Special Session

SS 03 - Coordination control of complex network systems and its industrial applications

SS 03 - Coordination control of complex network systems and its industrial applications


Guanghui Wen, Southeast University, China and Junjie Fu, Southeast University, China and Yuezu Lv, Beijing Institute of Technology, China and Chen Liu, RMIT University, Australia

Session Focus

Many industrial infrastructure systems can be described by models of evolving complex networks, where nodes represent the elements of the systems and links mimic the interactions among them. Prototypical examples including public transportation network, World Wide Web, smart grids and the multi-robot systems. The past few years have witnessed a strong upsurge of the study of complex networks in various fields, ranging from physics to mathematics and also to computer science and engineering. Key issues within the field of complex industrial networks include distributed resilience control, distributed optimization, privacy protection, and coordination. This special session focuses on theoretical and technological advances in distributed coordination, optimization and security control of complex networks, along with its various industrial applications.

Session Topics

  • Resilient consensus/synchronization for complex industrial networks
  • Cyber-security of industrial networks
  • Distributed coordination with sampled-data communication
  • Efficient coordination of multiple intelligent agent systems
  • Distributed coordination for state constrained industrial networks
  • Distributed control for industrial networks with input saturation
  • Distributed efficient tracking for complex industrial networks
  • Distributed fast coordination technique for industrial networks
  • Distributed efficient optimization for smart grids
  • Distributed accelerated optimization technique for complex networks
  • Artificial intelligence technology for constrained industrial networks

Bio of the organizers

Guanghui Wen (Senior Member, IEEE) received the Ph.D. degree in mechanical systems and control from Peking University, Beijing, China, in 2012. He is currently a Professor with the Department of Systems Science, Southeast University, Nanjing, China. His current research interests include autonomous intelligent systems, complex networked systems, distributed control and optimization, resilient control, and distributed reinforcement learning. He is a Reviewer for American Mathematical Review and is an Active Reviewer for many journals. He is currently an Associate Editor for the IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN INDUSTRIAL ELECTRONICS, the IEEE TRANSACTIONS ON SYSTEMS, MAN AND CYBERNETICS: SYSTEMS, the IEEE OPEN JOURNAL OF THE INDUSTRIAL ELECTRONICS SOCIETY, and the Asian Journal of Control. Since 2018, he has been named a Highly Cited Researcher by Clarivate Analytics. He is an IET Fellow. He was the recipient of the National Natural Science Fund for Excellent Young Scholars in 2017, the Australian Research Council Discovery Early Career Researcher Award in 2018, and the Asia Pacific Neural Network Society Young Researcher Award in 2019.
Junjie Fu (Member, IEEE) received the B.S. degree in 2011 and the Ph.D. degree in 2017, both from Peking University, Beijing, China. Since 2017, he has been with the Southeast University, Nanjing, China, where he is currently an Associate Professor. His current research interests include consensus and coordination in multi-agent systems, input saturation control and distributed optimization.
Yuezu Lv (Member, IEEE) received the B.S. and Ph.D. degrees in mechanical systems and control from Peking University, Beijing, China, in 2013 and 2018, respectively. From 2018-2020, he is a Lecture with the Department of Systems Science, School of Mathematics, Southeast University, Nanjing, China. He is currently an Associate Professor with Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology, Beijing, China. His research interests include cooperative control of multiagent systems, adaptive control, robust control of uncertain systems, and distributed resilient control.
Chen Liu received the bachelor’s degree (Hons.) in computer science, the master’s degree in information technology and the Ph.D. degree in Electrical & Electronic Engineering from RMIT University, Melbourne, VIC, Australia, in 2015, 2016 and 2021 respectively. He is currently a research fellow at RMIT’s School of Engineering. His current research interests include electric vehicles, smart grid, data mining, machine learning, and urban computing