DocumentCode
487851
Title
Use of Neural Nets For Dynamic Modeling and Control of Chemical Process Systems
Author
Bhat, Naveen ; Avoy, Thomas J.Mc
Author_Institution
Department of Chemical Engineering, University of Maryland, College Park, MD 20742
fYear
1989
fDate
21-23 June 1989
Firstpage
1342
Lastpage
1348
Abstract
Neural nets are inherently parallel and they hold great promise because of their ability to "learn" nonlinear relationships. This paper discusses the use of backpropagation neural nets for dynamic modeling and control of chemical process systems. The backpropagation algorithm and its rationale are reviewed. The algorithm is applied succesfully to model the dynamic response of pH in a CSTR. The use of backpropagation models for control is briefly discussed.
Keywords
Backpropagation algorithms; Chemical processes; Concurrent computing; Medical control systems; Neural networks; Pattern analysis; Pattern recognition; Process control; Signal analysis; Speech analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 1989
Conference_Location
Pittsburgh, PA, USA
Type
conf
Filename
4790399
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