[KMR12] Robust estimation of fractional models in the frequency domain using set membership methods

Revue Internationale avec comité de lecture : Journal Signal Processing, pp. ., 2012

Mots clés: Robustness; uncertainties; fractional; identification

Résumé: In this paper, the usual definition of \textit{Gr\"{u}nwald-Letnikov} fractional derivative is first extended to interval derivatives in order to deal with uncertainties in the differentiation orders. The \textit{Laplace} transform of interval derivatives is computed and its monotonicity studied in the frequency domain. Next, the main objectives of this paper are presented as the implementation of three methods for set membership parameters estimation of fractional differentiation models based on complex frequency data. The first one uses a rectangular inclusion function with rectangle sides corresponding to real and imaginary parts of the complex frequency response; the second one uses a polar inclusion function and the gain/phase representation; the third one uses a circular inclusion function with disk representation. Each inclusion function introduces pessimism differently. It is shown that all three approaches are complementary and that the results can be merged to obtain a smaller feasible solution set. The proposed methods can be applied to estimate parameters of certain/uncertain linear time variant/invariant systems.

Equipe: laetitia
Collaboration: SATIE , IMS


@article {
title="{Robust estimation of fractional models in the frequency domain using set membership methods}",
author="F. Khemane and R. Malti and T. Raïssi and X. Moreau",
journal="Signal Processing",