A New Deterministic Identification Approach to Hammerstein Systems
The deterministic identification of Hammerstein systems is investigated in this paper. Based on the over-sampling technique, a new deterministic identification approach is presented, which blindly identifies the linear dynamic part followed by the estimation of the nonlinear function. The proposed method allows us to identify the Hammerstein system using an over-sampling rate smaller than the numerator polynomial's length of the linear dynamic part as required by other existing methods. In addition, it can obtain the true values of the system parameters in the noise-free case and an asymptotically consistent estimate in the presence of noise. The richness condition of the system input and the selection of the over-sampling rate are studied for the identifiability of the Hammerstein system. Simulation examples are given to show the performance of the proposed method.