Event-triggered model predictive control for disturbed linear systems under two-channel transmissions

This article studies an event-triggered model predictive control problem for constrained continuous-time linear systems subject to bounded disturbances. Two different event-triggered strategies are constructed in the sensor and the controller nodes for reducing the communication and computational loads, respectively. The continuous predicted control trajectory generated by the controller is applied to the plant under a sample-and-hold implementation. By constructing a feasible control sequence, the sufficient conditions are derived to guarantee the feasibility and stability of the closed-loop system. Furthermore, the case of multiple samples within an event-triggered control update interval is considered. It is shown that a larger number of samples will improve the triggering performance while increasing the amount of transmission information. Finally, a simulation example is provided to show the feasibility and the effectiveness of the proposed strategy.