| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 755644 | Chinese Journal of Aeronautics | 2006 | 6 Pages |
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.
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