University of Illinois Urbana-Champaign

Modeling, identification and control of a quad-rotor drone using low-resolution sensing

Sun, Yue

Content Files
SUN_YUE.pdf

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https://hdl.handle.net/2142/34205

Description

Title
Modeling, identification and control of a quad-rotor drone using low-resolution sensing
Author(s)
Sun, Yue
Issue Date
2012-09-18T21:05:49Z
Director of Research (if dissertation) or Advisor (if thesis)
Dullerud, Geir E.
Department of Study
Mechanical Sci & Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2012-09-18T21:05:49Z
Keyword(s)
  • Modeling
  • Identification
  • Control
  • quadrotor
  • AR.Drone
Abstract
This thesis focuses on the modeling and identification, control and filter design, simulation and animation, and experiments of an electrical-motor drive model-scale quadrotor --- the AR.Drone. Equations of Motion of drone’s model were derived from Kinemics and Dynamics of common quadrotors. The identification was conducted thoroughly including its low-resolution on-board sensors, such as rate gyro and altimeter. Control targets are composed of two stages --- local references following and global position tracking. PID algorithm is used by both controllers with various filters designs, such as low/high pass filter, Complementary Filter and Kalman Filter. Simulation is also divided to two stages with two different simulators ---- MATLAB and C++. The first stage MATLAB simulation is intended to only test the controllers with no disturbances or noises. The second stage high fidelity C++ simulation contains everything including animation. Experiments results are presented and correlated to simulation to evaluate the identification and modeling. This thesis also includes modeling and identification of a low-resolution camera sensor --- Kinect. The model is included in global position tracking simulation. Some experiments videos and animation videos are available at http://www.youtube.com/user/sunyue89/videos. The author hopes this thesis is helpful to researchers and amateurs who would like to develop the AR.Drone or any other small scale quadrotors using low-resolution sensing for autonomous control.
Graduation Semester
2012-08
Permalink
http://hdl.handle.net/2142/34205
Copyright and License Information
Copyright 2012 Yue Sun

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