Event-triggered distributed predictive cooperation control for multi-agent systems subject to bounded disturbances

Abstract

This paper presents an event-triggered distributed predictive cooperation strategy for dynamically decoupled subsystems subject to bounded disturbances. Different from the traditional cooperative control using coupled constraints related to the agent’s state information, a synchronization parameter related to the agent’s control input information is introduced to design the parameterized synchronization constraint for the cooperation of multi-agent subsystems. An event-triggering condition involving the error between the system state and its optimal prediction is first designed for each agent, and the event-triggered distributed predictive control algorithm that is established on the triggering mechanism and the dual-mode approach is then designed. In such a framework, the distributed optimization problem is solved, and the parameterized information is exchanged between agents only when the triggering condition is satisfied, reducing the computation and communication load more efficiently. Moreover, the theoretical results guaranteeing the feasibility and closed-loop stability are developed. Finally, a formation control example for multiple mobile robots is given to verify the effectiveness of the proposed strategy.