RLS-based Identification of fractional order H n1,n2 system using the Singularity Function approximation

Authors

  • Yamina Ali Larnene Electrical Engineering Department, University of 20th August 1955, Skikda, 21000 Algeria
  • Samir LADACI Dept. of EEA, National polytechnic School of Constantine, BP. 75 A, Ali Mendjli, Constantine 25100, Algeria
  • Aissa Belemeguenai Laboratoire de Traitement du Signal, SP-Lab, Mentouri University of Constantine, Algeria

DOI:

https://doi.org/10.51485/ajss.v5i4.117

Keywords:

System Identification, Recursive Estimation, Recursive Least squares Method, Fractional order Integrator, Singularity Function approximation

Abstract

This paper presents a study of fractional order systems modeling and identification by recursive least squares (RLS) with forgetting factor estimation technique. The fractional order integrators are implemented using the Singularity Function approximation method. Parametric Identification of fractional order differential equations (FDE) is investigated when estimating system parameters by a linear model with respect to parameters, as well as non-integer orders from temporal data (H n1,n2 )-type model. A numerical simulation example illustrates the effectiveness of the proposed identification approach to ensure the convergence of the plant and model outputs even if a bias is persistent in parameters’ values.

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Published

2020-12-15

How to Cite

[1]
Ali Larnene, Y., LADACI, S. and Belemeguenai, A. 2020. RLS-based Identification of fractional order H n1,n2 system using the Singularity Function approximation. Algerian Journal of Signals and Systems . 5, 4 (Dec. 2020), 197-202. DOI:https://doi.org/10.51485/ajss.v5i4.117.

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Articles