Robust model predictive controller for tracking periodic signals

In this paper, we propose a novel robust model predictive control for tracking periodic signals formulation based on nominal predictions and constraint tightening. The proposed controller joins optimal periodic trajectory planning and a robust control for tracking in a single optimization problem and guarantees that the perturbed closed-loop system converges asymptotically to an optimal reachable periodic trajectory while satisfying the state and input constraints for all possible uncertainties. In addition, the closed-loop system maintains recursive feasibility even in the presence of sudden changes in the target reference. Two design procedures based on a robust positive invariant terminal region and on an equality terminal constraint are presented.