Identification of Approximative Nonlinear State-space Models by Subspace Methods
نویسندگان
چکیده
A subspace identification algorithm for state-affine state-space systems which allows to approximate nonlinear systems arbitrarily well is derived. The proposed algorithm depends on an approximation step where a detailed approximation error analysis is provided. A special case is presented in which this approximation error vanishes. To tackle higher-order systems and ill-posed problems a regularized kernel method is proposed. The algorithm is evaluated by a simulation study. Copyright c ©2005 IFAC
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تاریخ انتشار 2005