• DocumentCode
    523017
  • Title

    Based on Kalman Filtering Theory Gas Forecast System Research

  • Author

    Hua, Fu ; Feng, Wang

  • Author_Institution
    Electr. & Control Eng. Inst., Liaoning Project Technol. Univ., Huludao, China
  • Volume
    1
  • fYear
    2010
  • fDate
    4-6 June 2010
  • Firstpage
    69
  • Lastpage
    72
  • Abstract
    Based on modern control theory´s method, the research and the exploration gush out the process modelling using the Kalman filtering principle to the damp to carry on the real-time forecast. Carries on the description to the gas discharge process is the discrete system, 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 denoising most superior estimate and the predict that is also suitable for the computer observation system´s use. Has confirmed the algorithm feasibility through the experiment simulation and the sea day coal factory measured data contrast, for the gas forecast that has provided a new mentality.
  • Keywords
    Kalman filters; coal; forecasting theory; state-space methods; Kalman filtering theory; coal factory; discrete system; gas forecast system research; real-time forecast; state space model; state variable estimate; Computational modeling; Control theory; Discharges; Filtering theory; Kalman filters; Noise reduction; Predictive models; Production facilities; State estimation; State-space methods; Cannot control can observe; Control system; Gas forecast; Kalman filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Computing (ICIC), 2010 Third International Conference on
  • Conference_Location
    Wuxi, Jiang Su
  • Print_ISBN
    978-1-4244-7081-5
  • Electronic_ISBN
    978-1-4244-7082-2
  • Type

    conf

  • DOI
    10.1109/ICIC.2010.24
  • Filename
    5514234