie was elected fellow of IEEE in 2005 for his contribution to software and systems reliability.
报 告 人：黄捷，香港中文大学教授
报告题目：Distributed Formation Flying of Multiple Spacecraft Systems over Switching Networks
内容简介：The existing results on formation flying of multiple spacecraft systems are obtained under two key assumptions that the desired formation is static, and the communication network among the spacecraft systems is static and connected. In this talk, we will report our recent research progress on the formation flying for multiple spacecraft systems by relaxing these assumptions. For this purpose, we decompose the formation flying problem into the attitude control problem and the position control problem. We first synthesize a distributed attitude controller based on a distributed observer for the leader system producing the desired attitude and a purely decentralized attitude controller, and then further synthesize a distributed position controller based on another distributed observer for the leader system producing desired formations and a purely decentralized position controller. Our overall distributed controller is able to achieve a variety of time-varying formations for multiple spacecraft systems over jointly connected switching networks.
报告人简介：Jie Huang is now Choh-Ming Li Research Professor of Mechanical and Automation Engineering, CUHK. His research interests include nonlinear control, robotics and automation, networked control, and guidance and control of flight vehicles.
报 告 人：谢立华，南洋理工大学教授
报告题目：Efficient Reinforcement Learning-Based Control of Uncertain Nonlinear Systems
内容简介：Reinforcement learning (RL), which inspired by learning behaviour in nature, is a goal-oriented learning strategy wherein the agent learns the policy to optimize a pre-defined reward by interacting with the environment. For being data-driven, effectiveness in reaching optimal behavior, and adaptiveness to uncertain environment, RL has undergone rapid progress in control community. In this talk, we shall first discuss RL based disturbance rejection control for uncertain nonlinear systems with known nominal part. An extended state observer is first designed to estimate the system state and the total uncertainty. Based on the output of the observer, the control compensates for the total uncertainty in real time, and simultaneously, online approximates the optimal policy for the compensated system using a simulation of experience based RL technique. The approach does not require PE condition or probing signals. We further extend the study to systems with unknown nominal part, where a novel concurrent adaptive extended observer is developed to jointly estimate the parameters of the systems and the state, and a simulation of experience based RL is used to approximate the optimal policy.
报告人简介：Lihua Xie received the Ph.D. degree in electrical engineering from the University of Newcastle, Australia, in 1992. He was a faculty with the Department of Automatic Control, Nanjing University of Science and Technology from 1986 to 1989. Since 1992, he has been with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, where he is currently a professor and the Director of the Delta-NTU Corporate Laboratory for Cyber-Physical Systems. He served as the Head of Division of Control and Instrumentation from July 2011 to June 2014. His research areas include robust control, networked control, compressive sensing, localization and unmanned systems. He has been listed as a highly cited researcher by Thomson Routers and Clarivate Analytics annually since 2014. He is currently an Editor-in-Chief of Unmanned Systems and Associate Editor of IEEE Transactions on Control of Network Systems. He has served as an Editor of IET Book Series on Control and Associate Editor of IEEE Transactions on Automatic Control, IEEE Transactions on Control Systems Technology, Automatica, IEEE Transactions on Circuits and Systems-II, etc. He was an IEEE Distinguished Lecturer (2011-2014) and an elected member of the Board of Governors of IEEE Control System Society (Jan. 2016- Dec. 2018). He is Fellow of Academy of Engineering Singapore, Fellow of IEEE and Fellow of IFAC.
报 告 人：陈本美，香港中文大学教授
报告题目：Research Trends in Developing Intelligent Unmanned Systems
内容简介：The research and market for the unmanned aerial systems (UAS), or drones, has greatly expanded over the last few years. It is expected that the currently small civilian unmanned aircraft market is likely to become one of the major technological and economic stories of the modern age, due to a wide variety of possible applications and added value related to this potential technology. Modern unmanned aerial systems are gaining promising success because of their versatility, flexibility, low cost, and minimized risk of operation. In this talk, we highlight some key techniques involved and research trends in developing intelligent autonomous unmanned aerial vehicles, which include task and motion planning, flight control systems, perception and data processing. Some industrial application examples will be used as illustrations.
报告人简介：Ben M. Chen is currently a Professor of Mechanical and Automation Engineering at the Chinese University of Hong Kong and a Professor of Electrical and Computer Engineering (ECE) at the National University of Singapore (NUS). He was a Provost's Chair Professor in the NUS ECE Department, where he also served as the Director of Control, Intelligent Systems and Robotics Area, and Head of Control Science Group, NUS Temasek Laboratories. He was an Assistant Professor at the State University of New York at Stony Brook, in 1992–1993. His current research interests are in unmanned systems, robust control and control applications. Dr. Chen is an IEEE Fellow. He has authored/co-authored more than 450 journal and conference articles, and a dozen research monographs in control theory and applications, unmanned systems and financial market modeling. He had served on the editorial boards of a dozen international journals including Automatica and IEEE Transactions on Automatic Control. He currently serves as an Editor-in-Chief of Unmanned Systems. Dr. Chen has received a number of research awards. His research team has actively participated in international UAV competitions and won many championships in the contests.