Application of The Control Scheme based on RBF Inverse Dynamic Identification in Electrode System of Ladle Furnace

Author

Zhang, Shaode ; Zheng, Xiao

Author_Institution

Anhui Univ. of Technol., Maanshan

fYear

2007

fDate

23-25 May 2007

Firstpage

1109

Lastpage

1112

Abstract

RBF neural network ( RBFN ) based on nearest neighbor clustering algorithm is applied for three phase electrode system in Ladle Furnace ( LF ). Real time on line inverse identification and indirect decoupling of LF three phase electrode system is realized. Hereon, the inverse identification model is applied as inverse control model. The scheme of inverse control based on RBFN and PD control is designed, which is applied to LF electrode system successfully in third iron steel plant of Maanshan P.R.China.

Keywords

PD control; electric furnaces; electrodes; industrial control; industrial plants; radial basis function networks; steel manufacture; PD control; RBF inverse dynamic identification; RBF neural network; electrode system; indirect decoupling; inverse control; iron steel plant; ladle furnace; nearest neighbor clustering algorithm; three phase electrode system; Clustering algorithms; Control systems; Electrodes; Furnaces; Inverse problems; Iron; Nearest neighbor searches; Neural networks; PD control; Real time systems; RBFN; WinAC; electrode system in LF; inverse dynamic identification; on-line decoupling;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4244-0737-8

Electronic_ISBN

978-1-4244-0737-8

Type

conf

DOI

10.1109/ICIEA.2007.4318580

Filename

4318580