Robust stability constrained model predictive control

This paper proposes a robust model predictive control (MPC) scheme to asymptotically stabilize an uncertain linear plant with polytopic model uncertainty description. Quadratic robust stability constraints are explicitly imposed as contractive constraints on the predicted state at each sampling time. The feasibility of these constraints can be detected either off-line or at the first step of on-line optimization. The feasibility is independent of the selection of the optimization objective function and its parameters. Therefore, the objective function can be formulated to satisfy other criterion such as the performance requirements. The simulation study shows the effectiveness and features of the proposed method.