Direct Inverse Control using an Artificial Neural Network for the Autonomous Hover of a Helicopter

Author

Frye, M.T. ; Provence, R.S.

Author_Institution

Dept. of Eng., Univ. of the Incarnate Word, San Antonio, TX, USA

fYear

2014

fDate

5-8 Oct. 2014

Firstpage

4121

Lastpage

4122

Abstract

This paper presents the initial results of a research project which investigates the application of the Direct Inverse Control technique to the problem of the Autonomous Hover of a quadrotor UAV Helicopter. The goal of the project is to investigate the effectiveness of the Direct Inverse Control technique using an Artificial Neural Network to learn and then cancel out the Hover dynamics of the quadrotor UAV Helicopter under various environmental conditions during a hover mode. The project is to evaluate how robust the control technique is to uncertainty and change in nonlinear dynamics.

Keywords

aircraft control; autonomous aerial vehicles; helicopters; mobile robots; neurocontrollers; robot dynamics; robust control; vehicle dynamics; artificial neural network; autonomous helicopter hover; direct inverse control; nonlinear dynamics; quadrotor UAV helicopter hover dynamics; robust control; Aerodynamics; Aerospace control; Artificial neural networks; Helicopters; Nonlinear dynamical systems; Robustness; Vehicle dynamics; Direct Inverse Control; Flight Control; Neural Network; UAV helicopter;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on

Conference_Location

San Diego, CA

Type

conf

DOI

10.1109/SMC.2014.6974581

Filename

6974581