NDLI: Fractional order robust visual servoing control of a quadrotor UAV with larger sampling period

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Fractional order robust visual servoing control of a quadrotor UAV with larger sampling period

Content Provider	Semantic Scholar
Author	Shang, Bo Liu, Jianxin Zhao, Tiebiao Chen, Yangquan
Copyright Year	2016
Abstract	Unmanned aerial vehicles (UAVs) are widely applied in both civil and military fields, such as rescue, surveillance, exploration, navigation, precision agriculture and etc., because of small size, low cost and easy maintenance. However the autonomous flight of UAVs under unstructured environment is still open, especially when GPS is unavailable or indoor task is scheduled. Furthermore, GPS-based navigation accuracy needs to be improved. To deal with these limitations, in this paper, we provide an engineering-oriented solution of precise hovering based on visual servoing and fractional order proportional-integral-derivative (PID) controller without GPS information. First, the mathematical speed model of a quadcopter is obtained by step response experiments. Then, fractional order PID controller algorithm is designed to improve its hovering accuracy and robustness. In our work, the position reference is extracted with an on-board color based target recognition algorithm instead of GPS. Both simulation and field experimental results demonstrate that the proposed scheme can achieve a better performance in terms of hovering accuracy and robustness to disturbances. In particular, for the first time, we show that, the sampling period can be bigger than usual when using fractional order control algorithm, relaxing costly hardware requirement for fast real-time vision-based feedback.
Starting Page	1228
Ending Page	1234
Page Count	7
File Format	PDF HTM / HTML
DOI	10.1109/ICUAS.2016.7502645
Alternate Webpage(s)	http://mechatronics.ucmerced.edu/sites/mechatronics.ucmerced.edu/files/page/documents/as4006299660984321472529035373_content_1.pdf
Journal	2016 International Conference on Unmanned Aircraft Systems (ICUAS)
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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