Design of Robust Model Predictive Controller Based on Event Trigger Strategies

This paper proposes an event-triggered robust model predictive control algorithm for the linear discrete system with addictive bounded disturbances. Firstly, the robust predictive control optimization problem is designed by utilizing the constraint tightening method. And then, based on the sequence of optimal control law, the feasible control law is derived for the subsequent instants. Besides, the event trigger condition is obtained by means of input-state stability theory. Finally, the simulation results illustrate the effectiveness of the proposed event-trigger conditions, whose can reduce the computation complexity.