Characterization of min-max MPC with bounded uncertainties and a quadratic criterion

As shown by the authors in their previous paper (2001), min-max model predictive control (MPC) with a quadratic criterion, bounded additive uncertainties and a linear prediction model, results in a piecewise linear controller, which can be described in explicit form. This paper presents a characterization of these controllers. Techniques for composing a list of candidates for the optimal solution and for testing their optimality are presented. The results are illustrated by means of examples.