Learning-enhanced generalized predictive control for systems with periodic disturbances

Abstract

In this paper, a generalized predictive control (GPC) algorithm is developed for linear discrete systems that is capable of effectively addressing the presence of disturbances that are periodic in nature. First, a GPC algorithm is derived based on the assumption of the presence of a periodic disturbance. Next, a feedforward disturbance learning scheme is proposed for estimating the periodic disturbance. Finally, two sufficient conditions are provided to guarantee the convergence of the disturbance learning law.