Dynamic output feedback MPC for LPV systems via near-optimal solutions

This paper considers output feedback robust model predictive control (MPC) for the linear parameter varying (LPV) system with both polytopic uncertainty and bounded noise. We emphasize on the problem of near-optimal solution: a solution to the upper bound of the performance cost which is sufficiently close to the theoretically minimum one. The constraints on the input and output are guaranteed. The recursive feasibility is guaranteed, i.e., feasibility of the optimization problem at the initial time means its feasibility at all future time. The augmented state of the closed-loop system is guaranteed to converge to a neighborhood of the origin. An example for continuous stirred tank reactor (CSTR) is provided to illustrate the effectiveness.