基于事件触发机制的多智能体网络平均一致性研究

文章研究了事件触发机制下具有固定和切换拓扑结构的多智能体网络的平均一致性问题。为了有效降低多智能体一致性控制协议的更新次数,文章提出了仅依赖于各智能体及其邻居节点信息的分布式事件触发机制。为了使多智能体网络渐近收敛至初始平均状态,文章提出了基于事件触发机制的多智能体平均一致性协议。然后,文章建立了事件触发机制下的闭环系统模型,并分别获得了固定和切换拓扑结构下多智能体网络平均一致收敛的充分条件。仿真表明,基于事件触发机制的平均一致性协议保证了多智能体网络的平均一致性,并且分布式事件触发机制有效降低了多智能体一致性协议更新次数。

Study on average consistency of multi-agent networks based on event-triggered mechanism

This paper studied average consistency of the multi-agent networks under fixed and switched topologies based on event-triggered mechanism. To effectively reduce the update rate of the consistency protocol, this paper firstly proposed a distributed event-triggered mechanism by using only the local information of each agent and its neighbors. To guarantee the average consistency of the multi-agent networks, this paper presented a consistency control protocol based on the event-triggered mechanism. Then, this paper established the closed-loop system model and obtained sufficient conditions for the average consistency of the multi-agent networks under fixed and switched topologies, respectively. Simulation shows that the distributed event-triggered mechanism effectively reduces the update rate of the consistency protocol, while the consistency protocol guarantees the average consistency of the multi-agent networks.