Dynamic output feedback robust MPC for constrained quasi-LPV systems with both polyhedral and ellipsoidal bounds on estimation error

A new approach is proposed for the output feedback robust model predictive control (MPC) of a quasi-linear parameter varying (quasi-LPV) system with bounded noise. In the main optimization problem for finding the control law, the current true state is substituted with its bounds. The bounds are represented by either an ellipsoid or a polyhedron, the latter being used if and only if it is contained in the former. Both the ellipsoid and the polyhedron are refreshed at each sampling time. The recursive feasibility of the main optimization problem is guaranteed by a simple refreshment of the ellipsoid, the control performance can be improved by applying the polyhedron, and the closed-loop stability is achieved by the technique of quadratic boundedness. A numerical example is given to illustrate the effectiveness of the controller.