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
fDate :
June 30 2004-July 2 2004
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;
Conference_Titel :
American Control Conference, 2004. Proceedings of the 2004
Conference_Location :
Boston, MA, USA
Print_ISBN :
0-7803-8335-4