Prof. Xiuxian Li
Tongji University, China
Speech title：Distributed Online Optimization Over Directed Networks with Coupled Inequality Constraints
In this talk, we investigates the distributed online optimization problem over a multi-agent network subject to local set constraints and coupled inequality constraints, which has a lot of applications in many areas, such as wireless sensor networks, power systems and plug-in electric vehicles. In this problem, the cost function at each time step is the sum of local cost functions with each of them being gradually revealed to its corresponding agent, and meanwhile only local functions in coupled inequality constraints are accessible to each agent. To address this problem, a modified primal-dual algorithm, called distributed online primal-dual push-sum algorithm (DOPP), is developed in this talk, which does not rest on any assumption on parameter boundedness and is applicable to unbalanced networks. It is shown that the proposed algorithm is sublinear for both the dynamic regret and the violation of coupled inequality constraints. Finally, the theoretical results are supported by a simulation example.
Xiuxian Li received the B.S. degree in mathematics and applied mathematics and the M.S. degree in pure mathematics from Shandong University, Jinan, Shandong, China, in 2009 and 2012, respectively, and the Ph.D. degree in mechanical engineering from the University of Hong Kong, Hong Kong, in 2016. Since 2016, he has been a research fellow with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, and a senior research associate with the Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong. He held a visiting position at King Abdullah University of Science and Technology, Saudi Arabia, in September 2019. He has served as associate editor, chair, co-chair, organizer for a few international conferences, such as CCC, CAC, ASCC, IEEE ICCA. He is currently a professor with the Department of Control Science and Engineering, College of Electronics and Information Engineering, and Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University.