论文部分内容阅读
The parameter identification of a nonlinear Ham-merstein-type process is likely to be complex and challenging due to the existence of significant nonlinearity at the input side.In this paper,a new parameter identification strategy for a block-ori-ented Hammerstein process is proposed using the Haar wavelet operational matrix(HWOM).To determine all the parameters in the Hammerstein model,a special input excitation is utilized to separate the identification problem of the linear subsystem from the complete nonlinear process.During the first test period,a simple step response data is utilized to estimate the linear subsys-tem dynamics.Then,the overall system response to sinusoidal in-put is used to estimate nonlinearity in the process.A single-pole fractional order transfer function with time delay is used to mod-el the linear subsystem.In order to reduce the mathematical com-plexity resulting from the fractional derivatives of signals,a HWOM based algebraic approach is developed.The proposed method is proven to be simple and robust in the presence of measurement noises.The numerical study illustrates the effi-ciency of the proposed modeling technique through four different nonlinear processes and results are compared with existing meth-ods.