MPC for LPV systems with bounded parameter variation using ellipsoidal set prediction

This paper proposes a new model predictive control (MPC) method for linear parameter varying (LPV) systems with bounded parameter variation subject to input constraints. We adopt closed-loop prediction and construct ellipsoidal sets to predict the future states with reasonable computer load. Then the information on the parameter variation bounds is exploited to improve the accuracy of the prediction. In addition, we give a new terminal condition to enlarge the stabilizable region. The feasibility of the MPC problem at the initial step ensures the stability of the closed-loop system. Finally, a simulation result illustrates the effectiveness of the method