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Distributed Optimization and Scaling Design for Solving Sylvester Equations

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摘要 This paper develops distributed algorithms for solving Sylvester equations.The authors transform solving Sylvester equations into a distributed optimization problem,unifying all eight standard distributed matrix structures.Then the authors propose a distributed algorithm to find the least squares solution and achieve an explicit linear convergence rate.These results are obtained by carefully choosing the step-size of the algorithm,which requires particular information of data and Laplacian matrices.To avoid these centralized quantities,the authors further develop a distributed scaling technique by using local information only.As a result,the proposed distributed algorithm along with the distributed scaling design yields a universal method for solving Sylvester equations over a multi-agent network with the constant step-size freely chosen from configurable intervals.Finally,the authors provide three examples to illustrate the effectiveness of the proposed algorithms.
出处 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2024年第6期2487-2510,共24页 系统科学与复杂性学报(英文版)
基金 supported in part by the National Natural Science Foundation of China under Grant Nos.62103003,72171171,62073035,61973002 in part by the Anhui Provincial Natural Science Foundation under Grant No.2008085J32。
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