Asynchronous Event-Triggered Distributed Predictive Control for Multiagent Systems With Parameterized Synchronization Constraints

This paper proposes an asynchronous event-triggered distributed predictive control method for the cooperation of multi-agent systems with parameterized synchronization constraints. A novel event-triggering condition related to the parameterized information received from neighboring agents is derived for each agent based on the input-to-state stability (ISS) condition. In such a framework, the distributed optimization problem is solved and the parameterized information is exchanged between neighboring agents, only when the triggering condition is satisfied. In addition, the dual mode control is adopted in this work and no information will be exchanged between the agent and its neighbors when the agent enters the invariant set, reducing the computation and communication load. Moreover, the recursive feasibility of the proposed algorithm is proved, and a sufficient condition is developed to ensure the stability of the closed-loop system. Finally, numerical simulation is given to verify the effectiveness of the proposed method.