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

Sun, Yue

Permalink

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

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

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

Owning Collections