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
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