Title :
Intelligent landing control based on neural-fuzzy-GA hybrid system
Author :
Juang, Jih-Gau ; Chin, Kuo-Chih
Author_Institution :
Dept. of Commun. & Guidance Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan
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.
Keywords :
aircraft control; control system synthesis; fuzzy control; fuzzy systems; genetic algorithms; intelligent control; multilayer perceptrons; neurocontrollers; nonlinear control systems; automatic landing system; gain scheduling technique; genetic algorithm; intelligent aircraft automatic landing controllers; multilayered fuzzy modeling network; neural fuzzy GA hybrid system; neural network; nonlinear control design; safety envelope; Aerospace control; Aircraft; Automatic control; Control design; Control systems; Fuzzy control; Fuzzy systems; Genetic algorithms; Intelligent control; Neural networks;
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
Print_ISBN :
0-7803-8359-1
DOI :
10.1109/IJCNN.2004.1380878