• DocumentCode
    1797959
  • Title

    Application of fuzzy systems in the control of a shunt active power filter with four-leg topology

  • Author

    Acordi, Edson J. ; da Silva, I.N. ; Machado, Ricardo Q.

  • Author_Institution
    Inst. Fed. do Parana, Ivaipora, Brazil
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    1239
  • Lastpage
    1244
  • Abstract
    This paper presents the application of fuzzy controllers to act in the current control loop of a shunt active power filter (SAPF). The SAPF consists of a three-phase inverter with four-leg topology, and it has been used to reduce the harmonic content produced by nonlinear loads, as well as, in the reactive power compensation. The generation of the reference currents is based on the synchronous reference frame (SRF), which requires the use of a PLL (Phase Locked Loop) synchronization algorithm with the grid. The classic PI control is here replaced by a fuzzy controller that has features that allows fast convergence and robustness when there are parametric variations in the physical system. Results obtained from simulations are presented to validate the approach and to demonstrate the performance of the filter in the suppression of harmonic currents and reactive power.
  • Keywords
    active filters; convergence; fuzzy control; fuzzy systems; invertors; network topology; phase locked loops; power harmonic filters; reactive power control; robust control; synchronisation; PLL synchronization algorithm; SAPF; SRF; convergence; current control loop; four-leg topology; fuzzy controller; fuzzy systems; harmonic current suppression; nonlinear loads; phase locked loop; reactive power compensation; reactive power suppression; reference currents; robustness; shunt active power filter control; synchronous reference frame; three-phase inverter; Harmonic analysis; Insulated gate bipolar transistors; Niobium; Phase locked loops; Power harmonic filters; Reactive power; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), 2014 International Joint Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6627-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2014.6889705
  • Filename
    6889705