• DocumentCode
    128050
  • Title

    Torque ripples control and speed regulation of Permanent magnet Brushless dc Motor Drive using Artificial Neural Network

  • Author

    Kishore, Nikhitha ; Singh, Sushil

  • Author_Institution
    Electr. & Electron. Eng. Deptt., Lovely Prof. Univ., Jalandhar, India
  • fYear
    2014
  • fDate
    6-8 March 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents a torque control of Permanent magnet Brushless DC (PMBLDC) Motor Drive using Artificial Neural Network (ANN) for low torque ripples. Conventional BLDC Motor produces high ripples in electromagnetic torque and it is not directly controlled. The motor may lead to component loss as well as bearing failure due to vibrations caused by high torque ripples. The main drawback with the conventional Brushless dc motor drives (BLDCMD) is high torque ripples and the speed of BLDCMD is reduced under transient and dynamic state of operating condition. This drawback is reduced using with the proposed control technique. In this proposed control technique the speed of the BLDCMD is regulated by the PI controller and the torque ripple is reduced by the ANN. Complete simulation of the conventional BLDCMD is done in MATLAB Simulink.
  • Keywords
    DC motor drives; PI control; brushless DC motors; failure analysis; machine bearings; machine control; mathematics computing; neurocontrollers; permanent magnet motors; torque control; vibrations; ANN; BLDCMD speed; MATLAB Simulink; PI controller; PMBLDC motor drive; artificial neural network; bearing failure; dynamic state; electromagnetic torque; permanent magnet brushless dc motor drive; speed regulation; torque ripple control; transient state; vibrations; Artificial neural networks; Brushless DC motors; Permanent magnet motors; Synchronous motors; Torque; Artificial Neural Network (ANN); MATLAB Simulink; Permanent magnet Brushless DC motor drive (PMBLDC); direct current (DC);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering and Computational Sciences (RAECS), 2014 Recent Advances in
  • Conference_Location
    Chandigarh
  • Print_ISBN
    978-1-4799-2290-1
  • Type

    conf

  • DOI
    10.1109/RAECS.2014.6799498
  • Filename
    6799498