Recursive Feasibility and Stability of MPC with Time-Varying and Uncertain State Constraints

Abstract

This paper defines conditions for ensuring recursive feasibility and asymptotic stability of Model Predictive Control (MPC) for nonlinear systems subject to time-varying state constraints. Such constraints may arise from interaction with a dynamically evolving environment. For the cases that the change of the constraints is known to be bounded, or that a prediction model for the change of the constraints is available, we provide conditions under which recursive feasibility and asymptotic stability is guaranteed.