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dc.contributor.authorBoeira, Emerson Christpt_BR
dc.contributor.authorEckhard, Diegopt_BR
dc.date.accessioned2021-03-20T04:35:23Zpt_BR
dc.date.issued2020pt_BR
dc.identifier.issn2352-7110pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/219173pt_BR
dc.description.abstractIn this paper, thepyvrft, a Python package for the data-driven control method known as Virtual Reference Feedback Tuning (VRFT), is presented. Virtual Reference Feedback Tuning is a control designtechnique that does not use a mathematical model from the process to be controlled. Instead, it uses input and output data from an experiment to compute the controller’s parameters, aiming to minimizean H2 Model Reference criterion. The package implements an unbiased estimate of the controller for MIMO (Multiple-Input Multiple-Output) processes using both least-squares and instrumental variabletechniques. The package also provides accessory functions to import data and to perform MIMO systems simulations, together with some examples.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofSoftwareX. Holanda: Elsevier, 2020. Vol. 11, (Jan/Jun. 2020), p. 1-6pt_BR
dc.rightsOpen Accessen
dc.subjectControl systemsen
dc.subjectSistemas de controlept_BR
dc.subjectData-drivenen
dc.subjectcontrolVRFTen
dc.subjectPythonen
dc.titleA Python package for the Virtual Reference Feedback Tuning, a direct data-driven control methodpt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001114352pt_BR
dc.type.originEstrangeiropt_BR


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