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Research Papers

Nonlinear Control of a Quadrotor With Deviated Center of Gravity

[+] Author and Article Information
Bin Xian

Professor
Mem. ASME
School of Electrical Engineering
and Automation,
Tianjin University,
Tianjin 30072, China
e-mail: xbin@tju.edu.cn

Bo Zhao, Yao Zhang, Xu Zhang

School of Electrical Engineering
and Automation,
Tianjin University,
Tianjin 30072, China

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received December 19, 2015; final manuscript received July 19, 2016; published online September 9, 2016. Assoc. Editor: Yongchun Fang.

J. Dyn. Sys., Meas., Control 139(1), 011003 (Sep 09, 2016) (8 pages) Paper No: DS-15-1642; doi: 10.1115/1.4034366 History: Received December 19, 2015; Revised July 19, 2016

In this paper, a new adaptive tracking controller is developed for a quadrotor unmanned aerial vehicle (UAV) via immersion and invariance (I&I) approach. The controller is able to compensate parametric uncertainties such as the unmeasurable effects of the deviated center-of-gravity (CoG), as well as the aerodynamic coefficients. The globally asymptotic tracking of the desired attitude trajectories is proven via the Lyapunov-based stability analysis and LaSalle's invariance theorem. Real-time experiment results performed on a quadrotor attitude control testbed are given to show the good control performance of the proposed scheme.

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References

Figures

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Fig. 1

The coordinate system of the quadrotor UAV

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Fig. 2

A snapshot of the quadrotor UAV attitude control testbed

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Fig. 3

Simulink block diagram of the quadrotor control system

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Fig. 4

Desired attitude (ϕd,θd,ψd) and actual attitude (ϕ,θ,ψ) in case 1

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Fig. 5

Angular velocities (Ω1,Ω2,Ω3) in case 1

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Fig. 6

Partially zoomed-in details of the attitude angles in case 1 (from 50 s to 110 s)

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Fig. 7

Control input signals (τ1,τ2,τ3) in case 1

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Fig. 8

Motor speed (ω1,ω2,ω3,ω4) in case 1

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Fig. 9

Parameters estimation for ŝ1 in case 1

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Fig. 10

Parameters estimation for ŝ2 in case 2

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Fig. 11

Desired attitude (ϕd,θd,ψd) and actual attitude (ϕ,θ,ψ) in case 2

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Fig. 12

Angular velocities (Ω1,Ω2,Ω3) in case 2

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Fig. 13

Control input signals (τ1,τ2,τ3) in case 2

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Fig. 14

Motor speed (ω1,ω2,ω3,ω4) in case 2

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Fig. 15

Parameters estimation for ŝ1 in case 2

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Fig. 16

Parameters estimation for ŝ2 in case 2

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