Numerical evaluation of a robust self-triggered MPC algorithm

We present numerical examples demonstrating the efficacy of a recently proposed self-triggered model predictive control scheme for disturbed linear discrete-time systems with hard constraints on the input and state. In order to reduce the amount of communication between the controller and the actuator, the control input is not re-computed at each point in time but only at certain sampling instances. These instances are determined in a self-triggered fashion in the sense that at every sampling instant the next sampling instant is computed as a function of the current system state. A compact set in the state space, whose size is a design parameter in the control scheme, is stabilized.