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