Dynamic Event-Based Asymptotically Tracking Control for Multi-Agent Systems

This paper studies an adaptive dynamic event-triggered consensus asymptotical tracking control problem for nonlinear multi-agent systems. A distributed parameter adaptive law is designed to compensate for the parameter uncertainty involved in the acquisition of adjacency information by the agent. An event-triggered strategy with dynamic threshold is designed to reduce transmission load and controller updates. By reasonably constructing the dynamics of triggering threshold, the derived dynamic event-triggered control protocol can guarantee zero-error tracking and eliminate Zeno behavior. Simulation results verify the effectiveness of the developed scheme and the rationality of the theoretical results.