DocumentCode :
3572660
Title :
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
Link To Document :
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