Nonlinear System Identification in a Noisy Environment Using Wavelet Based SDP Models
نویسندگان
چکیده
Abstract: This paper presents an approach to the identification of nonlinear system in noisy environment using a wavelet based State Dependent Parameter (SDP) model to chacterize the system’s nonlinear dynamics. The obtained model is in the form of a set of linear regressive output/input terms (state) multiplied by the respective SDPs, which are compactly parameterized by wavelet basis functions. In this approach, a modified Instrumental Variable (IV) algorithm is used to solve to the inconsistency problem of linear least squares parameter’s estimation in the presence of noise. A simulation example is provided to illustrate the proposed approach.
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تاریخ انتشار 2008