Identification of Hammerstein model based on dynamical separation technology

By using two different pseudo_random binary signals (PRBS) as the system input, the linear dynamical part of the Hammerstein system can be separated by simple algebraic operations. So the parameters of the linear part can be identified. Then the intermediate input between the nonlinear part and linear part is reconstructed by using observed output based on the estimated linear part. Finally, the nonlinear element is identified by using the test input signal and the reconstructed intermediate input. The effectiveness of the proposed algorithm is demonstrated by simulation examples.