Distributed Nonsmooth Consensus Optimization Problems with Coupled Inequality Constraint: A Proximal Approach

Shaolei Lu, Yue Wei*, Yulong Ding, Jinqiang Cui, Hao Fang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Distributed nonsmooth consensus optimization problems with the coupled inequality constraint are investigated in this paper. The global objective consists of convex and nonsmooth local cost functions. Each agent has only the information of its corresponding local cost function. Moreover, the coupled inequality constraint and consensus constraint are also considered. By employing the proximal method, a distributed proximal-gradient algorithm is proposed. The convergence result is theoretically analysed by using Lyapunov stability theory. It shows that the multi-agent system driven by the proposed algorithm can reach consensus and satisfy the coupled equality constraint at the optimal solution. In the end, the results of the simulation show the efficiency of the proposed algorithm.

Original languageEnglish
Title of host publicationProceedings of the 41st Chinese Control Conference, CCC 2022
EditorsZhijun Li, Jian Sun
PublisherIEEE Computer Society
Pages194-199
Number of pages6
ISBN (Electronic)9789887581536
DOIs
Publication statusPublished - 2022
Event41st Chinese Control Conference, CCC 2022 - Hefei, China
Duration: 25 Jul 202227 Jul 2022

Publication series

NameChinese Control Conference, CCC
Volume2022-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference41st Chinese Control Conference, CCC 2022
Country/TerritoryChina
CityHefei
Period25/07/2227/07/22

Keywords

  • Coupled Inequality Constraint
  • Distributed Optimization
  • Proximal Algorithm

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