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Identification of continuous-time Hammerstein model based on modulation function method

The modulation method for identification of nonlinear continuous-time Hammerstein system is investigated. Through the digital modulating integral to the continuous-time Hammerstein model, an equivalent discrete identification model which is parameterized with continuous time model parameters is developed. Selecting Hermite and Hartley function as modulation function respectively, by shifting modulating window at time axes and changing frequency index of modulation function, the continuous-time Hammerstein model is modulated, and the model parameters are estimated by least-squares algorithm. Nonlinear parameters are gained by the average method. The simulation results with a second-order Hammerstein model show that the two methods can obtain model parameters with high accuracy and have good robustness to measurement noises.