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Continuous-time system identification with fractional models from noisy input/output measurements using third-order cumulants

Abstract : This paper considers the problem of identifying continuous-time fractional systems from noisy input/output measurements. Firstly, the differentiation orders are fixed and the differential equation coefficients are estimated using and estimator based on Higher-Order Statistics: fractional fourth-order cumulants based least squares. Then, the commensurate order is estimated along with the differential equation coefficients. Under some assumptions on the distributional properties of additive noises and the noise-free input signals, the developed estimator gives consistent results. Hence, the noise-free input signal is assumed to be non Gaussian, whereas the additive noises are assumed to be Gaussian. The performances of the developed algorithm are assessed through a numerical example.
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https://hal.archives-ouvertes.fr/hal-01709782
Contributor : Rachid Malti <>
Submitted on : Thursday, February 15, 2018 - 11:44:15 AM
Last modification on : Tuesday, March 31, 2020 - 2:12:19 PM

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Manel Chetoui, Rachid Malti, Mohamed Aoun, Magalie Thomassin, Mohamed Naceur Abdelkrim, et al.. Continuous-time system identification with fractional models from noisy input/output measurements using third-order cumulants. Nabil Derbel and Faouzi Derbel and Olfa Kanoun. Advances in Systems, Signals and Devices, 5, De Gruyter, pp.125-144, 2017, Systems, Automation, and Control, 9783110470468. ⟨10.1515/9783110470468-008⟩. ⟨hal-01709782⟩

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