An impulsive framework for consensus learning via event-triggered scheme

This paper proposes a novel impulsive framework to study the leader-following consensus in multi-agent systems with an event-triggered mechanism. To be specific, we design an impulsive model to reflect information exchange under event-triggered strategy. Hence the stabilization of this impulsive model can sufficiently guarantee that all followers in original multiagent systems can track the leader finally. The key idea is that impulses happen only when it is needed rather than elapse of time in conventional impulsive schemes. Moreover, we also apply an impulsive model to investigate the case where followers' states with the external disturbance is available instead of their exact states. Thus leader-following consensus can be achieved under well-designed event-triggered protocols.