Identification of multi-input multi-output Wiener-type nonlinear systems

A Wiener model consists of a linear dynamic system in followed by a static nonlinearity. The Wiener model are widely used to represent nonlinear systems, and the multiple-input multiple-output (MIMO) Wiener model appears frequently in many nonlinear systems. Therefore, it is proposed that the identification method of the MIMO Wiener model with two or more linear dynamic subsystems, whose outputs are transformed by multiple-input static nonlinearities. The linear dynamic subsystems are represented by the MIMO state-space representation. The MIMO static nonlinearities are expressed by the artificial neural networks which have the ability to learn the complex nonlinear relationships.