Low-Complexity Constrained Model Predictive Tracking Control: Parametric Programming Approach

In this paper, the constrained output tracking problem for linear systems with fast dynamics is addressed. It is assumed that the system is subject to input/state constraints and the reference signal is piecewise constant. Based upon the closed-loop control behavior, a simple controller is designed and it is shown that the proposed architecture guarantees the feasibility and asymptotic stability of the closed-loop system. Adapting and formulating the proposed controller as a model predictive control problem, an explicit optimal solution is obtained for the proposed controller. It is shown that the proposed approach can be effectively applied when the reference signal takes only some finite predefined values. However, non-predefined references are also handled and it is guaranteed to be feasible under some mild assumptions.