Min-max feedback model predictive control with state estimation

This paper proposes a state estimation scheme for output feedback min-max model predictive control (MPC). A set-membership state estimator bounds the current states of the physical system. A standard state estimator provides state feedback for the state feedback control law in MPC optimization over the prediction horizon. The paper presents a recursive method for the set-membership state estimation and conditions for bounded stability of the closed-loop system. The approach is illustrated with an example.

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