Self-Triggered Model Predictive Control With Sample-and-Hold Fashion for Constrained Continuous-Time Linear Systems

Abstract A novel self-triggered model predictive control (STMPC) strategy for linear constrained systems with additive disturbance is presented in this paper. The actuator adopts the control input from the controller by sample-and-hold fashion. At the same time, the triggering threshold is designed to ensure the feasibility of the algorithms and the stability of the closed-loop system. Furthermore, two different ways to generate the event triggered input signal, namely, using single sample and multiple samples, are proposed and it is shown that better triggering performance can be obtained as the number of samples increases. In the last, the effectiveness and applicability of the proposed methods are verified by simulation.