Application of fuzzy logic for automatic shape control in stainless steel rolling process

Author

Hur, YoneGi ; Rhee, DaeKeun

Author_Institution

Tech. Res. Lab., POSCO, Kyungbuk, South Korea

Volume

1

fYear

2001

fDate

25-28 July 2001

Firstpage

251

Abstract

The shape control of the stainless steel rolling has difficulty in obtaining symmetric shape and stabilizing strip shape despite an abnormal state that shows asymmetric shape pattern with respect to strip lateral direction. The objective of the shape control is to stabilize shape and material flow. The method for the strip shape recognition uses neural network (NN) and least squares method (LSQ). NN extracts symmetric component from the shape error. Moreover, LSQ does curve fitting and classifies the shape error into asymmetry. Fuzzy control method utilizing operator´s knowledge will be proposed in this paper. The experiments are carried out online and then the results show very efficient performance on tracking of the target shape

Keywords

curve fitting; fuzzy control; hot rolling; least squares approximations; neurocontrollers; pattern classification; process control; shape control; stability; stainless steel; steel manufacture; LSA; automatic shape control; curve fitting; fuzzy logic; least squares method; neural network; stainless steel rolling; strip shape stabilization; target shape tracking; Actuators; Error correction; Fuzzy control; Fuzzy logic; Milling machines; Neural networks; Shape control; Shape measurement; Steel; Strips;

fLanguage

English

Publisher

ieee

Conference_Titel

IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th

Conference_Location

Vancouver, BC

Print_ISBN

0-7803-7078-3

Type

conf

DOI

10.1109/NAFIPS.2001.944260

Filename

944260