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Communication Dans Un Congrès Année : 2012

Higher-Order Statistics-based methods for order and parameter estimation of continuous-time errors-in-variables fractional models

Résumé

This paper considers the problem of dynamic Errors-In-Variables identification by fractional model. First, differentiation orders are fixed and the differential equation coefficients are estimated using two estimators based on Higher-Order Statistics (third-order cumulants). Then, all differentiation orders are set as integer multiples of a commensurate order. The fractional third-order based least squares algorithm (ftocls) and the fractional third-order based iterative least squares algorithm (ftocils) are extended to estimate the commensurate order with a nonlinear optimization algorithm. A simulation example is used to demonstrate the performance of the proposed methods.
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Dates et versions

hal-00762988 , version 1 (10-12-2012)

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  • HAL Id : hal-00762988 , version 1

Citer

Manel Chetoui, Magalie Thomassin, Rachid Malti, Mohamed Aoun, Slaheddine Najar, et al.. Higher-Order Statistics-based methods for order and parameter estimation of continuous-time errors-in-variables fractional models. 5th symposium on Fractional Differentiation and its Applications, FDA2012, May 2012, Nanjing, China. pp.CDROM. ⟨hal-00762988⟩
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