• DocumentCode
    3302443
  • Title

    Unscented Kalman Filter for frequency and amplitude estimation

  • Author

    Novanda, H. ; Regulski, P. ; Gonzalez-Longatt, Francisco M. ; Terzija, Vladimir

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Univ. of Manchester, Manchester, UK
  • fYear
    2011
  • fDate
    19-23 June 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper introduces a new digital signal processing algorithm for frequency and amplitude estimation based on Unscented Kalman Filter (UKF). The results of computer simulated and realistic synthetic data tests are presented. The initial parameters used during the tests were chosen carefully using an established parameter estimation method, the Self Tuning Least Square (STLS). It is concluded that the proposed algorithm is simple, efficient and has low computational demands compare to STLS which makes the UKF a very promising method in next generation of power quality monitoring devices.
  • Keywords
    Kalman filters; amplitude estimation; digital signal processing chips; frequency estimation; least squares approximations; power supply quality; power system parameter estimation; STLS; UKF; amplitude estimation; digital signal processing algorithm; frequency estimation; parameter estimation method; power quality monitoring device; realistic synthetic data test; self tuning least square; unscented Kalman filter; Estimation; Frequency estimation; Kalman filters; Noise; Power quality; Power system dynamics; Signal processing algorithms; Kalman filters; amplitude estimation; frequency estimation; power quality; unscented transformation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    PowerTech, 2011 IEEE Trondheim
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-8419-5
  • Electronic_ISBN
    978-1-4244-8417-1
  • Type

    conf

  • DOI
    10.1109/PTC.2011.6019414
  • Filename
    6019414