Finite-time convergence results in model predictive control

ANDERSON, ALEJANDRO; GONZÁLEZ, ALEJANDRO HERNÁN; FERRAMOSCA, ANTONIO; KOFMAN, ERNESTO

Conferencia; European Control Conference, ECC 2018; 2018

Asymptotic stability (convergence and - stability)of invariant sets under model predictive control (MPC)strategies have been extensively studied in the last decades.Lyapunov theory is in some sense the common denominatorof the different forms to achieve such results. However, themeaningful problem of the finite-time convergence (for a givenfixed control horizon) has not received much attention in theliterature (with some remarkable exceptions). In this work anovel set-based MPC that ensures finite-time convergence ina natural way is presented. The contractivity and non-emptyinterior conditions of the target set, the consideration of anappropriate input set and the continuity of the dynamic modelare the main hypothesis to be made. An upper bound for theconvergence time is also provided.