文献类型：期刊文献

英文题名：Distributed Asynchronous Optimization of Multiagent Systems: Convergence Analysis and Its Application

作者：Nie, Rong[1];Du, Wenli[1,2];Wang, Ting[1];Li, Zhongmei[1];He, Shuping[3,4,5]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Engn Res Ctr Proc Syst Engn, Minist Educ, Shanghai 200231, Peoples R China;[3]Anhui Univ, Sch Elect Engn & Automat, Informat Mat & Intelligent Sensing Lab Anhui Prov, Hefei 230601, Peoples R China;[4]Chengdu Univ, Sch Elect Informat & Elect Engn, Chengdu 610106, Peoples R China;[5]Hefei Comprehens Natl Sci Ctr, Inst Artificial Intelligence, Hefei 230026, Peoples R China

年份：2024

卷号：20

期号：6

起止页码：8983

外文期刊名：IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

收录：;EI(收录号：20241515881203);WOS:【SCI-EXPANDED(收录号:WOS:001197924100001)】；

基金：No Statement Available

语种：英文

外文关键词：Optimization; Convergence; Heuristic algorithms; Multi-agent systems; Informatics; Distributed algorithms; Vectors; Asynchronous communication; bilaterally adjustable adaptive step size; constraint; distributed optimization; multiagent systems (MASs)

摘要：This article focuses on solving a distributed convex optimization problem of multiagent systems with multiple inequality constraints. Considering communications between agents are prone to failures and not synchronized among themselves in some cases, a novel asynchronous adaptive step sizes-DIGing algorithm is proposed through integrating the projection operators and logic-and framework. In specific, a bilaterally adjustable adaptive step size mechanism is introduced to automatically abandon the irrational evolutionary route which relieves the limitations of traditional DIGing algorithm. By adopting the operator theory, the almost sure convergence of the proposed algorithm under asynchronous communication is proved. Finally, the theoretical and simulation results for the plantwide optimization problem in the ethylene production process illustrate the effectiveness of the proposed algorithm.