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Research Papers

Geometric Adaptive Tracking Control of a Quadrotor Unmanned Aerial Vehicle on SE(3) for Agile Maneuvers

[+] Author and Article Information
Farhad A. Goodarzi

Department of Mechanical and
Aerospace Engineering,
George Washington University,
Washington, DC 20052
e-mail: fgoodarzi@gwu.edu

Daewon Lee

Department of Mechanical and
Aerospace Engineering,
George Washington University,
Washington, DC 20052
e-mail: daewonlee@gwu.edu

Taeyoung Lee

Assistant Professor
Department of Mechanical and
Aerospace Engineering,
George Washington University,
Washington, DC 20052
e-mail: tylee@gwu.edu

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received November 11, 2014; final manuscript received April 6, 2015; published online June 8, 2015. Assoc. Editor: Jwu-Sheng Hu.

J. Dyn. Sys., Meas., Control 137(9), 091007 (Jun 08, 2015) (12 pages) Paper No: DS-14-1472; doi: 10.1115/1.4030419 History: Received November 11, 2014

This paper presents nonlinear tracking control systems for a quadrotor unmanned aerial vehicle (UAV) under the influence of uncertainties. Assuming that there exist unstructured disturbances in the translational dynamics and the attitude dynamics, a geometric nonlinear adaptive controller is developed directly on the special Euclidean group. In particular, a new form of an adaptive control term is proposed to guarantee stability while compensating the effects of uncertainties in quadrotor dynamics. A rigorous mathematical stability proof is given. The desirable features are illustrated by numerical example and experimental results of aggressive maneuvers.

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Figures

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Fig. 8

Lissajous curve trajectory tracking results (dotted: desired and solid: actual): (a) attitude error variables Ψ, eR, and eΩ, (b) thrust of each rotor (N), (c) position (solid line) and desired (dotted line) x, xd (m), (d) linear velocity (m/s), (e) Eular angles (rad), and (f) angular velocity Ω, Ωd (rad/s)

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Fig. 9

Lissajous curve x–y plane trajectory

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Fig. 2

Flipping without adaptive term (dotted: desired and solid: actual): (a) attitude error function Ψ, (b) thrust at each rotor fi (N), (c) attitude error eR (rad), (d) angular velocity error eΩ (rad/s), (e) angular velocity Ω, Ωd (rad/s), and (f) position x, xd (m)

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Fig. 3

Flipping with adaptive term (dotted: desired and solid: actual): (a) attitude error function Ψ, (b) thrust at each rotor fi (N), (c) attitude error eR (rad), (d) angular velocity error eΩ (rad/s), (e) angular velocity Ω, Ωd (rad/s), and (f) position x, xd (m)

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Fig. 4

Snapshots of a flipping maneuver. The line attached to the quadrotor represents the rotation axis er=[1/2,1/2,0]. The quadrotor UAV rotates about the er axis by 360 deg. The trajectory of its mass center is denoted by dotted lines.

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Fig. 5

Hardware development for a quadrotor UAV: (a) hardware configuration and (b) motor calibration setup

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Fig. 6

Information flow of overall system

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Fig. 10

Flipping flight test results (dotted: desired and solid: actual): (a) attitude error variables Ψ, eR, and eΩ, (b) thrust of each rotor (N), (c) position x, xd (m), (d) linear velocity (m/s), (e) rotation matrix, and (f) angular velocity Ω, Ωd (rad/s)

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Fig. 11

Snapshots for flipping maneuver. A short video of the experiments is available on the ASME Digital Collection under the “Supplemental Data” tab for this paper. (a) t = 0.0 s, (b) t = 0.8756 s, (c) t = 1.008 s, (d) t = 1.079 s, (e) t = 1.125 s, (f) t = 1.175 s, (g) t = 1.844 s, (h) t = 2.312 s, and (i) t = 2.89 s.

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