Title :
Development of autonomous flight control systems for unmanned helicopter by use of neural networks
Author :
Nakanishi, Hiroaki ; Inoue, Koichi
Author_Institution :
Dept. of Aeronaut. & Astronaut., Kyoto Univ., Japan
fDate :
6/24/1905 12:00:00 AM
Abstract :
This paper describes approaches to develop command and control systems for unmanned aerial vehicles (UAVs). YAMAHA RMAX, which is an unmanned helicopter, is used in this study. The dynamics of RMAX is nonlinear, so that it is hard to develop autonomous flight control systems, but an efficient method to design controllers by training neural networks is proposed in this paper. Methods to develop controllers for feedback linearization and robust control systems are described and numerical simulations show the effectiveness of our method
Keywords :
aircraft control; feedback; helicopters; learning (artificial intelligence); linearisation techniques; neurocontrollers; robust control; YAMAHA RMAX; autonomous flight control systems; command and control systems; dynamics; feedback; learning algorithm; linearization; neural networks; neurocontrol; robust control; unmanned aerial vehicle; unmanned helicopter; Aerospace control; Command and control systems; Control systems; Design methodology; Helicopters; Linear feedback control systems; Neural networks; Nonlinear control systems; Unmanned aerial vehicles; Vehicle dynamics;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007558
