• DocumentCode
    3473964
  • Title

    Voltage-type active power line conditioner based on a novel neural network control scheme

  • Author

    Wang, Yen-Ju ; O´Connell, Robert M.

  • Author_Institution
    Dept. of Electr. Eng., Missouri Univ., Columbia, MO, USA
  • Volume
    2
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    861
  • Abstract
    The purpose of this paper is to propose a voltage-type active power line conditioner (APLC) with a neural network control using a fixed-frequency with variable-slope control method to obtain training data. The APLC is a type of active filter which is a very efficient apparatus for compensating harmonics caused by nonlinear loads. Simulations of the proposed APLC have been performed and compared to APLC with other means of control including constant frequency control, tolerance band control, sliding mode control and PWM control. The results show that the proposed APLC has lower current total harmonic distortion (THD), better power factor improvement, and less switching power loss than an APLC with the other control methods considered
  • Keywords
    bridge circuits; harmonic distortion; harmonics suppression; invertors; neurocontrollers; power factor; power system control; power system harmonics; PWM control; active filter; constant frequency control; fixed-frequency; full bridge inverter; harmonics compensation; neural network control scheme; nonlinear loads; power factor improvement; sliding mode control; switching power loss; tolerance band control; total harmonic distortion; training data; variable-slope control method; voltage-type active power line conditioner; Active filters; Frequency control; Neural networks; Power harmonic filters; Pulse width modulation; Reactive power; Sliding mode control; Total harmonic distortion; Training data; Voltage control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, 1999. IECON '99 Proceedings. The 25th Annual Conference of the IEEE
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    0-7803-5735-3
  • Type

    conf

  • DOI
    10.1109/IECON.1999.816522
  • Filename
    816522