A new fractional reduced-order model-inspired system identification method for dynamical systems

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dc.contributor.authorGude, Juan José
dc.contributor.authorTeodoro, Antonio di
dc.contributor.authorCamacho, Oscar
dc.contributor.authorGarcía Bringas, Pablo
dc.date.accessioned2024-11-15T10:09:38Z
dc.date.available2024-11-15T10:09:38Z
dc.date.issued2023
dc.date.updated2024-11-15T10:09:37Z
dc.description.abstractThis paper presents a new method for identifying dynamical systems to get fractional-reduced-order models based on the process reaction curve. This proposal uses information collected from the process. It can be applied to processes with an S-shaped step response that can be considered with fractional behavior and a fractional order range of α in [0.5, 1.0]. The proposed approach combines obtaining the fractional order of the model using asymptotic properties of the Mittag-Leffler function with time-based parameter estimation by considering two arbitrary points on the process reaction curve. The improvement in terms of accuracy of the identified FFOPDT model is obtained due to a more accurate estimation of α parameter. This method is characterized by its effectiveness and simplicity of implementation, which are key aspects when applying at an industrial level. Several examples are used to illustrate the effectiveness and simplicity of the proposed method compared to other well-established methods and other approaches based on the process reaction curve. Finally, it is also implemented on microprocessor-based hardware to demonstrate the applicability of the proposed method to identify the fractional model of a thermal process.en
dc.description.sponsorshipThe work of Juan J. Gude and Pablo García Bringas was supported by the Basque Government through the BEREZ-IA Elkartek Project under Grant KK-2023/00012. The work of Antonio Di Teodoro and Oscar Camacho was supported by Universidad San Francisco de Quito through the Poli-Grants Program under Grant 17965en
dc.identifier.citationGude, J. J., Di Teodoro, A., Camacho, O., & Bringas, P. G. (2023). A New Fractional Reduced-Order Model-Inspired System Identification Method for Dynamical Systems. IEEE Access, 11, 103214-103231. https://doi.org/10.1109/ACCESS.2023.3317230
dc.identifier.doi10.1109/ACCESS.2023.3317230
dc.identifier.issn2169-3536
dc.identifier.urihttp://hdl.handle.net/20.500.14454/1900
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subject.otherFractional first-order plus dead-time model
dc.subject.otherFractional-order systems
dc.subject.otherProcess identification
dc.titleA new fractional reduced-order model-inspired system identification method for dynamical systemsen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.endPage103231
oaire.citation.startPage103214
oaire.citation.titleIEEE Access
oaire.citation.volume11
oaire.licenseConditionhttps://creativecommons.org/licenses/by-nc-nd/4.0/
oaire.versionVoR
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