• 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