Using rational NARMAX models to recover static nonlinearities

This work presents an algebraic procedure for recovering information about static nonlinearities using NARMAX models identified directly from data. Such a procedure can be used to aid in choosing the structure of models when grey-box identification is performed. When black-box identification is attempted, it is shown that useful information about the system under investigation can be successfully recovered if the structure of the identified models are judiciously selected.