应航天学院王振华副教授的邀请，德国卡塞尔大学Zonglin Liu（刘宗林）博士将于2023年7月17日（周一）在我校举行学术讲座，欢迎感兴趣的师生参加。

一、报告时间

2023年7月17日（周一）16:30-18:00

二、报告地点

正心楼306室

三、报告题目

Resilience of Time-Varying Communication Graphs in Multi-Agent Systems

四、摘要

System performance of distributed control systems and networked computing systems is strongly dependent of the underlying communication topology. This report considers the rarely studied problem of how the topology can maintain resilience by reconfiguration in case that agents leave or join the network during online operation. Existing optimization-based approaches which reconfigure the entire network typically cannot be used in this case, since the computational burden is too high in online application. Thus, a novel combined offline-online scheme is proposed, which optimizes the topology for high convergence rate (of e.g. consensus problems, synchronization problems, distributed optimization problems, or distributed state estimation problems) while providing guarantees for the robustness against agent failures.

In the offline part, an optimization of the entire topology is performed with novel constraints to prepare resilience of the online process. In the latter part, the proposed scheme guarantees that robustness is maintained for joining agents and if a specified number of agents leave the network. In simulation, the proposed scheme is compared to existing approaches and the advantages of the online-offline process are demonstrated.

五、个人简介

Dr.-Ing. Zonglin Liu received B.Sc. from the Harbin Institute of Technology, China, in 2012, and M.Sc from the University of Kassel, Germany, in 2015. From 2015 to 2021, he was a doctoral researcher at the Control and System Theory Group of the University of Kassel, and received the best score Summa Cum Laude for his doctoral thesis with the title ''Optimizing Control of Distributed Cyber-Physical Systems''. From 2021 ongoing, he works as a Senior researcher in the same department. His research activities include developing methods for optimal and predictive control of cyber-physical systems with uncertainties, efficient distributed solutions for large-scale optimization problems, and use of system- and control-theoretic principles to help in diminishing the Covid pandemic.