DocumentCode
488516
Title
Optimizing Neural Net based Predictive Control
Author
Donat, Jean Saint ; Bhat, Naveen ; McAvoy, Thomas J.
Author_Institution
Department of Chemical Engineering, University of Maryland, College Park, MD 20742
fYear
1990
fDate
23-25 May 1990
Firstpage
2466
Lastpage
2472
Abstract
Neural networks hold great promise for application in the general area of process control. This paper focuses on using a backpropagation network in an optimization based model predictive control scheme. Since analytical expressions for the gradient and Hessian of the neural net model can be derived and these expressions can be calculated in paralle, extremely fast computation times are possible. The control approach is illustrated on a pH CSTR example.
Keywords
Algorithm design and analysis; Backpropagation algorithms; Biological neural networks; Chemicals; Computer architecture; Continuous-stirred tank reactor; Neural networks; Neurons; Predictive control; Speech analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 1990
Conference_Location
San Diego, CA, USA
Type
conf
Filename
4791171
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