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Bipartite consensus behavior of agents in networked systems

机译:网络系统中智能体的双向共识行为

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In this paper, bipartite consensus behavior of multiple agents in networked systems with single-integrator dynamics under directed signed graphs is investigated. It is assumed that the agents can be classified into two antagonistic groups such that the interactions between agents belonging to the same group are cooperative, while interactions between agents belonging to different groups are antagonistic. Positive weights are used to model the cooperative interactions and negative weights are used to model the antagonistic interactions. Firstly, the behavior of continuous-time agents with weighted, signed, directed graph is analyzed, including the strongly connected graph and the graph which has a spanning tree. Secondly, sampled-data based bipartite consensus of continuous-time multi-agent systems is derived. Thirdly, it is extended to the general weakly connected signed graphs. Finally, the theoretical results are illustrated by some simulations.
机译:本文研究了在有向有向图下具有单积分动力学的网络系统中多主体的双向共识行为。假定可以将药剂分为两个拮抗组,使得属于同一组的药剂之间的相互作用是协同的,而属于不同组的药剂之间的相互作用是拮抗的。正权重用于建模协作相互作用,负权重用于建模拮抗相互作用。首先,分析了具有权重,有符号,有向图的连续时间智能体的行为,包括强连通图和具有生成树的图。其次,推导了基于采样数据的连续时间多智能体系统的二分共识。第三,它扩展到一般的弱连接有符号图。最后,通过一些仿真说明了理论结果。

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