Neural network based control of the acrylonitrile polymerization process

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dc.authoridYuceer, Mehmet/0000-0002-2648-3931
dc.authorwosidYuceer, Mehmet/E-5110-2012
dc.contributor.authorAtasoy, Ilknur
dc.contributor.authorYuceer, Mehmet
dc.contributor.authorUlker, Ekrem Olguz
dc.contributor.authorBerber, Ridvan
dc.date.accessioned2024-08-04T20:30:38Z
dc.date.available2024-08-04T20:30:38Z
dc.date.issued2007
dc.departmentİnönü Üniversitesien_US
dc.description.abstractAcrylic fiber is commercially produced by free radical polymerization, initiated by a redox system. Industrial production of polyacrylonitrile is a variant of aqueous dispersion polymerization, which takes place in a homogenous phase under isothermal conditions with perfect mixing. The fact that the kinetics are a lot more complicated than those of ordinary polymerization systems makes it difficult to control the molecular weight. On the other hand, abundant data is being gathered in industrial polymerization systems, and this information makes the neural network based controllers a good candidate for managing such a difficult control problem. Multilayer neural networks have been applied successfully in the identification and control of dynamic systems. In this work, the neural network based control of continuous acrylonitrile (ACN) polymerization is studied, based on a previously developed new rigorous dynamic model for the polymerization of acrylonitrile. Two typical neural network controllers are investigated, i.e., model predictive control and NARMA-L2 (Nonlinear Auto Regressive Moving Average) control. These controllers are representative of the variety of common ways in which multilayer networks are used in control systems. The results present a comparison of the two common neural network controllers, and indicate that the model predictive controller requires a larger computational time.en_US
dc.identifier.doi10.1002/ceat.200700225
dc.identifier.endpage1531en_US
dc.identifier.issn0930-7516
dc.identifier.issue11en_US
dc.identifier.scopus2-s2.0-36348936777en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1525en_US
dc.identifier.urihttps://doi.org/10.1002/ceat.200700225
dc.identifier.urihttps://hdl.handle.net/11616/94403
dc.identifier.volume30en_US
dc.identifier.wosWOS:000251005400010en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWiley-V C H Verlag Gmbhen_US
dc.relation.ispartofChemical Engineering & Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectneural networksen_US
dc.subjectpolymerizationen_US
dc.titleNeural network based control of the acrylonitrile polymerization processen_US
dc.typeArticleen_US

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