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Nonlinear system identification using two-dimensional wavelet-based state-dependent parameter models. (English) Zbl 1292.93049

Summary: This article presents a nonlinear system identification approach that uses a two-dimensional (2-D) wavelet-based state-dependent parameter (SDP) model. In this method, differing from our previous approach, the SDP is a function with respect to two different state variables, which is realised by the use of a 2-D wavelet series expansion. Here, an optimised model structure selection is accomplished using a PRESS-based procedure in conjunction with orthogonal decomposition (OD) to avoid any ill-conditioning problems associated with the parameter estimation. Two simulation examples are provided to demonstrate the merits of the proposed approach.

MSC:

93B30 System identification
93C10 Nonlinear systems in control theory
65T60 Numerical methods for wavelets

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References:

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