Identification of nonlinear LFR systems with two nonlinearities

When identifying a system (e.g. mechanical, electrical or chemical) based on inand output measurements and without physical knowledge, an engineer faces many choices. First of all, there exist standard linear models, but when those do not sufficiently well describe the data, nonlinear models should be considered. There are many kinds of nonlinear models and it is often hard to choose among them. Most likely, the engineer will prefer a simple model (containing as few parameters as possible), which is yet flexible enough to describe the data. This paper presents an identification method that results in a block-structured model. The block-structure consists of a linear dynamic part and two (single-input single-output) static nonlinearities. Because of this structure, the model complexity remains reasonable, whereas the structure is flexible enough to describe any system with two static nonlinearities (including Hammerstein-Wiener, Wiener-Hammerstein, nonlinear feedback etc.).