Development and application analysis of the quadrotor UAV’s attitude control

Research Article
Open access

Development and application analysis of the quadrotor UAV’s attitude control

Shuaiwen Diao 1*
  • 1 Shenyang Aerospace University    
  • *corresponding author diaoshuaiwen@stu.sau.edu.cn
Published on 25 September 2023 | https://doi.org/10.54254/2755-2721/9/20230017
ACE Vol.9
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-007-3
ISBN (Online): 978-1-83558-008-0

Abstract

Due to the economy's tremendous growth and the technology's impressive advancement, the practicality of UAVs has become a hot topic of concern for all sectors of society at present. According to the classification of flight platform configuration, drones may be split into many different types. Quadrotor drones are a common type of aerial robot, which is widely used in civilian and military fields at this stage. The safety and stability of the UAV in use are particularly important, so its flight attitude must be humanly tuned and controlled. This paper mainly analyzes the attitude control technology of quadrotor UAVs. Firstly, the key components and technical difficulties of attitude control are analyzed. Then some common control methods and application scenarios of current mainstream control methods are introduced and analyzed in detail. Finally, future research directions are analyzed and summarized based on the existing methods.

Keywords:

quadrotor drones, attitude control, application scenarios, future research directions.

Diao,S. (2023). Development and application analysis of the quadrotor UAV’s attitude control. Applied and Computational Engineering,9,7-14.
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References

[1]. B. Tian, L. Liu, H. Lu, Z. Zuo, Q. Zong and Y. Zhang, "Multivariable Finite Time Attitude Control for Quadrotor UAV: Theory and Experimentation," in IEEE Transactions on Industrial Electronics, vol. 65, no. 3, pp. 2567-2577, March 2018, doi: 10.1109/TIE.2017.2739700.

[2]. K. U. Lee, Y. H. Yun, W. Chang, J. B. Park and Y. H. Choi, "Modeling and altitude control of quad-rotor UAV," 2011 11th International Conference on Control, Automation and Systems, Gyeonggi-do, Korea (South), 2011, pp. 1897-1902.

[3]. Z. Ma and S. M. Jiao, "Research on the attitude control of quad-rotor UAV based on active disturbance rejection control," 2017 3rd IEEE International Conference on Control Science and Systems Engineering (ICCSSE), Beijing, China, 2017, pp. 45-49, doi: 10.1109/CCSSE.2017.8087892.

[4]. Qiang Gao, Xinpeng Liu, Chunping Liu, Yuehui Ji, Junjie Liu, Quadrotor UAV tandem-level self-anti-disturbance attitude control and trajectory tracking [J/OL]. Electro-Optics and Control.

[5]. W. Qingtong, W. Honglin, W. Qingxian and C. Mou, "Backstepping-based attitude control for a quadrotor UAV using nonlinear disturbance observer," 2015 34th Chinese Control Conference (CCC), Hangzhou, China, 2015, pp. 771-776, doi: 10.1109/ChiCC.2015.7259733.

[6]. Sadeghzadeh,I., Mehta, A. ., Zhang, . Y., & Rabbath, C.-A. . (2011). Fault-Tolerant Trajectory Tracking Control of a Quadrotor Helicopter Using Gain-Scheduled PID and Model Reference Adaptive Control. Annual Conference of the PHM Society, 3(1).

[7]. N. P. Nguyen, N. X. Mung, H. L. N. N. Thanh, T. T. Huynh, N. T. Lam and S. K. Hong, "Adaptive Sliding Mode Control for Attitude and Altitude System of a Quadcopter UAV via Neural Network," in IEEE Access, vol.9,pp.40076-40085,2021, doi:10.1109/ACCESS.2021.3064883.

[8]. Jiang Feng, Hui Zhang, Xihai Zhang, Research on attitude control of plant protection UAV based on backstepping sliding mode algorithm[J]. Journal of Northeast Agricultural University, 2022, 53(1): 55-65. DOI: 10.19720/j.cnki.issn.1005-9369.2022.01.007.

[9]. B. -Y. Lee, H. -I. Lee and M. -J. Tahk, "Analysis of adaptive control using on-line neural networks for a quadrotor UAV," 2013 13th International Conference on Control, Automation and Systems (ICCAS 2013), Gwangju, Korea (South), 2013, pp. 1840-1844, doi: 10.1109/ICCAS.2013.6704240.

