Fractional order model identification: Computational optimization
dc.contributor.author | Guevara, E. | |
dc.contributor.author | Meneses, H. | |
dc.contributor.author | Arrieta, O. | |
dc.contributor.author | Vilanova, R. | |
dc.contributor.author | Visioli, A. | |
dc.contributor.author | Padula, Fabrizio | |
dc.date.accessioned | 2017-04-28T13:59:55Z | |
dc.date.available | 2017-04-28T13:59:55Z | |
dc.date.created | 2017-04-28T09:06:15Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Guevara, 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.uri | http://hdl.handle.net/20.500.11937/52789 | |
dc.identifier.doi | 10.1109/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.title | Fractional order model identification: Computational optimization | |
dc.type | Conference Paper | |
dcterms.source.volume | 2015-October | |
dcterms.source.title | IEEE International Conference on Emerging Technologies and Factory Automation, ETFA | |
dcterms.source.series | IEEE International Conference on Emerging Technologies and Factory Automation, ETFA | |
dcterms.source.isbn | 9781467379298 | |
curtin.department | Department of Mathematics and Statistics | |
curtin.accessStatus | Fulltext not available |
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