Abstract
This paper studies a procedure for identifying Hammerstein systems from input-output data, where the static nonlinearity is approximated by the trigonometric polynomials. Signals generated by the trigonometric function with white Gaussian inputs are analyzed in terms of the persistent excitation of linear time-invariant systems. Based on the analysis, an identification algorithm for Hammerstein systems is proposed via a subspace identification method. Numerical simulation results are also included to illustrate the effectiveness of the present algorithm.
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