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Dynamic on‐line optimization of a bioreactor

Dynamic on‐line optimization of a bioreactor 10.1002/bit.260350708.abs An algorithm was developed which uses recursive least squares to identify a dynamic, discrete time model of a poorly defined system and uses both the dynamic and static portions of the identified model for on‐line optimization. To test this new algorithm, a model of an continuous biochemical reactor was used as the “process.” The objective, here, was to maximize ethanol production from the reactor by manipulating the feed rate to the reactor. The new algorithm, which uses dynamic information, was found to be superior to previously published algorithms which use only the steady‐state portion of the identified model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biotechnology and Bioengineering Wiley

Dynamic on‐line optimization of a bioreactor

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References (12)

Publisher
Wiley
Copyright
Copyright © 1990 John Wiley & Sons, Inc.
ISSN
0006-3592
eISSN
1097-0290
DOI
10.1002/bit.260350708
pmid
18592567
Publisher site
See Article on Publisher Site

Abstract

10.1002/bit.260350708.abs An algorithm was developed which uses recursive least squares to identify a dynamic, discrete time model of a poorly defined system and uses both the dynamic and static portions of the identified model for on‐line optimization. To test this new algorithm, a model of an continuous biochemical reactor was used as the “process.” The objective, here, was to maximize ethanol production from the reactor by manipulating the feed rate to the reactor. The new algorithm, which uses dynamic information, was found to be superior to previously published algorithms which use only the steady‐state portion of the identified model.

Journal

Biotechnology and BioengineeringWiley

Published: Mar 25, 1990

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