System identification consists in the study of techniques allowing to estimate parameters of models for dynamical systems starting from input and output data experimentally collected. This problem is strongly motivated in the context of control system design and by a number of other practical situations such as the determination of useful system parameters in system’s testing or analysis. Among all the system identification algorithms, it is possible to recognize two big classes: • Black-box identification: allows to estimate parameters of a model whose structure is selected according to some general a-priori information which does not require any knowledge of the physics of the systems.