System identification of hammerstein models by using backward shift algorithm

Wen Mi and Tao Qian

Applied Mathematics and Computation, 2022, vol. 413, issue C

Abstract: In this paper, a new identification method for discrete-time Hammerstein systems is proposed. The method is a joint use of discrete Fourier transform, backward shift method, and the least squares method. The frequency responses are obtained with sampled input and output data in the time domain through discrete Fourier transform. It is followed by the backward shift algorithm that was originally developed for estimating poles of linear time-invariant systems. After poles of linear subsystem are estimated, coefficients of linear and nonlinear subsystems are respectively determined by using the least squares (LS) method. The robustness of the backward shift algorithm guarantees the effectiveness of the proposed algorithm. Simulation results show that the poles of linear subsystem are well located. Thus, it is practical to identify discrete Hammerstein systems.

Keywords: Nonlinear system; Backward shift; Hammerstein system; System identification; Transfer function (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300321007049
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:413:y:2022:i:c:s0096300321007049

DOI: 10.1016/j.amc.2021.126620

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().