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<dc:title>D2. 1–Report on Dynamic Data Reconciliation of Large-Scale Processes</dc:title>
<dc:creator>Pitarch Pérez, José Luis</dc:creator>
<dc:creator>Prada Moraga, César de</dc:creator>
<dc:contributor>EU-SPIRE</dc:contributor>
<dc:description>Producción Científica</dc:description>
<dc:description>Availability of reliable process information in real time is key in any decision-making procedure. Thus, good industrial decision-support implementations require dealing with gross errors and consideration of process transients in order to get a set of measurements which will be coherent with the basic underlying process dynamics. This report presents dynamic data reconciliation methods and tools adapted to the requirements of industrial environments (large-scale systems and noisy/faulty data). Moreover, basic concepts in literature are extended to artificially increase system redundancy as well as to cope with time-varying parameter estimation. The procedure summarized in this report has been tested in the Lenzing case study.</dc:description>
<dc:date>2019-01-09T11:36:18Z</dc:date>
<dc:date>2019-01-09T11:36:18Z</dc:date>
<dc:date>2018</dc:date>
<dc:type>info:eu-repo/semantics/report</dc:type>
<dc:identifier>J. L. Pitarch and C. de Prada, 2018. D2. 1-Report on dynamic data reconciliation of large-scale processes. Outcomes of the CoPro Project.</dc:identifier>
<dc:identifier>http://uvadoc.uva.es/handle/10324/33735</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>https://www.spire2030.eu/copro</dc:relation>
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