Frequency domain identification of Hammerstein models

This paper discusses Hammerstein model identification in frequency domain using the sampled input-output data. By exploring the fundamental frequency and harmonics generated by the unknown nonlinearity, we propose a frequency domain approach and show its convergence for both the linear and nonlinear subsystems in the presence of noise. No a priori knowledge of the structure of the nonlinearity is required and the linear part can be non-parametric.