DocumentCode :
2249462
Title :
Study on PID neural network control system in the main electromotor of the fine rolling mill
Author :
Guo, Xiucai ; Zhang, Tingting ; Zhang, Qiannan
Author_Institution :
Coll. of Electr. & Control Eng., Xi´´an Univ. of Sci. & Technol., Xi´´an, China
Volume :
2
fYear :
2010
fDate :
6-7 March 2010
Firstpage :
143
Lastpage :
146
Abstract :
The author analyzed the properties of a DC motor speed regulation system of rolling machine in the paper. He adopted PID neural network to form self-learning double loop closed DC moor speed regulating system. The forward and back-propagation are introduced and the double closed loop controller is constructed. The PID neural network adjusts its connective weight by self-learning and the complicated setting process to avoid tuning the parameters of the double loop controller. The better dynamic and steady-state behaviors are displayed in the simulation results.
Keywords :
DC motors; angular velocity control; backpropagation; closed loop systems; machine control; neurocontrollers; rolling mills; three-term control; DC motor speed regulation system; PID neural network control system; backpropagation; closed loop controller; double loop controller; main electromotor; rolling machine; rolling mill; self-learning; steady state behaviors; Control systems; Milling machines; Neural networks; Three-term control; DC motor speed regulation; double closed-loop regulation system; neural network control; rolling machine control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
Conference_Location :
Wuhan
ISSN :
1948-3414
Print_ISBN :
978-1-4244-5192-0
Electronic_ISBN :
1948-3414
Type :
conf
DOI :
10.1109/CAR.2010.5456748
Filename :
5456748
Link To Document :
بازگشت