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Published in IET Signal Processing IET Signal Process., pp. 1–12 Received on 2nd January 2013 doi: 10.1049/iet-spr.2013.0002 Revised on 14th May 2013
Accepted on 20th September 2013 doi: 10.1049/iet-spr.2013.0002
ISSN 1751-9675
Linear Fractional Order System Identification using Adjustable Fractional Order Differentiator
Daoud Idiou1,2, Abdelfatah Charef1, Abdelbaki Djouambi1,3
1Laboratoire de Traitement du Signal Département d’Electronique Université Mentouri de Constantine Route Ain El-bey - Constantine 25011 – Algeria
2Unité de recherche appliquée en Sidérurgie et Métallurgie URASM/CSC BP 196 - Annaba 23000 - Algeria
3Département des Sciences et Technologie Université Larbi Ben M’Hidi Oum-El-Bouaghi 04000 – Algeria
Abstract
In previous decades, it has been observed that many physical systems are well characterised by fractional order models. Hence, their identification is attracting more and more interest of the scientific community. However, they pose a more difficult identification problem, which requires not only the estimation of model coefficients but also the determination of fractional orders with the tedious calculation of fractional order derivatives. This study focuses on an identification scheme, in the time domain, of dynamic systems described by linear fractional order differential equations. The proposed identification method is based on the recursive least squares algorithm applied to an ARX structure derived from the linear fractional order differential equation using adjustable fractional order differentiators. The basic ideas and the derived formulations of the identification scheme are presented. Illustrative examples are presented to validate the proposed linear fractional order system identification approach.
