A non linear black-box structure for a dynamical system is a model structure that is prepared to describe virtually any non linear dynamics. There has been considerable recent interest in this area with structures based on neural networks, radial basis networks, wavelet networks, hinging hyperplanes, as well as wavelet transform based methods and models based on fuzzy sets and fuzzy rules. This paper describes all these approaches in a common framework, from a user's perspective. It focuses on what are the common features in the different approaches, the choices that have to be made and what considerations are relevant for a successful system identification application of these techniques.

Keywords : non linear system, model structures, parameter estimation, wavelets, neural networks, fuzzy modeling.