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Please use this identifier to cite or link to this item: http://scholars.ntou.edu.tw/handle/123456789/18139
Title: Intelligent landing control based on neural-fuzzy-GA hybrid system
Authors: Jih-Gau Juang 
Kuo-Chih Chin
Keywords: intelligent control;Control systems;automatic control;Aircraft;aerospace control;Fuzzy systems;fuzzy control;Control design;neural networks;Genetic algorithms
Issue Date: 25-Jul-2004
Publisher: IEEE
Journal Volume: 3
Start page/Pages: 1781-1786
Conference: 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)
Budapest, Hungary
Abstract: 
This work presents three intelligent aircraft automatic landing controllers that use fuzzy system, hybrid fuzzy-neural system and hybrid fuzzy-GA system to improve the performance of a conventional automatic landing system. In this study a multi-layered fuzzy modeling network is used as the controller. Control gains are selected by a combination method of a nonlinear control design, a neural network, and genetic algorithm. Comparisons on different control schemes are given. Simulation results show that the proposed automatic landing controllers can successfully expand the safety envelope of an aircraft to include severe wind disturbance environments without using the conventional gain scheduling technique.
URI: http://scholars.ntou.edu.tw/handle/123456789/18139
DOI: 10.1109/IJCNN.2004.1380878
Appears in Collections:通訊與導航工程學系

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