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Integration of Expert Systems and Neural Networks for the Control of Fermentation Processes

Gehlen, Stefan ; Tolle, Henning ; Kreuzig, J. ; Friedl, Peter (2023)
Integration of Expert Systems and Neural Networks for the Control of Fermentation Processes.
In: IFAC Proceedings Volumes, 1992, 25 (2)
doi: 10.26083/tuprints-00023386
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Integration of Expert Systems and Neural Networks for the Control of Fermentation Processes
Language: English
Date: 2023
Place of Publication: Darmstadt
Year of primary publication: 1992
Publisher: IFAC - International Federation of Automatic Control
Journal or Publication Title: IFAC Proceedings Volumes
Volume of the journal: 25
Issue Number: 2
DOI: 10.26083/tuprints-00023386
Corresponding Links:
Origin: Secondary publication service
Abstract:

Expert systems and neural networks are new tools for the control of fermentation processes. With expert systems the fermentation plant and the process itself is modelled via a generalized, qualitative system description based on the experience of human experts. On the other hand neural networks and interpolating associative memories can learn the process behaviour directly by process observation. The paper at hand reports, how both control techniques can be combined for purposes like process supervision, modelling and optimization of biological plants.

Uncontrolled Keywords: Expert systems, neural networks, associative memories, learning control, fermentation processes, biotechnology
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-233869
Additional Information:

Zugl. Konferenzveröffentlichung: 2nd IFAC Symposium on Modelling and Control of Biotechnical Processes and Computer Applications in Fermentation Technology (5th International Conference), 29.03.-02.04.1992, Keystone, Colorado, USA

Classification DDC: 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau
Divisions: 18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Intelligent Systems
Date Deposited: 25 Apr 2023 12:37
Last Modified: 12 Jul 2023 12:25
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/23386
PPN: 509531334
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