Asymptotic identification of discrete event systems

This work deals with the analysis of the online identifiability of the discrete event systems (DES) using interpreted Petri nets. A theoretical framework characterizing identifiable systems when only the input and output system´s signals are available is first addressed. Based on this framework, an algorithm that progressively builds an IPN model of the system is then presented. As a possible application of the problem herein addressed, the online identification problem is adapted to address the problem of DES model validation