Dynamic output feedback MPC for LPV systems via iterative optimization

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 recursive feasibility: feasibility at the initial time means feasibility for all future time. We assume that the estimation error lies in an ellipsoid. This ellipsoid is refreshed at each sampling time by invoking the previous solution of the optimization problem. The recursive feasibility is indeed guaranteed for the proposed algorithm, and the closed-loop stability is proven. A numerical example is provided to illustrate the effectiveness.