Modelling and identification for highly nonlinear processes

M. Boutayeb, M. Darouach and P.M. Frank

Mathematics and Computers in Simulation (MATCOM), 1998, vol. 46, issue 5, 551-557

Abstract: This paper is devoted to modelling and identification of nonlinear dynamic systems. At first, we propose a new input–output representation to describe highly and/or large-scale nonlinear processes. The proposed mathematical model is nonlinear in parameters and is written as a product of several polynomials which may be selected in a sequential approach. In the second part of this note, a simple and recursive identification technique is detailed. It is shown that, under strong persistently exciting condition, global convergence of the parameters estimation algorithm is guaranteed. One of the main results of this contribution is that parameters to be estimated are considerably reduced in comparison with the general Kolmogorov–Gabor structure.

Date: 1998
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475498000846
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:matcom:v:46:y:1998:i:5:p:551-557

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().