DocumentCode :
2693202
Title :
Classical vs. neural network control: an industrial application
Author :
Moncada, R. ; De Castillo, Maite Uria
Author_Institution :
Dept. de Procesos y Sistemas, Simon Bolivar Univ., Caracas, Venezuela
Volume :
3
fYear :
1994
fDate :
2-5 Oct 1994
Firstpage :
2443
Abstract :
A comparison between a conventional PI control vs. a multilayered neural network (MNN) scheme over an industrial process is presented. The process is a distillation column which has a conventional temperature feedback control loop. Also taken under consideration is the first order dynamic of a thermowell with which the temperature of the third stage of the column is measured. The control action takes place 5 minutes after startup of the process. Two kinds of networks were used: one with three layers and another with four layers, all trained under the back-propagation learning algorithm
Keywords :
backpropagation; chemical industry; distillation; feedback; multilayer perceptrons; neurocontrollers; process control; 5 min; back-propagation learning algorithm; distillation column; industrial process; multilayered neural network; neural network control; temperature feedback control loop; thermowell; Distillation equipment; Error correction; Feedback control; Industrial control; Multi-layer neural network; Neural networks; Pi control; Temperature control; Temperature distribution; Valves;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2129-4
Type :
conf
DOI :
10.1109/ICSMC.1994.400233
Filename :
400233
Link To Document :
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