Identification of Wiener systems with steady-state non-linearities

Wiener type of systems consist of linear dynamics followed by a static non-linear part. In this paper, a restricted class of Wiener systems is considered where the static mapping represents a steady-state model for the process. A Wiener model structure is suggested for the identification of MISO steady-state static systems with linear unit steady-state gain OE dynamics for each input. The derivatives required by gradient-based parameter estimation techniques are given. Example with MISO data from a pump-valve pilot plant, using sigmoid neural networks to model the non-linearities, illustrates the behaviour of the approach.