New comparisons and overview of interpolation methods for the uncertain case

A recent paper [17] proposed a new interpolation method for predictive control which formulated a control law that systematically combines two existing approaches. The key benefit is an algorithm that requires only a quadratic programming optimisation while giving good feasibility and potential for robustness. This paper first shows how to extend this algorithm to the uncertain case. In addition, a detailed overview of many existing interpolations methods precedes a full comparison among them. Furthermore, the numeric comparisons include higher order examples whereas earlier papers have tended to focus on lower order models.