  Lipschitz constants for linear MPC are useful for certifying inherent
robustness against unmodeled disturbances or robustness for neural
network-based approximations of the control law. In both cases, knowing the
minimum Lipschitz constant leads to less conservative certifications. Computing
this minimum Lipschitz constant is trivial given the explicit MPC. However, the
computation of the explicit MPC may be intractable for complex systems. The
paper discusses a method for efficiently computing the minimum Lipschitz
constant without using the explicit control law. The proposed method simplifies
a recently presented mixed-integer linear program (MILP) that computes the
minimum Lipschitz constant. The simplification is obtained by exploiting
saturation and symmetries of the control law and irrelevant constraints of the
optimal control problem.
