NDLI: Analysis of pilot landing control in crosswind using neural networks

Content Provider	IEEE Xplore Digital Library
Author	Mori, R. Suzuki, S.
Copyright Year	2009
Description	Author affiliation: University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Japan, 113-8656 (Mori, R.; Suzuki, S.)
Abstract	Human pilot control at visual approach has been analyzed using a neural network modeling technique. Neural network models simulate the relationship between control (e.g., elevator, throttle, etc.) and human input (visual information) and can be analyzed mathematically. In previous research, only longitudinal operation was analyzed, because the characteristic flare maneuver is said to be one of the most difficult maneuvers in normal operations. However, lateral control is also difficult especially under crosswind conditions. In a crosswind approach, crab control is applied first, and then winglow sideslip control is applied. The transition process of these two controls is called decrab, which is recognized as quite a difficult maneuver. Moreover, the longitudinal control also depends on the lateral control, and the influence of this coupling deserves some interest, too. In this paper we focus on the lateral control analysis. As in the previous research, neural network plot models are investigated with sensitivity analysis. Several simulator experiments were conducted with different pilots and under various wind conditions, and the analysis results clarify the differences in control strategies.
Starting Page	1
Ending Page	10
File Size	909873
Page Count	10
File Format	PDF
ISBN	9781424426218
ISSN	1095323X
DOI	10.1109/AERO.2009.4839640
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Aircraft Automatic control Analytical models Nose Air traffic control Humans Mathematical model Elevators Information analysis
Content Type	Text
Resource Type	Article
Subject	Aerospace Engineering Space and Planetary Science

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