[10]. Razmi, H., & Afshinfar, S. (2019). Neural network-based adaptive sliding mode control design for position and attitude control of a quadrotor UAV. Aerospace Science and technology, 91, 12-27.

[11]. Cheema, P., Luo, S., & Gibbens, P. (2016). Development of a Control and Vision Interface for an AR. Drone. In MATEC Web of Conferences (Vol. 56, p. 07002). EDP Sciences.

Cite this article

Diao,S. (2023). Development and application analysis of the quadrotor UAV’s attitude control. Applied and Computational Engineering,9,7-14.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Mechatronics and Smart Systems

ISBN：978-1-83558-007-3(Print) / 978-1-83558-008-0(Online)
Editor：Seyed Ghaffar, Alan Wang
Conference website: https://2023.confmss.org/
Conference date: 24 June 2023
Series: Applied and Computational Engineering
Volume number: Vol.9
ISSN：2755-2721(Print) / 2755-273X(Online)

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References

[1]. B. Tian, L. Liu, H. Lu, Z. Zuo, Q. Zong and Y. Zhang, "Multivariable Finite Time Attitude Control for Quadrotor UAV: Theory and Experimentation," in IEEE Transactions on Industrial Electronics, vol. 65, no. 3, pp. 2567-2577, March 2018, doi: 10.1109/TIE.2017.2739700.

[2]. K. U. Lee, Y. H. Yun, W. Chang, J. B. Park and Y. H. Choi, "Modeling and altitude control of quad-rotor UAV," 2011 11th International Conference on Control, Automation and Systems, Gyeonggi-do, Korea (South), 2011, pp. 1897-1902.

[3]. Z. Ma and S. M. Jiao, "Research on the attitude control of quad-rotor UAV based on active disturbance rejection control," 2017 3rd IEEE International Conference on Control Science and Systems Engineering (ICCSSE), Beijing, China, 2017, pp. 45-49, doi: 10.1109/CCSSE.2017.8087892.

[4]. Qiang Gao, Xinpeng Liu, Chunping Liu, Yuehui Ji, Junjie Liu, Quadrotor UAV tandem-level self-anti-disturbance attitude control and trajectory tracking [J/OL]. Electro-Optics and Control.

[5]. W. Qingtong, W. Honglin, W. Qingxian and C. Mou, "Backstepping-based attitude control for a quadrotor UAV using nonlinear disturbance observer," 2015 34th Chinese Control Conference (CCC), Hangzhou, China, 2015, pp. 771-776, doi: 10.1109/ChiCC.2015.7259733.

[6]. Sadeghzadeh,I., Mehta, A. ., Zhang, . Y., & Rabbath, C.-A. . (2011). Fault-Tolerant Trajectory Tracking Control of a Quadrotor Helicopter Using Gain-Scheduled PID and Model Reference Adaptive Control. Annual Conference of the PHM Society, 3(1).

[7]. N. P. Nguyen, N. X. Mung, H. L. N. N. Thanh, T. T. Huynh, N. T. Lam and S. K. Hong, "Adaptive Sliding Mode Control for Attitude and Altitude System of a Quadcopter UAV via Neural Network," in IEEE Access, vol.9,pp.40076-40085,2021, doi:10.1109/ACCESS.2021.3064883.

[8]. Jiang Feng, Hui Zhang, Xihai Zhang, Research on attitude control of plant protection UAV based on backstepping sliding mode algorithm[J]. Journal of Northeast Agricultural University, 2022, 53(1): 55-65. DOI: 10.19720/j.cnki.issn.1005-9369.2022.01.007.

[9]. B. -Y. Lee, H. -I. Lee and M. -J. Tahk, "Analysis of adaptive control using on-line neural networks for a quadrotor UAV," 2013 13th International Conference on Control, Automation and Systems (ICCAS 2013), Gwangju, Korea (South), 2013, pp. 1840-1844, doi: 10.1109/ICCAS.2013.6704240.

[10]. Razmi, H., & Afshinfar, S. (2019). Neural network-based adaptive sliding mode control design for position and attitude control of a quadrotor UAV. Aerospace Science and technology, 91, 12-27.

[11]. Cheema, P., Luo, S., & Gibbens, P. (2016). Development of a Control and Vision Interface for an AR. Drone. In MATEC Web of Conferences (Vol. 56, p. 07002). EDP Sciences.

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