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Proceedings Paper

Neural-network-based navigation and control of unmanned aerial vehicles for detecting unintended emissions
Author(s): H. Zargarzadeh; David Nodland; V. Thotla; S. Jagannathan; S. Agarwal
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Paper Abstract

Unmanned Aerial Vehicles (UAVs) are versatile aircraft with many applications, including the potential for use to detect unintended electromagnetic emissions from electronic devices. A particular area of recent interest has been helicopter unmanned aerial vehicles. Because of the nature of these helicopters' dynamics, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via output feedback control for trajectory tracking of a helicopter UAV using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic, virtual, and dynamic controllers and an observer. Optimal tracking is accomplished with a single NN utilized for cost function approximation. The controller positions the helicopter, which is equipped with an antenna, such that the antenna can detect unintended emissions. The overall closed-loop system stability with the proposed controller is demonstrated by using Lyapunov analysis. Finally, results are provided to demonstrate the effectiveness of the proposed control design for positioning the helicopter for unintended emissions detection.

Paper Details

Date Published: 24 May 2012
PDF: 11 pages
Proc. SPIE 8387, Unmanned Systems Technology XIV, 83870H (24 May 2012); doi: 10.1117/12.919355
Show Author Affiliations
H. Zargarzadeh, Missouri Univ. of Science and Technology (United States)
David Nodland, Missouri Univ. of Science and Technology (United States)
V. Thotla, Missouri Univ. of Science and Technology (United States)
S. Jagannathan, Missouri Univ. of Science and Technology (United States)
S. Agarwal, U.S. Army Night Vision & Electronic Sensors Directorate (United States)

Published in SPIE Proceedings Vol. 8387:
Unmanned Systems Technology XIV
Robert E. Karlsen; Douglas W. Gage; Charles M. Shoemaker; Grant R. Gerhart, Editor(s)

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