Adaptive LAMDA applied to identify and regulate a process with variable dead time

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dc.contributor.authorMorales L.
dc.contributor.authorPozo D.
dc.contributor.authorAguilar J.
dc.contributor.authorRosales A.
dc.contributor.departmentUniversidad EAFIT. Departamento de Ingeniería de Sistemasspa
dc.contributor.researchgroupI+D+I en Tecnologías de la Información y las Comunicacionesspa
dc.date.accessioned2021-04-12T21:07:09Z
dc.date.available2021-04-12T21:07:09Z
dc.date.issued2020-01-01
dc.description.abstractIn this paper, an adaptive intelligent controller based on the fuzzy algorithm called LAMDA (Learning Algorithm for Multivariable Data Analysis) is presented in order to identify and regulate a process with variable dead time. The original algorithm has been used for supervised and unsupervised learning, whose main field of application is the identification of functional states of the systems. In this work a modification of LAMDA has been implemented which is capable of online learning using hybrid techniques. The proposal consists of two stages: training stage to learn about the unknown plant in order to establish initial parameters to the controller, and a second phase, called application, in which the control strategy is updated using online learning. The proposed method is tested in the control objective of regulation of a process with variable dead time, to analyze the viability of its utilization in these types of systems in which their dynamics are variable and unknown. © 2020 IEEE.eng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=12192
dc.identifier.doi10.1109/FUZZ48607.2020.9177687
dc.identifier.issn10987584
dc.identifier.otherSCOPUS;2-s2.0-85090497318
dc.identifier.urihttp://hdl.handle.net/10784/28780
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85090497318&doi=10.1109%2fFUZZ48607.2020.9177687&partnerID=40&md5=5313014a87530d06d8ab1b05d6f202b9
dc.rightsInstitute of Electrical and Electronics Engineers Inc.
dc.sourceIEEE International Conference on Fuzzy Systems
dc.subject.keywordControllerseng
dc.subject.keywordE-learningeng
dc.subject.keywordFuzzyeng
dc.subject.keywordsetseng
dc.subject.keywordMultivariableeng
dc.subject.keywordsystemseng
dc.subject.keywordControleng
dc.subject.keywordobjectiveseng
dc.subject.keywordControleng
dc.subject.keywordstrategieseng
dc.subject.keywordHybrideng
dc.subject.keywordtechniqueseng
dc.subject.keywordIntelligenteng
dc.subject.keywordcontrollerseng
dc.subject.keywordLearningeng
dc.subject.keywordalgorithmeng
dc.subject.keywordforeng
dc.subject.keywordmultivariableeng
dc.subject.keyworddataeng
dc.subject.keywordanalysiseng
dc.subject.keywordOriginaleng
dc.subject.keywordalgorithmseng
dc.subject.keywordSupervisedeng
dc.subject.keywordandeng
dc.subject.keywordunsupervisedeng
dc.subject.keywordlearningeng
dc.subject.keywordVariableeng
dc.subject.keyworddeadeng
dc.subject.keywordtimeeng
dc.subject.keywordLearningeng
dc.subject.keywordalgorithmseng
dc.titleAdaptive LAMDA applied to identify and regulate a process with variable dead timeeng
dc.typeinfo:eu-repo/semantics/conferencePapereng
dc.typeconferencePapereng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
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