• Title of article

    Improved Algorithms for Flush Airdata Sensing System

  • Author/Authors

    ZHENG، نويسنده , , Cheng-jun and LU، نويسنده , , Yu-ping and HE، نويسنده , , Zhen، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2006
  • Pages
    6
  • From page
    334
  • To page
    339
  • Abstract
    The Flush Airdata Sensing (FADS) system and its pressure model are presented briefly. The improved algorithm for calculating the impact pressure, static pressure and modifying coefficient are studied. First, the non-linear equations are simplified using Moore-Penrose inverse. Then the impact pressure and static pressure are computed with the improved iteration and BP neural network. Both the two improved algorithms meet the requirements of the flush airdata sensing system on precision, reliability and speed. BP neural network has great advantages on real-time requirements, for it needs only 5% time to reach the required precision comparing to the original algorithm.
  • Keywords
    flush airdata sensing system , general inverse , BP neural network , Convergence
  • Journal title
    Chinese Journal of Aeronautics
  • Serial Year
    2006
  • Journal title
    Chinese Journal of Aeronautics
  • Record number

    2264602