Keywords
Unmmaned aerial vehicle, uav, path planning, dynamic inversion, nonlinear autopilot
Abstract
The role of the unmanned aerial vehicle (UAV) has significantly expanded in the military sector during the last decades mainly due to their cost effectiveness and their ability to eliminate the human life risk. Current UAV technology supports a variety of missions and extensive research and development is being performed to further expand its capabilities. One particular field of interest is the area of the low cost expendable UAV since its small price tag makes it an attractive solution for target suppression. A swarm of these low cost UAVs can be utilized as guided munitions or kamikaze UAVs to attack multiple targets simultaneously. The focus of this thesis is the development of a cooperative online path planning algorithm that coordinates the trajectories of these UAVs to achieve a simultaneous arrival to their dynamic targets. A nonlinear autopilot design based on the dynamic inversion technique is also presented which stabilizes the dynamics of the UAV in its entire operating envelope. A nonlinear high fidelity six degrees of freedom model of a fixed wing aircraft was developed as well that acted as the main test platform to verify the performance of the presented algorithms.
Notes
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Graduation Date
2012
Semester
Fall
Advisor
Qu, Zhihua
Degree
Master of Science in Electrical Engineering (M.S.E.E.)
College
College of Engineering and Computer Science
Department
Electrical Engineering and Computing
Degree Program
Electrical Engineering; Controls and Robotics
Format
application/pdf
Identifier
CFE0004613
URL
http://purl.fcla.edu/fcla/etd/CFE0004613
Language
English
Release Date
December 2012
Length of Campus-only Access
None
Access Status
Masters Thesis (Open Access)
Subjects
Dissertations, Academic -- Sciences, Sciences -- Dissertations, Academic
STARS Citation
Vega-Nevarez, Juan, "Online Path Planning And Control Solution For A Coordinated Attack Of Multiple Unmanned Aerial Vehicles In A Dynamic Environment" (2012). Electronic Theses and Dissertations. 2430.
https://stars.library.ucf.edu/etd/2430