基于周期事件触发的多智能体系统平均一致性

Average consistency of multi-agent system based on periodic event-triggered mechanism

本文研究了一阶多智能体系统在固定无向连通拓扑下的平均一致性问题。为了减少多智能体系统的资源消耗,避免Zeno现象,本文提出了在离散时间下周期地对状态值进行采样的周期事件触发机制;同时为了减少智能体的控制输入更新次数,提出了一种新的事件触发条件。利用代数图论和李雅普诺夫理论,获得了多智能体系统达到平均一致性的充分条件。最后,仿真实例验证了该触发机制的有效性。

The average consistency problem of a first-order multi-agent system under a fixed undirected connected topology is studied.In order to reduce the resource consumption of the multi-agent system and avoid the Zeno phenomenon,a periodic event triggering mechanism that periodically samples the state value in discrete time is proposed;at the same time,in order to reduce the number of updates to the control input of the multi-agent system,a new The event trigger condition.Using algebraic graph theory and Lyapunov theory,a sufficient condition for multi-agent systems to achieve average consistency is obtained.Finally,a simulation example verifies the effectiveness of the trigger mechanism.