Novel Event-Triggered Control for Time-Varying Leader–Follower MASs on Directed Graphs
针对有向图上的时变多智能体系统，提出一种完全分布式自适应事件触发方案，保证正的最小事件间隔时间，并避免连续通信。
The article studies the fully distributed leader–follower and adaptive event-triggered problem with the guarantee of positive minimum interevent times (MIET) for time-varying MAS on directed graphs. First, a novel fully distributed adaptive event-triggered scheme that includes a time-varying matrix gain and two dynamic gains is designed, and the requirement for global topology information can be removed. A novel dynamic triggering mechanism is then put forward for each follower, where an auxiliary dynamic parameter is introduced into the triggering function to guarantee the existence of positive MIETs. Meanwhile, it is worth mentioning that a direct measurement parameter using only the sampling information is leveraged to avoid the use of continuous communication with neighbors. Finally, simulation results are presented to confirm the performance of the proposed method.