DocumentCode
2498401
Title
DRNN network DTC in electromagnetic continuously variable transmission
Author
Fu, Xingfeng ; Luo, Yutao ; Zhou, Sijia ; Zhang, Yinxian
Author_Institution
Dept. of Automobile Eng., South China Univ. of Technol., Guangzhou
fYear
2008
fDate
25-27 June 2008
Firstpage
7831
Lastpage
7834
Abstract
In order to reduce the serious fluctuation of torque, fluxes and stator current in electromagnetic continuously variable transmission motor direct torque control, an amendatory direct torque control method based on the diagonal recurrent neural network technology was presented in this paper. This method can reduce the torque and flux ripple in static run and enhance the performance of low speed. The simulation experimental results indicate that this method may be feasible alternative and high robust capabilities.
Keywords
machine control; recurrent neural nets; torque control; DRNN network DTC; diagonal recurrent neural network technology; electromagnetic continuously variable transmission; flux ripple; motor direct torque control; Converters; Engines; Equations; Mechanical power transmission; Reluctance motors; Rotors; Shafts; Stator windings; Torque control; Vehicles; Direct Torque Control; Motor Timing System; Robust Characteristic;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-2113-8
Electronic_ISBN
978-1-4244-2114-5
Type
conf
DOI
10.1109/WCICA.2008.4594151
Filename
4594151
Link To Document