Repetitive model based predictive controller to reject periodic disturbances

This paper presents a repetitive model predictive controller to reject periodic disturbances in industrial processes. The proposed technique uses a state-space model with embedded repetitive action to integrate most important characteristics from both repetitive and predictive controllers. Thus, the obtained control strategy combines best characteristics from both repetitive and model predictive control. A simulation case study is presented to discuss several aspects related to disturbance rejection performance, parameters tuning and constraints effects, and to compare this new control strategy with traditional repetitive and model predictive controllers