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Please use this identifier to cite or link to this item: http://scholars.ntou.edu.tw/handle/123456789/18138
Title: Intelligent Automatic Landing System Using Fuzzy Neural Networks and Genetic Algorithm
Authors: Jih-Gau Juang 
Kuo-Chih Chin
Jern-Zuin Chio
Keywords: intelligent systems;Intelligent networks;fuzzy neural networks;Genetic algorithms;fuzzy control;Automatic control;Control design;Airplanes;robustness;Software performance
Issue Date: 2-Jul-2004
Publisher: IEEE
Journal Volume: 6
Start page/Pages: 5790-5795
Conference: Proceedings of the 2004 American Control Conference
Boston, MA, USA
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://scholars.ntou.edu.tw/handle/123456789/18138
ISBN: 0-7803-8335-4
ISSN: 0743-1619
DOI: 10.23919/ACC.2004.1384780
Appears in Collections:通訊與導航工程學系

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