Self-Triggered Min–Max DMPC for Asynchronous Multiagent Systems With Communication Delays

This article studies the formation stabilization problem of asynchronous nonlinear multiagent systems (MAS) subject to parametric uncertainties, external disturbances, and bounded time-varying communication delays. A self-triggered min–max distributed model predictive control (DMPC) approach is proposed address this problem. At triggering instants, each agent solves a local optimization based on system states predicted neighbors, determines its next instant, broadcasts state trajectory neighbors. As result, load greatly alleviated while retaining robustness comparable performance compared periodic DMPC algorithms. In order handle delays, novel consistency constraint incorporated into restrict deviation between newest previously broadcasted states. Consequently, can utilize neighbors achieve cooperation in presence The algorithm’s recursive feasibility MAS’s closed-loop stability at instants are proven. Finally, numerical simulations conducted verify theoretical results.