  This paper proposes a method for enlarging the region of attraction of Linear
Model Predictive Controllers (MPC) when tracking piecewise-constant references
in the presence of pointwise-in-time constraints. It consists of an add-on
unit, the Feasibility Governor (FG), that manipulates the reference command so
as to ensure that the optimal control problem that underlies the MPC feedback
law remains feasible. Offline polyhedral projection algorithms based on
multi-objective linear programming are employed to compute the set of feasible
states and reference commands. Online, the action of the FG is computed by
solving a convex quadratic program. The closed-loop system is shown to satisfy
constraints, be asymptotically stable, exhibit zero-offset tracking, and
display finite-time convergence of the reference.
