Consensus stability analysis for stochastic multi-agent systems with multiplicative measurement noises and Markovian switching topologies

IF 1.1 Q2 MATHEMATICS, APPLIED

Numerical Algebra Control and Optimization Pub Date : 2021-01-01 DOI:10.3934/naco.2021024

Xiaojin Huang, Hongfu Yang, Jianhua Huang

引用次数: 0

Abstract

We investigate the consensus stability for linear stochastic multi-agent systems with multiplicative noises and Markovian random graphs and investigate the asymptotic consensus in the mean square sense for the systems. To establish the consensus stability for the systems, we analysis the consensus error systems by developing general stochastic differential equation with jumps, matrix theory and algebraic graph theory, and then show that the error consensus in the mean square sense finally tending to zero as time goes on is determined by the strongly connected property of union of topologies. Finally, we provide an example to demonstrate the effectiveness of our theoretical results.

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具有乘性测量噪声和马尔可夫切换拓扑的随机多智能体系统的一致性稳定性分析

研究了具有乘性噪声和马尔可夫随机图的线性随机多智能体系统的一致性稳定性，并研究了系统在均方意义上的渐近一致性。为了建立系统的一致性稳定性，利用一般跳跃随机微分方程、矩阵理论和代数图理论对一致性误差系统进行了分析，并证明了误差一致性在均方意义上随着时间的推移最终趋于零是由拓扑并的强连通性质决定的。最后，通过实例验证了理论结果的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Numerical Algebra Control and Optimization MATHEMATICS, APPLIED-

CiteScore

3.10

自引率

0.00%

发文量

期刊介绍： Numerical Algebra, Control and Optimization (NACO) aims at publishing original papers on any non-trivial interplay between control and optimization, and numerical techniques for their underlying linear and nonlinear algebraic systems. Topics of interest to NACO include the following: original research in theory, algorithms and applications of optimization; numerical methods for linear and nonlinear algebraic systems arising in modelling, control and optimisation; and original theoretical and applied research and development in the control of systems including all facets of control theory and its applications. In the application areas, special interests are on artificial intelligence and data sciences. The journal also welcomes expository submissions on subjects of current relevance to readers of the journal. The publication of papers in NACO is free of charge.