Kothari, Kajal and Mehta, Utkal V. and Prasad, Vineet and Vanualailai, Jito (2020) Identification scheme for fractional Hammerstein Models with the delayed Haar Wavelet. IEEE/CAA Journal of Automatica Sinica, 7 (3). pp. 882-891. ISSN 2329-9274
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Abstract
The parameter identification of a nonlinear Hammerstein-type process is likely to be complex and challenging due
to the existence of significant nonlinearity at the input side. In this paper, a new parameter identification strategy for a block-oriented Hammerstein process is proposed using the Haar wavelet operational matrix (HWOM). To determine all the parameters in the Hammerstein model, a special input excitation is utilized to separate the identification problem of the linear subsystem from the complete nonlinear process. During the first test period, a simple step response data is utilized to estimate the linear subsystem dynamics. Then, the overall system response to sinusoidal input is used to estimate nonlinearity in the process. A single-pole fractional order transfer function with time delay is used to model the linear subsystem. In order to reduce the mathematical complexity resulting from the fractional derivatives of signals, a HWOM based algebraic approach is developed. The proposed method is proven to be simple and robust in the presence of measurement noises. The numerical study illustrates the efficiency of the proposed modeling technique through four different nonlinear processes and results are compared with existing methods.
Item Type: | Journal Article |
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > Robotics and Automation |
Divisions: | Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics |
Depositing User: | Utkal Mehta |
Date Deposited: | 05 May 2020 00:58 |
Last Modified: | 05 May 2020 00:58 |
URI: | https://repository.usp.ac.fj/id/eprint/12058 |
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