四川大学学报（自然科学版）2025，Vol.62Issue(2)：309-324,16.DOI:10.19907/j.0490-6756.240086
具有量测和通信时延的随机极值搜索分布式优化
Distributed optimization with measurement and communication delays via stochastic extremum seeking
摘要
Abstract
In this paper,we propose a distributed algorithm based on stochastic extremum seeking to solve the distributed optimization problem in the presence of measurement and communication delays.Firstly,based on delayed measurements of local objective functions,we design a distributed algorithm via the stochas-tic extremum seeking method.Then,a stochastic averaging theorem for nonlinear systems with stochastic perturbation and multiple delays is established to analyze the convergence of the algorithm.Furthermore,by utilizing the established stochastic averaging theorem,we prove that the proposed algorithm is exponentially convergent in the almost sure sense and derive an upper bound on communication delays for the convergence of the algorithm.Numerical simulations are conducted to validate the effectiveness of the proposed algorithm.关键词
分布式优化/随机极值搜索/随机平均/时延Key words
Distributed optimization/Stochastic extremum seeking/Stochastic averaging/Delay分类
数学引用本文复制引用
张佩佩,刘淑君..具有量测和通信时延的随机极值搜索分布式优化[J].四川大学学报（自然科学版）,2025,62(2):309-324,16.基金项目
四川省自然科学基金(2024NSFSC0437) （2024NSFSC0437）
