Identification of Nonlinear Dynamic System with SVR

Abstract
An identification method for nonlinear dynamic system based on support vector regression(SVR) was discussed and the corresponding deduction processes and learning algorithm were also addressed. Firstly, the Hammerstein model was adopted to describe the nonlinear dynamic system, which was expressed by a nonlinear static subunit followed by a linear dynamic subunit. Then, through the function expansion, the intermediate linear model was established, by which the nonlinear transfer function of Hammerstein model could be convert to the same form as linear one. Thirdly, by SVR algorithm, the coefficients of the intermediate model were gotten. Finally, the relations of the coefficients of intermediate model and that of Hammerstein model were derived, through which the nonlinear static subunit and linear dynamic subunit were identified simultaneously. Simulations results show the identification method for nonlinear dynamic system is effective.

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