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dc.contributor.authorLiu, Dayan
dc.contributor.authorLaleg-Kirati, Taous-Meriem
dc.contributor.authorGibaru, O.
dc.contributor.authorPerruquetti, Wilfrid
dc.date.accessioned2015-08-11T13:44:09Z
dc.date.available2015-08-11T13:44:09Z
dc.date.issued2013-06
dc.identifier.isbn9781479901777
dc.identifier.issn07431619
dc.identifier.doi10.1109/ACC.2013.6580077
dc.identifier.urihttp://hdl.handle.net/10754/565867
dc.description.abstractThe modulating functions method has been used for the identification of linear and nonlinear systems. In this paper, we generalize this method to the on-line identification of fractional order systems based on the Riemann-Liouville fractional derivatives. First, a new fractional integration by parts formula involving the fractional derivative of a modulating function is given. Then, we apply this formula to a fractional order system, for which the fractional derivatives of the input and the output can be transferred into the ones of the modulating functions. By choosing a set of modulating functions, a linear system of algebraic equations is obtained. Hence, the unknown parameters of a fractional order system can be estimated by solving a linear system. Using this method, we do not need any initial values which are usually unknown and not equal to zero. Also we do not need to estimate the fractional derivatives of noisy output. Moreover, it is shown that the proposed estimators are robust against high frequency sinusoidal noises and the ones due to a class of stochastic processes. Finally, the efficiency and the stability of the proposed method is confirmed by some numerical simulations.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.titleIdentification of fractional order systems using modulating functions method
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.identifier.journal2013 American Control Conference
dc.conference.date17-19 June 2013
dc.conference.nameAmerican Control Conference (ACC), 2013
dc.conference.locationWashington, DC
dc.identifier.arxividarXiv:1303.3877v1
kaust.personLiu, Dayan
kaust.personLaleg-Kirati, Taous-Meriem


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