Distributed hybrid optimization for multi-agent systems

查看全文 作　　者：TAN [1,2]XueGang;YUAN [2]Yang;HE [2]WangLi;CAO [1]JinDe;HUANG [3]TingWen

机构地区：[1]School of Mathematics,Southeast University,Nanjing 210096,China;[2]Key Laboratory of Smart Manufacturing in Energy Chemical Process,Ministry of Education,East China University of Science and Technology,Shanghai 200237,China;[3]Department of Science,Texas A&M University at Qatar,Doha 23874,Qatar

出　　处：《Science China(Technological Sciences)》索引2022年第65卷第8期,共10页

基　　金：supported in part by the National Key Research and Development Program of China (Grant No. 2020YFA0714300);the National Natural Science Foundation of China (Grant Nos. 61833005 and 62003084);the Fundamental Research Funds for the Central Universities;the Jiangsu Provincial Key Laboratory of Networked Collective Intelligence (Grant No. BM2017002)。 摘　　要：This paper addresses the distributed optimization problems of multi-agent systems using a distributed hybrid impulsive protocol.The objective is to ensure the agents achieve the state consensus and optimize the aggregate objective functions assigned for each agent with distributed manner. We establish two criteria related to the optimality condition and the impulsive gain upper estimation, and propose a distributed hybrid impulsive optimal protocol, which includes two terms: the local averaging term in the continuous interval and the term involving the gradient information at impulsive instants. The simulation results show that the optimal consensus can be realized under the distributed hybrid impulsive optimization algorithm. 关键词：multi-agent systems hybrid impulsive strategy optimal consensus distributed optimization

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Distributed hybrid optimization for multi-agent systems

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