• DocumentCode
    3057477
  • Title

    Adaptive Control for Single-Phase Unified Power Quality Conditioner Using Neural Networks

  • Author

    Li, Chunwen ; Rong, Yuanjie ; Cao, Lingzhi ; Zheng, Xuesheng

  • Author_Institution
    Key Lab. of Informational Electr. Apparatus in Henan State, Zhengzhou Univ. of Light Ind., Zhengzhou
  • fYear
    2007
  • fDate
    14-17 Sept. 2007
  • Firstpage
    146
  • Lastpage
    150
  • Abstract
    Reliable model and high performance controller are of two main issues in research of single-phase Unified Power Quality Conditioner (UPQC). Single-phase UPQC is a nonlinear multi input multi output coupled system and can´t be modeled accurately. Therefore neural network with NARMA-L2 structure is utilized to describe the dynamic progress. Based on the NARMA-L2 model, neural feedback linearization controllers are designed for shunt and series active power filters separately. For the DC-link side, a PI-controller is used to maintain the voltage around the reference value. Parameters perturbation and load change simulation experiments are performed to verify the effectiveness, robustness and reliability of the proposed control strategy.
  • Keywords
    MIMO systems; PI control; active filters; adaptive control; autoregressive moving average processes; control system synthesis; feedback; linearisation techniques; neurocontrollers; nonlinear control systems; power harmonic filters; power supply quality; DC-link voltage; NARMA-L2 structure; PI-controller; adaptive control; neural feedback linearization controller design; neural network; nonlinear autoregressive moving average model; nonlinear multi input multi output coupled system; series active power filter; shunt active power filter; single-phase unified power quality conditioner; Active filters; Adaptive control; Couplings; Linear feedback control systems; Neural networks; Neurofeedback; Nonlinear dynamical systems; Power quality; Power system modeling; Power system reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bio-Inspired Computing: Theories and Applications, 2007. BIC-TA 2007. Second International Conference on
  • Conference_Location
    Zhengzhou
  • Print_ISBN
    978-1-4244-4105-1
  • Electronic_ISBN
    978-1-4244-4106-8
  • Type

    conf

  • DOI
    10.1109/BICTA.2007.4806438
  • Filename
    4806438