Dynamic Output Feedback Robust Model Predictive Control
动态输出反馈鲁棒模型预测控制

This paper addresses the synthesis approach of dynamic output feedback robust model predictive control for systems with both polytopic uncertainty and bounded disturbance. The system is quasi-linear parameter varing, i.e., the time-varing parameters of the system are exactly known at the current time but unknown in the future. The notion of quadratic boundedness is utilized to characterize the stability properties of the augmented closed-loop system. The primary contribution of this paper is to propose a method for the auxiliary optimization to provide reliable bounds of true state for the main optimization problem at the next sampling time. A continuous stirred tank reactor control system is given to illustrate the effectiveness of the approach.