Abstract
The purpose of this paper is to investigate the use of evolutionary fuzzy neural systems to aircraft automatic landing control and to make the automatic landing system more intelligent. Three intelligent aircraft automatic landing controllers are presented that use fuzzy-neural controller with BPTT algorithm, hybrid fuzzy-neural controller with adaptive control gains, and fuzzy-neural controller with particle swarm optimization, to improve the performance of conventional automatic landing system. Current flight control law is adopted in the intelligent controller design. Tracking performance and adaptive capability are demonstrated through software simulations. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Juang, J. G., Lin, B. S., & Chin, K. C. (2006). Intelligent fuzzy systems for aircraft landing control. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3613 LNAI, pp. 851–860). Springer Verlag. https://doi.org/10.1007/11539506_105
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