A multi-stage least squares method for identifying Hammerstein model nonlinear systems

This paper considers the parameter identification of nonlinear systems using Hammerstein model and in the presence of correlated output noise. Existing identification methods are all iterative. The proposed method, called MSLS, is a noniterative four-stage least square solution procedure. Therefore, it is computationally simpler. The estimates so obtained are statistically consistent. Two examples are included to demonstrate the utility of this method.