Neuro-fuzzy hybrid control system of nonlinear process in petroleum plant

Author

Tani, Tetsuji ; Sasada, Tomonari ; Utashiro, Makoto ; Umano, Motohide ; Tanaka, Kazuo

Author_Institution

Dept. of Manuf., Idemitsu Kosan Co. Ltd., Chiba, Japan

Volume

5

fYear

1995

fDate

Nov/Dec 1995

Firstpage

2501

Abstract

This paper proposes a practical control method using neural networks and fuzzy control techniques. Neural networks effectively simulate a well-experienced operator´s procedure to control the tank level with estimation of a rough control target. Fuzzy control techniques compensate the estimated rough control target using operator´s knowledge. The control system was applied to a reflux tank level control of a hydro-desulfurizing plant in the feed oil switching and it controlled the level effectively

Keywords

backpropagation; feedforward neural nets; fuzzy control; level control; neurocontrollers; petroleum industry; process control; backpropagation; feed oil switching; fuzzy control; hydro-desulfurizing plant; neural networks; neuro-fuzzy hybrid control system; nonlinear process; petroleum plant; tank level control; Artificial neural networks; Control systems; Feeds; Fuzzy control; Hydrogen; Inductors; Level control; Neural networks; Nonlinear control systems; Petroleum;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1995. Proceedings., IEEE International Conference on

Conference_Location

Perth, WA

Print_ISBN

0-7803-2768-3

Type

conf

DOI

10.1109/ICNN.1995.487755

Filename

487755