• DocumentCode
    684890
  • Title

    BLDC motor field orientation control system based on LPIDBP neural network

  • Author

    Xiao Jin-feng ; Zhang Lei ; Ou Min ; Zhu Fei-hui

  • Author_Institution
    Sch. of Electr. Eng., Univ. of South China, Hengyang, China
  • fYear
    2012
  • fDate
    7-9 Dec. 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In order to improve the performance of BLDC motor system , a brushless direct current (BLDC) motor FOC control system based on LPIDBP neural network is designed in this paper, which combining LPIDBP neural network with field orientation control (FOC) strategy. The control strategy and implementation method are put forward, and the system simulation model is established. The simulation results show the control performance of designed BLDC motor FOC control system is good, the torque ripple and speed ripple is small. STM32F103B is used as the main control chip to design the BLDC motor FOC control system test platform, and a BLDC motor monitoring system is designed by VB(Visual Basic). The contrast testing speed curves from monitoring system show the best performance of BLDC motor FOC control system based on LPIDBP neural network ,the system response is the fastest, the speed ripple is the smallest, and the operation is the stablest.
  • Keywords
    Visual BASIC; brushless DC motors; control system CAD; machine vector control; neurocontrollers; BLDC motor field orientation control system; BLDC motor monitoring system design; BLDC system performance; LPIDBP neural network; STM32F103B; VB; Visual Basic; brushless direct current motor FOC control system design; contrast testing speed curves; control chip; field orientation control strategy; speed ripple; system simulation model; torque ripple; BLDC motor; LPIDBP neural network; field orientation control; monitoring system;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Information Science and Control Engineering 2012 (ICISCE 2012), IET International Conference on
  • Conference_Location
    Shenzhen
  • Electronic_ISBN
    978-1-84919-641-3
  • Type

    conf

  • DOI
    10.1049/cp.2012.2476
  • Filename
    6755855