• DocumentCode
    482563
  • Title

    Based on fuzzy-neural network of high speed linear induce motor efficiency optimization (HSLIMEO)

  • Author

    Hanxia, Zhang ; Yongxian, Song

  • Author_Institution
    Dept. of Electron. Eng., Huaihai Inst. of Technol., Lianyungang
  • fYear
    2008
  • fDate
    17-20 Oct. 2008
  • Firstpage
    1515
  • Lastpage
    1519
  • Abstract
    Electromagnetic aircraft launch system (EMALS) use linear motor to accelerate aircraft to launch speed. This paper presents a new method based on fuzzy-neural of HSLIMEO. It is important to improve efficiency not only saving economic and energy, but also reducing environmental pollution. To optimize efficiency, fuzzy controller combined with field-oriented scheme is proposed to work to optimize flux during transients, and neural network state-observe (NNSO) is adopted to predict steady-state condition time for the rotor flux. The drive system with the proposed efficiency optimization controller has been simulated with high speed linear induce motor. The desired result is to increase the overall efficiency of the motor by bringing the rotor flux wave up to its desired level before the actual acceleration begins.
  • Keywords
    aircraft power systems; environmental factors; fuzzy control; induction motor drives; linear motors; machine vector control; neurocontrollers; EMALS; HSLIMEO; NNSO; electromagnetic aircraft launch system; environmental pollution reduction; field oriented control; field-oriented scheme; fuzzy controller; fuzzy-neural network; high speed linear induce motor efficiency optimization; linear induction motor drives; neural network state-observe; optimization controller; rotor flux steady-state condition time; Acceleration; Aircraft; Economic forecasting; Electromagnetic launching; Environmental economics; Fuzzy control; Fuzzy neural networks; Pollution; Power generation economics; Rotors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-3826-6
  • Electronic_ISBN
    978-7-5062-9221-4
  • Type

    conf

  • Filename
    4770967