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