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Parameters selection in predictive online simulation
Aalto University, Helsinki.
VTT Technical Research Centre of Finland Ltd, Espoo.
VTT Technical Research Centre of Finland Ltd, Espoo.
VTT Technical Research Centre of Finland Ltd, Espoo.
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Antal upphovsmän: 72017 (Engelska)Ingår i: IEEE International Conference on Industrial Informatics (INDIN), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, s. 726-729, artikel-id 7819254Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Industrial applications with reliable predictive features are becoming increasingly important. A tracking simulator is an example of an online simulation system with great capabilities that fills the gap left by other predictive applications. In a tracking simulator, a simulation model is run in parallel with a physical process controlled by the process' control system. At the same time, a tracking mechanism is used to keep the state of the simulation model as close as possible to the real process by continually adjusting parameters of the model. The selection of these parameters impacts directly on the quality of the tracking simulation results and it is a complex task in processes with a big number of variables. This paper presents two case studies of tracking simulation where the controlled parameters are selected using different techniques. The first case study deals with a laboratory-scale hot water generation process where the parameters' selection is performed manually. The second case study deals with a combined heat and power production process with major uncertainties in the process structure. In this case, we focus on the variance decomposition method used to determine the most suitable controlled parameters. Conclusions and future work are finally presented.

Ort, förlag, år, upplaga, sidor
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017. s. 726-729, artikel-id 7819254
Serie
IEEE International Conference on Industrial Informatics INDIN, ISSN 1935-4576
Nationell ämneskategori
Datavetenskap (datalogi)
Forskningsämne
Kommunikations- och beräkningssystem
Identifikatorer
URN: urn:nbn:se:ltu:diva-62199DOI: 10.1109/INDIN.2016.7819254ISI: 000393551200110Scopus ID: 2-s2.0-85012912222ISBN: 9781509028702 (digital)OAI: oai:DiVA.org:ltu-62199DiVA, id: diva2:1077589
Konferens
14th IEEE International Conference on Industrial Informatics, INDIN 2016, Poitiers, France, 19-21 July 2016
Tillgänglig från: 2017-02-28 Skapad: 2017-02-28 Senast uppdaterad: 2018-01-13Bibliografiskt granskad

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Vyatkin, Valeriy

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