Event-triggered robust model predictive control with stochastic event verification

Abstract

This paper is concerned with event-triggered robust model predictive control (MPC) for linear discrete-time systems with bounded disturbances. Based on the ergodicity of a purposely designed Markov chain, a stochastic triggering scheme involving a prescribed triggering function, an updating law for the transition probabilities of the Markov chain, and a checking function is proposed to achieve aperiodic and non-persistent event verification and enlarge the inter-execution time. Both tube-based MPC and linear matrix inequality-based (LMI-based) MPC are considered, and they show complementary merits with such a stochastic triggering scheme. Under mild conditions, recursive feasibility and closed-loop robust stability of both approaches are guaranteed theoretically. Simulation results are provided to show the effectiveness and merits of the proposed approaches.