Robust fuzzy-logic flight control for unmanned aerial vehicles (UAVs)

Authors

DOI:

https://doi.org/10.58190/ijamec.2024.79

Keywords:

Fuzzy Control, Quadrotors, UAVs, Robustness

Abstract

Researches on Unmanned Aerial Vehicles (UAVs) have been recently attracting considerable interest in the field of control theory applications. They are used in a wide range of areas thanks to having the potential of high manoeuvrability, hovering and flying, taking off and landing capabilities. However, to maintain robust control action towards changing conditions of the system is not an easy matter since quadrotor UAVs are highly unstable systems with high precision. Therefore, the main purpose of this study is to control a quadrotor UAV by using a proposed multi-input single-output (MISO) fuzzy-logic controller that ensures robustness if model parameters and trajectory change. For that reason, a 2-dimensional 3 degree-of-freedom quadrotor was used in this study to better evaluate the performance of proposed controller on UAVs. Afterwards, numerical analysis was performed and the findings were analysed. Consequently, the single most striking observation to emerge from the study is that the satisfactory results have been obtained demonstrating that the proposed fuzzy logic controller has remarkable advantage on the robustness of quadrotor UAVs.

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References

A. Agrawal, N. Bucki, P. Kotaru, D. Meister, and M. Xu, “Obstacle Avoidance for 2D Quadrotor with Hanging Load,” Accessed: Mar. 30, 2023. [Online]. Available: https://youtu.be/BfGQMpfwSIc.

C. Nimbargi, Y. Mane, and N. Lokhande, “Control of Quadrotor in 2-D for a Commanded Trajectory,” 2022 2nd Asian Conf. Innov. Technol. ASIANCON 2022, 2022, doi: 10.1109/ASIANCON55314.2022.9909194.

M. Santos, V. López, and F. Morata, “Intelligent fuzzy controller of a quadrotor,” Proc. 2010 IEEE Int. Conf. Intell. Syst. Knowl. Eng. ISKE 2010, pp. 141–146, 2010, doi: 10.1109/ISKE.2010.5680812.

P. Bai, B. Guerreiro, R. Cunha, P. Kornatowski, D. Floreano, and C. Silvestre, “Wall-contact sliding control strategy for a 2D caged quadrotor,” 2018 18th Int. Conf. Control. Autom. Syst., 2018.

C. Li, Y. Wang, and X. Yang, “Adaptive fuzzy control of a quadrotor using disturbance observer,” Aerosp. Sci. Technol., vol. 128, p. 107784, Sep. 2022, doi: 10.1016/J.AST.2022.107784.

A. Iyer and H. O. Bansal, “Modelling, Simulation, and Implementation of PID Controller on Quadrotors,” 2021 Int. Conf. Comput. Commun. Informatics, ICCCI 2021, Jan. 2021, doi: 10.1109/ICCCI50826.2021.9402301.

J. Escareño, S. Salazar, H. Romero, and R. Lozano, “Trajectory control of a quadrotor subject to 2D wind disturbances: Robust-adaptive approach,” J. Intell. Robot. Syst. Theory Appl., vol. 70, no. 1–4, pp. 51–63, Apr. 2013, doi: 10.1007/S10846-012-9734-1/METRICS.

B. E. Demir, R. Bayir, and F. Duran, “Real-time trajectory tracking of an unmanned aerial vehicle using a self-tuning fuzzy proportional integral derivative controller,” Int. J. Micro Air Veh., vol. 8, no. 4, pp. 252–268, Dec. 2016, doi: 10.1177/1756829316675882/ASSET/IMAGES/LARGE/10.1177_1756829316675882-FIG2.JPEG.

A. Prayitno, V. Indrawati, and G. Utomo, “Trajectory Tracking of AR.Drone Quadrotor Using Fuzzy Logic Controller,” TELKOMNIKA (Telecommunication Comput. Electron. Control., vol. 12, no. 4, pp. 819–828, Nov. 2014, doi: 10.12928/TELKOMNIKA.V12I4.368.

V. S. Fnu, “Autonomous Control of a Quadrotor UAV using Fuzzy Logic,” 2015, doi: 10.21535/PROICIUS.2013.V9.230.

M. F. Q. Say, E. Sybingco, A. A. Bandala, R. R. P. Vicerra, and A. Y. Chua, “2D Position Control of a UAV Using Fuzzy Logic Control,” 2021 IEEE/SICE Int. Symp. Syst. Integr. SII 2021, pp. 679–683, Jan. 2021, doi: 10.1109/IEEECONF49454.2021.9382784.

V. Desh, “MATLAB & Simulink Tutorial: Quadrotor UAV Trajectory and Control Design (PID + Cascaded) - YouTube.” https://www.youtube.com/watch?v=iS5JFuopQsA&list=PLlIRr36VdiM_Ja6tr91mk_ZQF6ATvVRXP&index=26&t=4s (accessed Mar. 31, 2023).

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Published

27-03-2024

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Section

Research Articles

How to Cite

[1]
“Robust fuzzy-logic flight control for unmanned aerial vehicles (UAVs)”, J. Appl. Methods Electron. Comput., vol. 12, no. 1, pp. 16–21, Mar. 2024, doi: 10.58190/ijamec.2024.79.