Data Informativity for the Closed-Loop Identification of MISO ARX Systems. Issue 7 (2021) - Colin, Kévin; Bako, Laurent; Bombois, Xavier
Abstract: In the Prediction Error identification framework, it is crucial that the collected data are informative with respect to the chosen model structure to get a consistent estimate. In this work, we focus on the data informativity property for the identification of multi-inputs single-output ARX systems in closed-loop and we derive a necessary and sufficient condition to verify if a given multisine external excitation combined with the feedback introduced by the controller yields informative data with respect to the chosen model structure.