• DocumentCode
    2666336
  • Title

    Harmonic Detection Based on the TLS Estimation Algorithm

  • Author

    Kaipei, Liu ; Junmin, Zhang

  • Author_Institution
    Sch. of Electr. Eng., Wuhan Univ.
  • Volume
    3
  • fYear
    2006
  • fDate
    14-16 Aug. 2006
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Based on the Newton learning algorithm, a new algorithm for TLS estimation and its application in harmonic detection is presented in this paper. It is shown that the LMS algorithm and constrained anti-Hebbian algorithm are two examples of the proposed algorithm in this paper. To solve the contravention between the detecting precision and speediness, analog detecting architectures are studied. The simulation results show that its noise rejection capability is superior to those of the LMS and constrained anti-Hebbian algorithms and the new algorithm gives faster convergence and better precision than another two methods
  • Keywords
    learning (artificial intelligence); least mean squares methods; power engineering computing; power harmonic filters; LMS algorithm; Newton learning algorithm; TLS estimation algorithm; active power filter; constrained anti-Hebbian algorithm; convergence; harmonic detection; noise rejection capability; Active filters; Adaptive filters; Filtering theory; Frequency; Least squares approximation; Low pass filters; Neurons; Power harmonic filters; Power system harmonics; Power system transients; Newton algorithm; TLS estimation; adaptive; harmonic detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics and Motion Control Conference, 2006. IPEMC 2006. CES/IEEE 5th International
  • Conference_Location
    Shanghai
  • Print_ISBN
    1-4244-0448-7
  • Type

    conf

  • DOI
    10.1109/IPEMC.2006.4778287
  • Filename
    4778287