Closed-Loop Model Validation Using Coprime Factor Uncertainty Models

Abstract

Model (in)validation techniques are used to bridge the gap between models used in robust control synthesis and uncertainty models obtained from identification experiments. In most applications the aim is to design a robust controller and therefore it is valuable to validate or invalidate an uncertainty model in view of this application by considering a closed-loop model validation technique. In this paper a model validation approach is presented that generalizes the (in) validation of possibly unstable models on the basis of closed-loop experiments with a stabilizing, but possibly unstable, controller. The approach is presented in a robust control framework with an uncertainty model described with coprime factor perturbations. It is shown that this approach yields an affine expression of the uncertainty model in all possible transfer functions that can be measured via a closed-loop experiments, which facilitates the optimization involved with a model invalidation.