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An on-line adaptive control based on DO/pH measurements and ANN pattern recognition model for fed-batch cultivation

Paper ID Volume ID Publish Year Pages File Format Full-Text
4927 258 2006 9 PDF Available
Title
An on-line adaptive control based on DO/pH measurements and ANN pattern recognition model for fed-batch cultivation
Abstract

An on-line adaptive control strategy based on DO/pH measurements and artificial neural network pattern recognition (ANNPR) model for fed-batch cultivation processes was proposed. Various changing patterns of pH and dissolved oxygen concentration (DO) under pH-Stat, DO-Stat, and the conditions of substrate in excess were collected and used to train the ANNPR models. Based on the on-line measured pH and DO data, the recognition results on current physiological state was deduced by the ANNPR models, and then the on-line adaptive control of nutrient feeding rate was implemented. Compared with the traditional pH-Stat control, the proposed control strategy increased cell productivity about 150% without byproduct accumulation. The control strategy is potentially useful for high cell density cultivation of recombinant microorganisms to efficiently express value-added foreign proteins or enzyme with the most traditional pH and DO sensors.

Keywords
Artificial neural network; Fed-batch culture; On-line adaptive control; Pattern recognition; Traditional pH and DO sensors
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An on-line adaptive control based on DO/pH measurements and ANN pattern recognition model for fed-batch cultivation
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biochemical Engineering Journal - Volume 30, Issue 1, 1 May 2006, Pages 88–96
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us