• DocumentCode
    3017041
  • Title

    Kalman Filter Based on Wavelet Multi-scale Gas Forecasting System

  • Author

    Hua, Fu ; Feng, Wang

  • Author_Institution
    Electr. & Control Eng. Inst., Liaoning Project Technol. Univ., Huludao, China
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Firstpage
    1222
  • Lastpage
    1225
  • Abstract
    Based on modern control theory´s method, the research and the exploration gush out the process description the damp are the discrete systems, proposed unified the wavelet multi-scale principle by the Kalman filter to carry on the denoising most superior estimate and the real-time forecast to the system modeling. Uses the state space model, uses the preceding time the estimated value and the present time observed value renews to the state variable estimate, realizes to the gas predict that the use wavelet theory optimization algorithm precision. Have confirmed the algorithm feasibility through the experiment simulation and the measured data fitting, for the gas forecast that has provided a new mentality.
  • Keywords
    Kalman filters; discrete systems; gas industry; optimisation; real-time systems; signal denoising; state estimation; state-space methods; wavelet transforms; Kalman filter; data fitting; discrete system; modern control theory method; real time forecast; state space model; state variable estimation; system modeling; wavelet multiscale gas forecasting system; wavelet theory optimization algorithm; Fuel processing industries; Kalman filters; Noise; Noise measurement; Predictive models; Wavelet transforms; Gas prediction; control; kalman filter; wavelet multi-scale;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Control Engineering (ICECE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6880-5
  • Type

    conf

  • DOI
    10.1109/iCECE.2010.305
  • Filename
    5631781