• DocumentCode
    3433545
  • Title

    The investigation of ANN space vector PWM and diagnostic controller for four switch three phase inverter fed induction motor drive

  • Author

    Lee, Hong Hee ; Dzung, Phan Quoc ; Hoa, Truong Phuoc ; Phuong, Le Minh

  • Author_Institution
    Sch. of Electr. Eng., Univ. of Ulsan, Ulsan
  • fYear
    2009
  • fDate
    10-13 Feb. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper is to present the investigation of neural-network-based controller of space vector modulation (ANN-SVPWM) for four switch three phase inverter (FSTPI) fed induction motor drive. This ANN-SVPWM controller completely covers the under modulation and over modulation modes with operation extended linearly and smoothly up to square wave (six-step). The ANN controller uses the individual training strategy with the fixed weight and supervised models. Furthermore, ANN diagnosis method for real-time fault detection of power switches is proposed in this paper. The complete ANN-SVPWM and diagnostic controller can be used in power applications such as motor drives. A computer simulation program is developed using Matlab/Simulink together with the neural network toolbox for training the ANN-controller.This method has been validated experimentally using kit ACE 1104 (DSPACE) .
  • Keywords
    PWM invertors; induction motor drives; machine control; neurocontrollers; diagnostic controller; four switch three phase inverter; neural network toolbox; neural-network-based controller; real-time fault detection; space vector modulation; three phase inverter fed induction motor drive; Application software; Artificial neural networks; Fault detection; Fault diagnosis; Induction motor drives; Mathematical model; Phase modulation; Pulse width modulation inverters; Space vector pulse width modulation; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology, 2009. ICIT 2009. IEEE International Conference on
  • Conference_Location
    Gippsland, VIC
  • Print_ISBN
    978-1-4244-3506-7
  • Electronic_ISBN
    978-1-4244-3507-4
  • Type

    conf

  • DOI
    10.1109/ICIT.2009.4939636
  • Filename
    4939636