• DocumentCode
    1413560
  • Title

    Feedback-Feedforward PI-Type Iterative Learning Control Strategy for Hybrid Active Power Filter With Injection Circuit

  • Author

    Luo, An ; Xu, Xianyong ; Fang, Lu ; Fang, Houhui ; Wu, Jingbing ; Wu, Chuanping

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
  • Volume
    57
  • Issue
    11
  • fYear
    2010
  • Firstpage
    3767
  • Lastpage
    3779
  • Abstract
    In this paper, the configuration characteristic of Hybrid active power filter (APF) with injection circuit (IHAPF) is analyzed, as well as its current closed-loop control model is established. Because of the character of reperiod of current harmonics in steady-load power system, the iterative learning control algorithm based on the PI-type learning law is presented. The systemic robustness is enhanced by using a forgetting factor. In order to improve the dynamic performance of a control system, a feedforward based on the D-type learning law of referenced current error by fuzzy reasoning is proposed. The system of the IHAPF with the proposed control strategy has been applied in a steel plant in Guangxi, China. Simulation and industrial application results show that the IHAPF with the proposed control method is not only easy to calculate and implement but also very effective in improving the performance of the filter. Meanwhile, IHAPF shows great promise in reducing harmonics and improving power factor with a relatively low capacity of APF.
  • Keywords
    PI control; electric current control; fuzzy control; fuzzy reasoning; intelligent control; power filters; D-type learning law; current closed loop control; current error; feedback-feedforward PI type control; fuzzy reasoning; hybrid active power filter; injection circuit; iterative learning control; Active filters; Circuit analysis; Control systems; Feedback circuits; Hybrid power systems; Power harmonic filters; Power system analysis computing; Power system dynamics; Power system harmonics; Power system modeling; D-type learning law; PI-type iterative learning control; forgetting factor; fuzzy adjustor; hybrid active power filter (APF);
  • fLanguage
    English
  • Journal_Title
    Industrial Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0046
  • Type

    jour

  • DOI
    10.1109/TIE.2010.2040567
  • Filename
    5409664