DocumentCode :
2810717
Title :
Research of AC adjusting speed system based on DTC and neural network supervision control
Author :
Xu, Rui ; Bai, Hui
Author_Institution :
Coll. of Electr. & Inf. Eng., Anhui Univ. of Sci. & Technol., Quzhou, China
fYear :
2011
fDate :
15-17 July 2011
Firstpage :
4279
Lastpage :
4281
Abstract :
The conventional direct torque control system in low speed condition has the larger motor torque ripple, that makes the system´s low-speed performance poor. To address this problem, we use neural network supervisory controller to replace the original PID controller based on the traditional direct torque control system, and create a system model by the SimPowerSystems of MATLAB software. This system is simulated on the MATLAB / Simulink simulation platform ,and the simulation results are compared with the original system´s. Simulation results show that this method can effectively reduce the torque ripple of the direct torque control system in low-speed condition and improve the system´s low-speed performance.
Keywords :
induction motors; neurocontrollers; three-term control; torque control; velocity control; AC adjusting speed system; DTC; Matlab software; PID controller; SimPowerSystems; Simulink simulation; conventional direct torque control system; neural network supervision control; system low-speed performance; Educational institutions; Induction motors; MATLAB; Neurons; Simulation; Torque; Torque control; asynchronous motor; direct torque control; neural network supervision;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2011 Second International Conference on
Conference_Location :
Hohhot
Print_ISBN :
978-1-4244-9436-1
Type :
conf
DOI :
10.1109/MACE.2011.5987950
Filename :
5987950
Link To Document :
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