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oai:uvadoc.uva.es:10324/337352021-06-23T11:22:05Zcom_10324_1168com_10324_931com_10324_894col_10324_1950

00925njm 22002777a 4500 dc Pitarch Pérez, José Luis author Prada Moraga, César de author 2018 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. J. L. Pitarch and C. de Prada, 2018. D2. 1-Report on dynamic data reconciliation of large-scale processes. Outcomes of the CoPro Project. http://uvadoc.uva.es/handle/10324/33735 D2. 1–Report on Dynamic Data Reconciliation of Large-Scale Processes