Document Detail


Artificial intelligence and the supervision of bioprocesses (real-time knowledge-based systems and neural networks).
MedLine Citation:
PMID:  8460575     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The ability to supervise and control a highly non-linear and time variant bioprocess is of considerable importance to the biotechnological industries which are continually striving to obtain higher yields and improved uniformity of production. Two AI methodologies aimed at contributing to the overall intelligent monitoring and control of bioprocess operations are discussed. The development and application of a real-time knowledge-based system to provide supervisory control of fed-batch bioprocesses is reviewed. The system performs sensor validation, fault detection and diagnosis and incorporates relevant expertise and experience drawn from both bioprocess engineering and control engineering domains. A complementary approach, that of artificial neural networks is also addressed. The development of neural network modelling tools for use in bioprocess state estimation and inferential control are reviewed. An attractive characteristic of neural networks is that with the appropriate topology any non-linear functional relationship can be modelled, hence significantly reducing model-process mismatch. Results from industrial applications are presented.
Authors:
M Aynsley; A Hofland; A J Morris; G A Montague; C Di Massimo
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Review    
Journal Detail:
Title:  Advances in biochemical engineering/biotechnology     Volume:  48     ISSN:  0724-6145     ISO Abbreviation:  Adv. Biochem. Eng. Biotechnol.     Publication Date:  1993  
Date Detail:
Created Date:  1993-04-23     Completed Date:  1993-04-23     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  8307733     Medline TA:  Adv Biochem Eng Biotechnol     Country:  GERMANY    
Other Details:
Languages:  eng     Pagination:  1-27     Citation Subset:  IM    
Affiliation:
Department of Chemical and Process Engineering, University of Newcastle, Newcastle upon Tyne, England.
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MeSH Terms
Descriptor/Qualifier:
Artificial Intelligence*
Biotechnology*
Computer Systems
Fusarium / growth & development
Neural Networks (Computer)
Penicillin G / metabolism
Quality Control
Chemical
Reg. No./Substance:
61-33-6/Penicillin G

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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