• DocumentCode
    1890919
  • Title

    Parameter Identification of PMSM Based on FHPSO Algorithm

  • Author

    Qian Miao-wang ; Tan Guo-Jun ; Ling Zang

  • Author_Institution
    Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
  • fYear
    2010
  • fDate
    25-26 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A new fuzzy hybrid particle swarm optimization algorithm (FHPSO) is presented in the paper for parameter identification of permanent magnet synchronous motor (PMSM).The FHPSO algorithm uses hybrid optimal model which is obtained by the combination of global optimal model and local optimal model.And for the disadvantages of basic particle swarm optimization (BPSO) and fuzzy particle swarm optimization (FPSO) algorithm proposed by former researchers,a new fuzzy control method for inertia weight is presented.The results of comparison between BPSO,FPSO and FHPSO algorithms show that the FHPSO algorithm has better capacity than other 2 algorithms.In addition,the results of parameter identification indicate that the algorithm has good performances on different noise levels. Therefore,the FHPSO algorithm is viable for parameter identification of PMSM.
  • Keywords
    fuzzy control; machine control; particle swarm optimisation; permanent magnet motors; synchronous motors; BPSO; FHPSO algorithm; FPSO; PMSM; fuzzy control; fuzzy hybrid particle swarm optimization; global optimal model; hybrid optimal model; inertia weight; local optimal model; parameter identification; permanent magnet synchronous motor; Fuzzy control; Noise level; Optimization; Parameter estimation; Particle swarm optimization; Permanent magnet motors; Prediction algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
  • Conference_Location
    Wuhan
  • ISSN
    2156-7379
  • Print_ISBN
    978-1-4244-7939-9
  • Electronic_ISBN
    2156-7379
  • Type

    conf

  • DOI
    10.1109/ICIECS.2010.5677904
  • Filename
    5677904