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A recurrent neural network model to describe manufacturing cell dynamics

Rovithakis, George A., 1968-, Gaganis Vasileios, Christodoulou Manolis, Perrakis, Stelios

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URIhttp://purl.tuc.gr/dl/dias/A14634BF-82F7-435C-92ED-202FC4AF2453-
Identifierhttps://doi.org/10.1109/CDC.1996.572808-
Identifierhttp://ieeexplore.ieee.org/document/572808/-
Languageen-
Extent6 pagesen
TitleA recurrent neural network model to describe manufacturing cell dynamicsen
CreatorRovithakis, George A., 1968-en
CreatorGaganis Vasileiosen
CreatorΓαγανης Βασιλειοςel
CreatorChristodoulou Manolisen
CreatorΧριστοδουλου Μανωληςel
CreatorPerrakis, Steliosen
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryA neural network approach to the manufacturing cell modelling problem is discussed. A recurrent high-order neural network structure (RHONN) is employed to identify cell dynamics, which is supposed to be unknown. The model is constructed in such a way that enables the design of a controller which will force the model and thus the original cell to display the required behaviour. The control input signal is transformed to a continuous one so as to conform with the RHONN assumptions, thus converting the original discrete-event system to a continuous one. A case study demonstrates the approximation capabilities of the proposed architecture.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-07-
Date of Publication1996-
SubjectArtificial neural networksen
SubjectNets, Neural (Computer science)en
SubjectNetworks, Neural (Computer science)en
SubjectNeural nets (Computer science)en
Subjectneural networks computer scienceen
Subjectartificial neural networksen
Subjectnets neural computer scienceen
Subjectnetworks neural computer scienceen
Subjectneural nets computer scienceen
SubjectFlexible production systemsen
SubjectFMS (Production engineering)en
SubjectManufacturing systems, Flexibleen
SubjectProduction systems, Flexibleen
Subjectflexible manufacturing systemsen
Subjectflexible production systemsen
Subjectfms production engineeringen
Subjectmanufacturing systems flexibleen
Subjectproduction systems flexibleen
Bibliographic CitationG. Rovithakis, V. Gaganis, S. Perrakis and M. Christodoulou, “A recurrent neural network model to describe manufacturing cell dynamics”, in 1996 35th IEEE Conference on Decision and Control, pp. 1728-1733. doi: 10.1109/CDC.1996.572808en

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