Identification of Fractional Model by Least-Squares Method and Instrumental Variable-Reference-Cited by-同舟云学术

Identification of Fractional Model by Least-Squares Method and Instrumental Variable

Published:2015-09-01 Issue:5 Volume:10 Page:
ISSN:1555-1415
Container-title:Journal of Computational and Nonlinear Dynamics
language:en
Short-container-title:

Author:

Khadhraoui Abir¹,Jelassi Khaled¹,Trigeassou Jean-Claude²,Melchior Pierre³

Affiliation:

1. Laboratoire des systèmes Electriques (LSE), Ecole Nationale d’Ingenieurs de Tunis, Le Belvedere 1002 Tunis, Tunisia e-mail:

2. Laboratoire Intégration du Matériau au Système (IMS-APS), Université Bordeaux 1, Bordeaus, France e-mail:

3. Laboratoire Intégration du Matériau au Système (IMS-APS), Université Bordeaux 1, Bordeaux, France e-mail:

Abstract

This paper deals with fractional model identification using least-squares (LS) method and instrumental variable (IV) in a noisy output context. A new identification method, which extends LS techniques to fractional system to identify not only the parameters but also the unknown order, is presented. In order to eliminate the bias of identification results, IV method is chosen which permits unbiased parameter estimation. Monte Carlo simulation analyses are used to demonstrate the validity and the performance of the proposed fractional order system identification method.

Publisher

ASME International

Subject

Applied Mathematics,Mechanical Engineering,Control and Systems Engineering,Applied Mathematics,Mechanical Engineering,Control and Systems Engineering

Link

http://asmedigitalcollection.asme.org/computationalnonlinear/article-pdf/doi/10.1115/1.4029904/6105925/cnd_010_05_050801.pdf

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3. Refined Instrumental Variable Methods of Recursive Time-Series Analysis Part III. Extensions;Int. J. Control,1980

4. Unbiased Recursive Identification Using Model Reference Adaptive Techniques;IEEE Trans. Autom. Control,1976

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