Tracking periodic parametric references using model predictive control.

This paper presents a model predictive controller for tracking periodic parametric reference curves. The controller is formulated in a single layer so that the time‐parameterization of the reference curve, the trajectory planning, and the trajectory tracking tasks are solved in a single optimization problem which is computed at each sampling time. The auxiliary state and input trajectories are introduced into the optimization problem as decision variables, which become the planned trajectory to be effectively followed. By design, the closed‐loop system guarantees of recursive feasibility of the optimization problem while being able to handle arbitrary changes of reference during execution time. Such properties are discussed in detail, and new results on the asymptotic average performance are presented. Simulation results show the benefits of the proposed strategy. [ABSTRACT FROM AUTHOR]