Identification of Hammerstein/Wiener nonlinear systems with extended Kalman filters

Abstract

The extended Kalman filter (EKF) is considered for parameter identification of Hammerstein/Wiener nonlinear systems. The EKFs for parameter identification of both combined Hammerstein/Wiener as well as for pure Hammerstein and pure Wiener models are formulated. In order to enable efficient estimation of unknown nonlinearities linear parametrizations with linear static mappings and basis function expansions are proposed and the EKFs for these cases are established. The efficiency and performance of the approach is demonstrated by means of a computer simulation of a Hammerstein and a Wiener model.