Joint estimation of the fractional differentiation orders and the unknown input for linear fractional non-commensurate system

Zehor Belkhatir, Taous-Meriem Laleg-Kirati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper deals with the joint estimation of the unknown input and the fractional differentiation orders of a linear fractional order system. A two-stage algorithm combining the modulating functions with a first-order Newton method is applied to solve this estimation problem. First, the modulating functions approach is used to estimate the unknown input for a given fractional differentiation orders. Then, the method is combined with a first-order Newton technique to identify the fractional orders jointly with the input. To show the efficiency of the proposed method, numerical examples illustrating the estimation of the neural activity, considered as input of a fractional model of the neurovascular coupling, along with the fractional differentiation orders are presented in both noise-free and noisy cases.
Original languageEnglish (US)
Title of host publication2015 IEEE Conference on Control Applications (CCA)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages388-393
Number of pages6
ISBN (Print)9781479977871
DOIs
StatePublished - Nov 5 2015

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