Application of MN-AGC based on intelligent control in continuous hot rolling

Author

Li, Bo-qun ; Le Yu

Author_Institution

Sch. of Electron. & Inf. Eng., Univ. of Sci. & Technol. Liaoning, Anshan

fYear

2008

fDate

1-3 Sept. 2008

Firstpage

2402

Lastpage

2405

Abstract

It is always primary object to improve gauge control accuracy in hot strip mills. Limitation based on conventional PID emerges when the controlled object is strong nonlinear, uncertain and multi-constrained features. BP-PID control strategy is introduced in MN-AGC for realizing finished combination of controller parameters. The practical application results have shown the effectiveness of this algorithm. The controller has better adaptability for varieties of model parameters and environment changes, which makes a output follow system input tracks faster.

Keywords

adaptive control; gauges; hot rolling; neurocontrollers; nonlinear control systems; process control; rolling mills; strips; three-term control; uncertain systems; BP neural network; BP-PID control strategy; MN-AGC system; adaptive controller; backpropagation; continuous hot rolling; gauge control; hot strip mill; intelligent control; multi constrained feature; nonlinear system; uncertain system; Automatic control; Control systems; Intelligent control; Milling machines; Neural networks; Nonlinear control systems; Pi control; Proportional control; Strips; Three-term control; BP neural network; hot strip; monitor AGC;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on

Conference_Location

Qingdao

Print_ISBN

978-1-4244-2502-0

Electronic_ISBN

978-1-4244-2503-7

Type

conf

DOI

10.1109/ICAL.2008.4636570

Filename

4636570