引用本文:时侠圣,林志赟,王雪松,董世建.非平衡有向网络的完全分布式凸优化[J].控制理论与应用,2022,39(6):1071~1078.[点击复制]
SHI Xia-sheng,LIN Zhi-yun,WANG Xue-song,Dong Shi-jian.A fully distributed convex optimization algorithm over the unbalanced directed network[J].Control Theory and Technology,2022,39(6):1071~1078.[点击复制]
非平衡有向网络的完全分布式凸优化
A fully distributed convex optimization algorithm over the unbalanced directed network
摘要点击 1431  全文点击 446  投稿时间：2021-05-10  修订日期：2021-10-18
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DOI编号  10.7641/CTA.2021.10389
  2022,39(6):1071-1078
中文关键词  分布式凸优化  非平衡有向网络  非负余量  分布式步长
英文关键词  distributed convex optimization  unbalanced directed network  non-negative surplus  distributed step-size
基金项目  国家自然科学基金项目(62173118), 江苏省自然科学基金项目(BK20210492, BK20210493), 中央高校基本科研业务费青年科技基金项目 (2021QN1052)资助.
作者单位E-mail
时侠圣 中国矿业大学 shixiasheng@cumt.edu.cn 
林志赟 杭州电子科技大学  
王雪松* 中国矿业大学 wangxuesongcumt@163.com 
董世建 中国矿业大学  
中文摘要
      分布式凸优化问题的目的是如何以分布式方法最小化局部智能体成本函数和, 而现有分布式算法的控制 步长选取依赖于系统智能体个数、伴随矩阵等全局性信息, 有悖于分布式算法的初衷. 针对此问题, 提出一种基于 非平衡有向网络的完全分布式凸优化算法(FDCOA). 基于多智能体一致性理论和梯度跟踪技术, 设计了一种非负余 量迭代策略, 使得FDCOA的控制步长收敛范围仅与智能体局部信息相关, 进而实现控制步长的分布式设置. 进一步 分析了FDCOA在固定强连通和时变强连通网络情形下的收敛性. 仿真结果表明本文构建的分布式控制步长选取方 法对FDCOA在有向非平衡下的分布式凸优化问题是有效的.
英文摘要
      The aim of the distributed convex optimization problem is how to minimize the sum of all local agent cost functions, and however, the control step-size of the existing distributed algorithms is related to the global information, such as agent numbers of system, adjacency matrix, which is contracted to the distributed algorithm. For solving this problem, a fully distributed convex optimization algorithm (FDCOA) is proposed over the unbalanced directed network. Based on the multi-agent consensus theory and gradient tracking technology, a non-negative surplus iteration scheme is designed to make the convergence range of the control step-size only related to the local information of each agent, and then to realize the uncoordinated and distributed setting of the control step-size. Further, the convergence analysis of the FDCOA is given for both fixed and time-varying strongly connected digraphs. The experimental results show that the designed distributed selection method of the control step-size is effective for the application of FDCOA to the distributed convex optimization problems under an unbalanced directed network.