A synthesis approach for output feedback robust constrained model predictive control

This paper addresses the synthesis approach for output feedback robust model predictive control for systems with polytopic description, bounded state disturbance and measurement noise. Off-line, it calculates a sequence of output feedback laws based on the state estimators, by solving linear matrix inequality (LMI) optimization problems. On-line, at each sampling time, it chooses an appropriate output feedback law from this sequence. The primary contribution is to present a rigorous method to guarantee satisfaction of input/state constraints. A numerical example is given to illustrate the effectiveness of the controller.