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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40993

Title: Intelligent Automatic Landing System Using Fuzzy Neural Networks and Genetic Algorithm
Authors: Jih-Gau Juang;Kuo-Chih Chin;Jern-Zuin Chio
Contributors: 國立臺灣海洋大學:通訊與導航工程學系
Date: 2004
Issue Date: 2017-02-07T08:51:32Z
Publisher: American Control Conference, 2004. Proceedings of the 2004
Abstract: Abstract: In this paper, an intelligent automatic landing system using fuzzy neural networks and genetic algorithms is developed to improve the performance of the conventional automatic landing systems. This study uses a functional fuzzy neural network as the controller. Control gains are selected by a combination method of a nonlinear control design and genetic algorithm. The simulation results are described for the automatic landing system of a commercial airplane. Tracking performance and robustness are demonstrated through software simulations. Simulation results show that the proposed scheme can successfully expand the safety envelope of an aircraft to include severe wind disturbance environments.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40993
Appears in Collections:[通訊與導航工程學系] 演講及研討會

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