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dc.contributor.authorGuevara, E.
dc.contributor.authorMeneses, H.
dc.contributor.authorArrieta, O.
dc.contributor.authorVilanova, R.
dc.contributor.authorVisioli, A.
dc.contributor.authorPadula, Fabrizio
dc.date.accessioned2017-04-28T13:59:55Z
dc.date.available2017-04-28T13:59:55Z
dc.date.created2017-04-28T09:06:15Z
dc.date.issued2015
dc.identifier.citationGuevara, E. and Meneses, H. and Arrieta, O. and Vilanova, R. and Visioli, A. and Padula, F. 2015. Fractional order model identification: Computational optimization.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/52789
dc.identifier.doi10.1109/ETFA.2015.7301630
dc.description.abstract

© 2015 IEEE.This paper deals with the identification of fractional models with one fractional parameter. This kind of models are capable to represent an extensive range of dynamics, including overdamped and oscillatory behaviors. The identification algorithm consists in applying an optimization function, starting from an initial point, that allows the program to calculate a very representative model of the process. The results demonstrate the usefulness and robustness of the tool, which can be employed to identify integer and fractional systems in an easy way and this can be later exploited for further studies, for example the development of tuning rules.

dc.titleFractional order model identification: Computational optimization
dc.typeConference Paper
dcterms.source.volume2015-October
dcterms.source.titleIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
dcterms.source.seriesIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
dcterms.source.isbn9781467379298
curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusFulltext not available


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