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学术报告第201737期

发布时间:2017-06-27 编辑:admin 来源:华科自动化学院

报告题目Distributed optimization over Lossy Communication networks

报 人:吴均峰 教授浙江大学

报告时间2017年7月3日10:00

报告地点南一楼中311

Abstract:

We consider distributed optimization by a collection of nodes, each having knowledge of its own convex objective function. Information exchange among the nodes occurs over a communication network described by a directed graph. The goal of the whole network is to minimize the sum of the objective functions. We consider the case where the communication networks may be subject to link failures with certain probability. We develop a robustified distributed optimization algorithm. Under the assumption that the undergoing network is strongly connected and the probability of link failure is strictly less than one, we show that the robustified algorithm is able to solve the distributed optimization problem in the sense that the algorithm converges to an optimal solution almost surely. In case study, we will apply the proposed algorithm to distributed energy resources (DER) coordination problem for power grids, where the goal is to minimize the total generation cost while meeting total demand and satisfying individual generator output limit.

Biography:

Junfeng Wu received the B.Eng. from the Department of Automatic Control, Zhejiang University, Hangzhou, China, in 2009 and the Ph.D. degree in Electrical and Computer Engineering from the Hong Kong University of Science and Technology, Hong Kong, in 2013. From September to December 2013, he was a Research Associate in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology, Hong Kong. He was a Postdoctoral Researcher at ACCESS (Autonomic Complex Communication networks, Signals and Systems) Linnaeus Center, School of Electrical Engineering, KTH Royal Institute of Technology, Sweden from 2014 and 2017. He is currently with the College of Control Science and Engineering, Zhejiang University, P. R. China. His research interests include networked control systems, state estimation, and wireless sensor networks, multi-agent systems.