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

Volume

3

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

2626

Lastpage

2631

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on

Conference_Location

Honolulu, HI

ISSN

1098-7576

Print_ISBN

0-7803-7278-6

Type

conf

DOI

10.1109/IJCNN.2002.1007558

Filename

1007558