نمایش مختصر رکورد

dc.contributor.authorJazayeri Rad, Hooshangen_US
dc.date.accessioned1399-07-08T20:14:15Zfa_IR
dc.date.accessioned2020-09-29T20:14:15Z
dc.date.available1399-07-08T20:14:15Zfa_IR
dc.date.available2020-09-29T20:14:15Z
dc.date.issued2004-12-01en_US
dc.date.issued1383-09-11fa_IR
dc.date.submitted2003-05-03en_US
dc.date.submitted1382-02-13fa_IR
dc.identifier.citationJazayeri Rad, Hooshang. (2004). Rejection of the Feed-Flow Disturbances in a Multi-Component Distillation Column Using a Multiple Neural Network Model-Predictive Controller. Iranian Journal of Chemistry and Chemical Engineering (IJCCE), 23(2), 13-23.en_US
dc.identifier.issn1021-9986
dc.identifier.urihttp://www.ijcce.ac.ir/article_8134.html
dc.identifier.urihttps://iranjournals.nlai.ir/handle/123456789/84100
dc.description.abstract<em>This article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (MPC) of a chemical plant. A combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (MIMO) process with time delays.  An optimization procedure for a neural MPC algorithm based on this model is then developed. The proposed scheme has been tested on a model of an 18-plate multi-component distillation column. The algorithm provides excellent disturbance rejection for this process.</em>en_US
dc.format.extent1121
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoen_US
dc.publisherIranian Institute of Research and Development in Chemical Industries (IRDCI)-ACECRen_US
dc.relation.ispartofIranian Journal of Chemistry and Chemical Engineering (IJCCE)en_US
dc.subjectMulti-component distillation columnen_US
dc.subjectNeural Networksen_US
dc.subjectNonlinear Model-predictive controlen_US
dc.subjectMass Transfer, Separation Processesen_US
dc.titleRejection of the Feed-Flow Disturbances in a Multi-Component Distillation Column Using a Multiple Neural Network Model-Predictive Controlleren_US
dc.typeTexten_US
dc.typeResearch Articleen_US
dc.contributor.departmentThe Petroleum University of Technology, P.O. Box 63431, Ahwaz, I.R. IRANen_US
dc.citation.volume23
dc.citation.issue2
dc.citation.spage13
dc.citation.epage23


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