Event-Triggered Active MPC for Nonlinear Multiagent Systems with Packet Losses

In this paper, event-triggered active model predictive control is investigated for a nonlinear multiagent system (MAS) with packet losses. By designing event-triggered mechanisms which reduce sensing cost, event-triggered conditions are detected at certain sampling instants. The prediction horizons of all agents are selected actively through the event-triggered mechanisms. Selecting a maximal predictive horizon, a common predictive horizon of the nonlinear MAS is obtained to ensure synchronous updating. The Bernoulli distributions are applied to describe the packet losses which are dealt with by model predictive control. Finally, the effectiveness of the proposed algorithm design is verified by a numerical simulation.