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Integration of distributed multi-analyzer monitoring and control in bioprocessing based on a real-time expert system
Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för fysik, kemi och biologi, Teknisk biologi.ORCID-id: 0000-0001-9711-794X
2003 (engelsk)Inngår i: Journal of Biotechnology, ISSN 0168-1656, E-ISSN 1873-4863, Vol. 103, nr 3, s. 237-248Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

A computer system solution for integration of a distributed bioreactor monitoring and control instrumentation on the laboratory scale is described. Bioreactors equipped with on-line analyzers for mass spectrometry, near-infrared spectroscopy, electrochemical probes and multi-array gas sensors and their respective software were networked through a real-time expert systems platform. The system allowed data transmission of more than 1800 different signals from the instrumentation, including signals from gas sensors, electrodes, spectrometer detectors, balances, flowmeters, etc., and were used for processing and carrying out a number of computational tasks such as partial least-square regression, principal component analysis, artificial neural network modelling, heuristic decision-making and adaptive control. The system was demonstrated on different cultivations/fermentations which illustrated sensor fusion control, multivariate statistical process monitoring, adaptive glucose control and adaptive multivariate control. The performance of these examples showed high operational stability and reliable function and meet typical requirements for production safety and quality. © 2003 Elsevier B.V. All rights reserved.

sted, utgiver, år, opplag, sider
2003. Vol. 103, nr 3, s. 237-248
Emneord [en]
Bioreactor monitoring, Fermentation control, Knowledge-based expert system, Multi-analyzers
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-46519DOI: 10.1016/S0168-1656(03)00121-4OAI: oai:DiVA.org:liu-46519DiVA, id: diva2:267415
Tilgjengelig fra: 2009-10-11 Laget: 2009-10-11 Sist oppdatert: 2019-01-22

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