In the paper, an advanced Gauss pseudospectral method（AGPM） is proposed to estimate the parameters of the continuous-time（CT） Hammerstein model consisting of a CT linear block followed by a static nonlinearityThe ...
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In the paper, an advanced Gauss pseudospectral method（AGPM） is proposed to estimate the parameters of the continuous-time（CT） Hammerstein model consisting of a CT linear block followed by a static nonlinearityThe basic idea of AGPM is to transcribe the CT identification problem into a discrete nonlinear programming problem（NLP）, which can be solved with the well-developed sequential quadratic programming（SQP） algorithmThe nonlinear part of the Hammerstein system is approximated with the Gauss pseudospectral approximation methodThe linear part is written as a controllable canonical formAGPM can converge to the true values of the CT Hammerstein model with few interpolated Legendre-Gauss（LG） nodesLastly illustrative examples are proposed to verify the accuracy and efficiency of the method.
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