Predictive functional control using state estimator-based internal model for ramp disturbance rejection

We propose a state estimator-based disturbance suppression technique for predictive functional control (PFC), which puts emphasis on attenuation of ramp disturbances. Augmenting the plant model with a disturbance model, we build a prediction-type estimator for the augmented model, which estimates ramp disturbances as well as the plant states. The state estimator enables us to predict the future output in the presence of ramp disturbances. We also analyse the structure of the proposed PFC system and controller poles and prove that the estimator-based PFC system actually has two integral actions. Finally, several numerical simulation tests are conducted to validate the effectiveness of the proposed method.