Block-oriented identification of Hammerstein/Wiener-models using the RLS-algorithm

Issue title: Proceedings of the twelfth International Symposium on Interdisciplinary Electromagnetic, Mechanic and Biomedical Problems, ISEM Bad Gastein

Article type: Research Article

Authors: Kozek, Martin^{a; *} | Hametner, Christoph^a

Affiliations: [a] Vienna University of Technology, Guß hausstraß e 27–29, 1040 Vienna, Austria

Correspondence: [*] Corresponding author. Tel.: +43 0 1 58801 32812; Fax: +43 01 58801 32899; E-mail: [email protected]

Abstract: A new method for identifying Hammerstein/Wiener models is proposed, where the non-linear characteristic is modelled by a piecewise linear function and the linear dynamic part is represented by a linear transfer function. The parameters of the overall model are estimated by recursive least-squares (RLS), therefore enabling the algorithm to be implemented on-line. Using appropriate validity functions the edges of the piecewise linear characteristic may be smoothed out in order to achieve a better fit. An adaptive algorithm for optimal partitioning of the local linear models is also proposed on the basis of statistical analysis. Using the new approach an efficient and accurate model can be identified.

Keywords: Hammerstein and Wiener model, recursive identification, nonlinear parameter estimation, prediction intervals

DOI: 10.3233/JAE-2007-860

Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 25, no. 1-4, pp. 529-535, 2007