Decoupling control of thickness and tension based on DRNN-PID in cold-rolling

Author

Boqun Li ; Xiangwen Fan ; Chunlian Jiang ; Guanjie Jiang

Author_Institution

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

fYear

2014

Firstpage

1180

Lastpage

1184

Abstract

Considering the features of coupling, multivariable, and nonlinearity in thickness and tension system for cold-rolling, this paper proposes a dynamic coupling model. Furthermore, a new compound decoupling control algorithm is designed based on diagonal recurrent neural network combined with PID(DRNN-PID) for decoupling control. Simulation results show the proposed algorithm has stronger adaptive tracking, faster response, and better anti-interference than PID. The performances can meet the requirement of practical rolling and effectively enhance the control accuracy of thickness and tension.

Keywords

cold rolling; neurocontrollers; recurrent neural nets; thickness control; three-term control; DRNN-PID; cold-rolling; compound decoupling control algorithm; diagonal recurrent neural network combined with PID; dynamic coupling model; tension control; tension system; thickness control; thickness system; Accuracy; Couplings; Equations; Heuristic algorithms; Mathematical model; Recurrent neural networks; Strips; Cold-rolling mill; DRNN-PID; Decoupling control; Thickness and tension;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2014 11th World Congress on

Type

conf

DOI

10.1109/WCICA.2014.7052886

Filename

7052886