输入约束下高阶智能体均方一致性研究

Mean Square Consensus of High-Order Multi-Agent with Constrained Control Input

  • 摘要: 该文对高阶多智能体系统拓扑结构Markov切换且控制输入受到非凸约束时的均方一致性问题进行了研究。首先,引入了一个非凸约束算子,并且根据多智能体系统中邻居节点信息设计了系统的控制协议;之后,利用非负矩阵的性质,得到了当高阶多智能体系统拓扑结构是Markov切换时,系统能够实现均方一致性的充要条件;最后,通过数值仿真验证了在该控制协议下,系统能够达到均方一致性。

     

    Abstract: This paper focuses on the mean square consensus problem of multi-agent system which has the nonconvex input and Markov switching graphs. First, a non-convex constraint operator is introduced and a distributed control algorithm is designed according to the neighbor node information in the multi-agent system. Then, based on the property of non-negative matrix, the sufficient and necessary conditions are obtained for the mean square consensus problem of the multi-agent system with Markov switching graphs. Finally, numerical simulation results validate that the mean square consensus can be achieved when the control input is restricted in a nonconvex set.

     

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