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MODEL PREDICTIVE CONTROL WITH STATE ESTIMATOR FOR POLYTOPIC UNCERTAIN SYSTEM WITH ACTUATOR SATURATION

A novel model predictive control with state estimator is proposed for polytopic uncertain systems with actuator saturation in which the actuator saturation is described as a convex hull composition. At each sampling time, a state feedback control law is obtained such that the upper bound of the quadratic objective function is minimized. The intrinsic relationship between infinite horizon control problem and finite horizon control problem is derived. And the robust stability of proposed model predictive control is proved. Furthermore, considering the state is partial measurable, a state estimator is designed. And the robust stability criterion for closed-loop system combined controller and estimator is given. Finally, the numerical example demonstrates the effectiveness of the proposed model predictive control with state estimator.