Robust identification of linear parameter varying systems

We study the robust identification problem for a special class of linear parameter varying systems, when it is assumed that there is only one varying parameter and all the states of the system under identification can be measured. We consider a worst-case approach, i.e., we look for a set of models in a class of systems defined a priori, which could have generated the available bounded-error data. The proposed method performs the identification recursively and in real time