Research Papers

Robust Attitude Control for Quadrotors Based on Parameter Optimization of a Nonlinear Disturbance Observer

[+] Author and Article Information
Shatadal Mishra

Robotics and Intelligent Systems Laboratory,
The Polytechnic School,
Arizona State University,
Mesa, AZ 85212
e-mail: smishr13@asu.edu

Todd Rakstad

Salt River Project,
P.O. Box 52025,
Phoenix, AZ 85072
e-mail: todd.rakstad@srpnet.com

Wenlong Zhang

Robotics and Intelligent Systems Laboratory,
The Polytechnic School,
Arizona State University,
Mesa, AZ 85212
e-mail: wenlong.zhang@asu.edu

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received December 8, 2017; final manuscript received January 30, 2019; published online March 25, 2019. Assoc. Editor: Yongchun Fang.

J. Dyn. Sys., Meas., Control 141(8), 081003 (Mar 25, 2019) (12 pages) Paper No: DS-17-1608; doi: 10.1115/1.4042741 History: Received December 08, 2017; Revised January 30, 2019

This paper presents a nonlinear disturbance observer (NDOB) for active disturbance rejection in the attitude control loop for quadrotors. An optimization framework is developed for tuning the parameter in the NDOB structure, which includes the infinity-norm minimization of the weighted sum of noise-to-output transfer function and load disturbance sensitivity function. Subsequently, the minimization generates an optimal value of the parameter based on the tradeoff between disturbance rejection and noise propagation in the system. The proposed structure is implemented on PIXHAWK, a real-time embedded flight control unit. Simulation tests are carried out on a custom built, high-fidelity simulator providing physically accurate simulations. Furthermore, experimental flight tests are conducted to demonstrate the performance of the proposed approach. The system is injected with step, sinusoidal, and square wave disturbances, and the corresponding system tracking performance is recorded. Experimental results show that the proposed algorithm attenuates the disturbances better compared to just a baseline controller implementation. The proposed algorithm is computationally cheap, an active disturbance rejection technique and robust to exogenous disturbances.

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Fig. 1

Frames of reference in a quadrotor

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Fig. 2

Work flow of a quadrotor

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Fig. 3

Nonlinear disturbance observer structure

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Fig. 4

System response in the presence of sinusoidal disturbance for different values of λ in simulations

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Fig. 5

System response in the presence of step disturbance for different values of λ in simulations

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Fig. 6

System response in the presence of square wave disturbance for different values of λ in simulations

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Fig. 7

A DJI F330 quadrotor used in experiments

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Fig. 8

Roll angle responses with sinusoidal disturbances for different values of λ in experiments

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Fig. 9

Roll angle responses with step disturbances for different values of λ in experiments

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Fig. 10

Roll angle responses with square wave disturbances for different values of λ in experiments

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Fig. 11

Roll angle responses to step disturbance while flying with baseline control and NDOB in experiments



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