Abstract:
In view of the color noise in actual industrial processes, a two-stage identification method of the Hammerstein nonlinear system corrupted by colored noise is proposed. The combined signals are used to separate the parameter identification of nonlinear and linear blocks for the Hammerstein system, which simplifies the identification process. In the first stage, based on the input and output data of separable signals, the parameters of the linear block are identified by adopting a correlation analysis algorithm, which reduces the impact of the unknown colored noise term on identification. In the second stage, based on the input and output data of random signals, the filtering technology is introduced into the least squares algorithm, and the filtering-based recursive extended least squares algorithm is derived, which improves the identification accuracy of nonlinear block and noise model parameters. The simulation results show that the proposed two-stage identification method improves the identification accuracy and effectively suppresses the interference of colored noise.