RLS-based Identification of fractional order H n1,n2 system using the Singularity Function approximation
Keywords:System Identification, Recursive Estimation, Recursive Least squares Method, Fractional order Integrator, Singularity Function approximation
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.
How to Cite
Copyright (c) 2020 Yamina Ali Larnene, Samir LADACI, Aissa Belemeguenai
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.