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Consensus Tracking of Multi-Agent Systems With Lipschitz-Type Node Dynamics and Switching Topologies

机译:具有Lipschitz型节点动力学和切换拓扑的多智能体系统的共识跟踪

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Distributed consensus tracking is addressed in this paper for multi-agent systems with Lipschitz-type node dynamics. The main contribution of this work is solving the consensus tracking problem without the assumption that the topology among followers is strongly connected and fixed. By using tools from $M$-matrix theory, a class of consensus tracking protocols based only on the relative states among neighboring agents is designed. By appropriately constructing Lyapunov function, it is proved that consensus tracking in the closed-loop multi-agent systems with a fixed topology having a directed spanning tree can be achieved if the feedback gain matrix and the coupling strength are suitably selected. Furthermore, with the assumption that each possible topology contains a directed spanning tree, it is theoretically shown that consensus tracking under switching directed topologies can be achieved if the control parameters are suitably selected and the dwell time is larger than a positive threshold. The results are then extended to the case where the communication topology contains a directed spanning tree only frequently as the system evolves with time. Finally, some numerical simulations are given to verify the theoretical analysis.
机译:本文针对具有Lipschitz型节点动力学的多智能体系统,解决了分布式共识跟踪问题。这项工作的主要贡献是解决了共识跟踪问题,而无需假设跟随者之间的拓扑结构是牢固连接和固定的。通过使用$ M $-矩阵理论的工具,设计了一类仅基于相邻代理之间的相对状态的共识跟踪协议。通过适当构造Lyapunov函数,证明了如果适当选择反馈增益矩阵和耦合强度,则可以在具有定向生成树的固定拓扑的闭环多智能体系统中实现共识跟踪。此外,假设每个可能的拓扑都包含有向生成树,则理论上表明,如果适当选择控制参数并且驻留时间大于正阈值,则可以在切换有向拓扑结构下实现共识跟踪。然后将结果扩展到通信拓扑仅在系统随时间变化时频繁包含定向生成树的情况。最后,通过数值模拟验证了理论分析的正确性。

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