• DocumentCode
    2293764
  • Title

    PMSM Control Research Based on Particle Swarm Optimization BP Neural Network

  • Author

    Yu, Ren ; Zhou Li-meng

  • Author_Institution
    Intell. Control Inst., Hangzhou Dianzi Univ., Hangzhou
  • fYear
    2008
  • fDate
    22-24 Sept. 2008
  • Firstpage
    832
  • Lastpage
    836
  • Abstract
    This paper presents a control method of the combination of particle swarm optimization algorithm (PSO) and BP neural network for the control of PMSM. PSO can easily and quickly find a optimal parameters of PI, which can be used to generate the study sample space of BP neural network .The BP neural network can be off-line learning, then the network after learning apply to PI controller to control PMSM. This method combines the advantages of PSO and BP neural network learning ability. Compare with the traditional PI control, this method shows a better control performance, can quickly learn ideal PI parameters for motor control.
  • Keywords
    PI control; backpropagation; machine control; neurocontrollers; optimal control; particle swarm optimisation; permanent magnet motors; synchronous motors; BP neural network learning ability; PI controller; PI parameters; PMSM control research; motor control; particle swarm optimization BP neural network; Control systems; Electronic mail; Motor drives; Neural networks; Optimal control; Particle swarm optimization; Pi control; Position control; System performance; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cyberworlds, 2008 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-0-7695-3381-0
  • Type

    conf

  • DOI
    10.1109/CW.2008.140
  • Filename
    4741407