DocumentCode
425342
Title
Intelligent automatic landing system using fuzzy neural networks and genetic algorithm
Author
Juang, Jih-Gau ; Chin, Kuo-Chih ; Chio, Jem-Zuin
Author_Institution
Dept. of Commun. & Guidance Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan
Volume
6
fYear
2004
fDate
June 30 2004-July 2 2004
Firstpage
5790
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.
Keywords
aerospace simulation; air safety; aircraft landing guidance; control system synthesis; fuzzy control; fuzzy neural nets; genetic algorithms; intelligent control; neurocontrollers; nonlinear control systems; robust control; aircraft safety; control gains; fuzzy neural networks; genetic algorithm; intelligent automatic landing system; nonlinear control design; robustness; software simulation; wind disturbance;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2004. Proceedings of the 2004
Conference_Location
Boston, MA, USA
ISSN
0743-1619
Print_ISBN
0-7803-8335-4
Type
conf
Filename
1384780
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