会议室：腾讯会议室ID 806 382 299
Modelling and Approximation in Complex Networked Systems
Complex networked systems are becoming ever more prevalent in our society. The term ‘complex’ refers to large-scale topological features of the interactions as well as high-dimensional dynamics from different physical domains. The overwhelming complexity of these systems poses significant challenges in the systems and control domain how to effectively and efficiently analyse and control these systems. In this report, I will briefly introduce my research on scalable modelling and complexity reduction in dynamic networked systems. The first part considers identifiability problem in complex networks, which aims to allocate external excitation signals such that all the dynamics in a network can be identified from data. The second part is focused on model-order reduction of structured networked systems that is to reduce the dimension of a complex network system while retain all the salient structures and dynamics in the network avoiding unnecessary redundancy.
Xiaodong Cheng is a postdoctoral researcher with the Department of Electrical Engineering, Eindhoven University of Technology, the Netherlands. He received the B.S. and M.S. degrees in School of Electronics and Information from Northwestern Polytechnic University, Xi'an, China, in 2011 and 2014, respectively. In November 2018, he received the Ph.D. degree (with distinction cum laude) in systems and control from the University of Groningen, the Netherlands. His main research interests include model reduction, distributed control, and identification of networked systems. He is the recipient of the Paper Prize Award of IFAC Journal Automatica in 2020.