Closed-loop performance inference for controller selection in switching supervisory control

It is shown that an effective way for inferring the performance of a linear feedback loop made up by an uncertain plant and a given candidate controller is to resort to the concept of a virtual reference. This allows one to compute a performance-related distance measure, called divergence, between the loop made up by the unknown plant in feedback with the candidate controller and the nominal “tuned” loop related to the candidate controller. It is proved that divergence can be obtained by suitably filtering an output prediction error.