Using wavelet multi-resolution nature to accelerate the identification of fractional order system |
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Affiliation: | 1.B-DAT, School of Information and Control, Nanjing University of Information Science & Technology, Nanjing 210044, China;2.Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, China |
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Abstract: | Because of the fractional order derivatives, the identification of the fractional order system(FOS) is more complex than that of an integral order system(IOS). In order to avoid high time consumption in the system identification, the leastsquares method is used to find other parameters by fixing the fractional derivative order. Hereafter, the optimal parameters of a system will be found by varying the derivative order in an interval. In addition, the operational matrix of the fractional order integration combined with the multi-resolution nature of a wavelet is used to accelerate the FOS identification, which is achieved by discarding wavelet coefficients of high-frequency components of input and output signals. In the end, the identifications of some known fractional order systems and an elastic torsion system are used to verify the proposed method. |
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Keywords: | fractional order system system identification operational matrix wavelet multi-resolution analysis |
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