Self-triggered consensus of multi-agent systems via model predictive control**This work was supported by the National Natural Science Foundation (No. 61273223), and the National Science Fund for Distinguished Young Scholars of China (No. 61425019).

Abstract

Abstract This paper proposes a self-triggered consensus algorithm for multi-agent systems by using model predictive control (MPC), where the self-triggering rule and the control algorithm are optimized jointly. The proposed self-triggered MPC consensus algorithm drives the system to reach consensus asymptotically under mild assumptions, if the communication topology is connected. Numerical examples are finally presented to verify the effectiveness and advantages of the self-triggered MPC consensus algorithm. By comparing with the conventional time-triggered and event-triggered consensus algorithms, the self-triggered MPC consensus algorithm is shown to achieve equivalent performance with significant reduction of the numbers of controller updates and information transmission.