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

Yamina Ali Larnene, S. Ladaci, Aissa Belemeguenai
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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.
基于rls的分数阶H n1,n2系统奇异函数逼近辨识
本文研究了基于遗忘因子估计的递推最小二乘(RLS)对分数阶系统的建模和辨识。分数阶积分器采用奇异函数逼近法实现。研究了分数阶微分方程(FDE)的参数辨识问题,该问题是基于时间数据(H n1,n2)的非整数阶模型,采用线性模型对系统参数进行估计。数值模拟实例说明了所提出的识别方法的有效性,即使在参数值中存在持续偏差的情况下,也能保证系统和模型输出的收敛性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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