Orthogonal least square based non-linear system identification of a refrigeration system

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dc.contributor.authorDANTA, T. S. S.
dc.contributor.authorIvan Carlos Franco
dc.contributor.authorSILVA, F. V.
dc.contributor.authorOrcidhttps://orcid.org/0000-0003-4811-8158
dc.date.accessioned2022-01-12T21:59:18Z
dc.date.available2022-01-12T21:59:18Z
dc.date.issued2016-08-05
dc.description.abstractChillers are important part of several processes in the Chemical, Petro-Chemical, Pharmaceutical, Beverage and Food industries. Controlling these processes at an advantageous operating point is essential to achieve high productivity and profitability. Ultimately control system design and controller tuning depend on accurate process knowledge in the form of dynamic mathematical models. But attempts to develop analytical models often stumble upon problems such as unknown physical parameters. In this work, system identification, an established modeling technique, is used to build a non-linear dynamic model of a chiller from raw Input-Output data. Two dynamic nonlinear stochastic models where obtained, one more compact and the other with more terms but more precise, showing good simulation results and average prediction errors between 3.65%-5.23%.
dc.description.firstpage152
dc.description.lastpage159
dc.identifier.citationDANTA, T. S. S.; FRANCO, I. C.; SILVA, F. V. Orthogonal least square based non-linear system identification of a refrigeration system. Proceedings of the 6th IASTED International Conference on Modelling, Simulation and Identification, MSI 2016, P. 152-159, 2016.
dc.identifier.doi10.2316/P.2016.840-024
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/3921
dc.relation.ispartofProceedings of the 6th IASTED International Conference on Modelling, Simulation and Identification, MSI 2016
dc.rightsAcesso Restrito
dc.subject.otherlanguageSystem identification Refrigeration Non-linear Dynamic Modeling
dc.titleOrthogonal least square based non-linear system identification of a refrigeration system
dc.typeArtigo de evento
fei.scopus.citations0
fei.scopus.eid2-s2.0-85015675254
fei.scopus.subjectAverage prediction error
fei.scopus.subjectDynamic mathematical model
fei.scopus.subjectDynamic non-linear
fei.scopus.subjectNon-linear dynamics
fei.scopus.subjectNon-linear system identification
fei.scopus.subjectOrthogonal least squares
fei.scopus.subjectPhysical parameters
fei.scopus.subjectRefrigeration system
fei.scopus.updated2024-07-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85015675254&origin=inward
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