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Stochastic consensus of continuous-time multi-agent systems with additive measurement noises

机译:具有加性测量噪声的连续时间多智能体系统的随机一致性

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This work is concerned with stochastic consensus of multi-agent systems with additive measurement noises, where the information exchange among agents is described by a directed graph. By combining the algebraic graph theory, matrix theory and stochastic analysis, the stochastic weak and strong consensus are examined. For the case with general digraphs, we give the necessary and sufficient conditions for the almost sure strong consensus and show that the mean square strong consensus and almost sure strong consensus are equivalent. We also give some necessary conditions and sufficient conditions for the mean square and almost sure weak consensus. Especially, the necessary and sufficient conditions for the mean square weak consensus are given for the case with undirected graphs.
机译:这项工作涉及具有加性测量噪声的多智能体系统的随机一致性,其中智能体之间的信息交换由有向图描述。通过将代数图论,矩阵论和随机分析相结合,检验了随机的弱共识和强共识。对于一般有向图的情况,我们给出了几乎肯定的强共识的必要和充分条件,并表明均方强共识和几乎确定强共识是等价的。我们还为均方和几乎肯定的弱共识提供了一些必要条件和充分条件。特别是,对于无向图的情况,给出了均方弱共识的充要条件。

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