International Journal of Frontiers in Engineering Technology, 2023, 5(12); doi: 10.25236/IJFET.2023.051215.
Yang Yang, Wei Su
School of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin, 132000, China
An adaptive super-twisting sliding mode control strategy is proposed to solve the problems of quadrotor UAV is easily disturbed by uncertainties in the environment in actual flight. Firstly, aiming at the chattering problem of traditional sliding mode control in the application process, the super-twisting sliding mode control in high-order sliding mode theory was used to weaken the chattering problem of the system. Then, aiming at the parameter adjustment problem of the controller, the adaptive control is used to automatically adjust the controller parameters to realize the trajectory tracking control, and the stability of the controller is proved based on Lyapunov theory. Finally, the simulation results show that the proposed strategy has faster response speed and higher accuracy.
quadrotor UAV; adaptive; super-twisting sliding mode control; trajectory control
Yang Yang, Wei Su. Trajectory Control of Quadrotor UAV Based on Adaptive Super-twisting Sliding Mode. International Journal of Frontiers in Engineering Technology (2023), Vol. 5, Issue 12: 97-105. https://doi.org/10.25236/IJFET.2023.051215.
[1] Idrissi M, Salami M, Annaz F. A review of quadrotor unmanned aerial vehicles: applications, architectural design and control algorithms[J]. Journal of Intelligent & Robotic Systems, 2022, 104(2): 22.08.
[2] Wei Z, Zhu M, Zhang N, et al. UAV-assisted data collection for internet of things: A survey[J]. IEEE Internet of Things Journal, 2022, 9(17): 15460-15483.
[3] Su J, Zhu X, Li S, et al. AI meets UAVs: A survey on AI empowered UAV perception systems for precision agriculture[J]. Neurocomputing, 2023, 518: 242-270.
[4] Brahim K S, El Hajjaji A, Terki N, et al. Finite Time Adaptive SMC for UAV Trajectory Tracking under Unknown Disturbances and Actuators Constraints[J]. IEEE Access, 2023.
[5] ZHAO L, SONG X Y. Backstepping-Based Finite-Time Control for High-Order Discrete-Time Systems [J]. IEEE Transactions on Circuits and Systems II: Express Briefs, 2023, 70(6): 2127-2130.
[6] Lindqvist B, Mansouri S S, Mohammadi A A A, et al. Nonlinear MPC for Collision Avoidance and Control of UAVs with Dynamic Obstacles[J]. IEEE Robotics and Automation Letters, 2020, 5(4): 6001-6008.
[7] Song W, Li Z, Xu B, et al. Research on Improved Control Algorithm of Quadrotor UAV based on Fuzzy PID[C]//2022 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). IEEE, 2022: 361-365.
[8] Antonysamy R P, Lee S R, Jung S Y, et al. Performance Enhancement Using Robust Sliding Mode Approach-Based Current Control for PMVG-WECS[J]. IEEE Transactions on Industrial Electronics, 2022, 70(10): 10156-10166.
[9] Giap V N, Vu H S, Huang S C. Time-varying disturbance observer based on regulating boundary layer thickness sliding mode control for microelectromechanical systems gyroscope[J]. Measurement and Control, 2022, 55(5-6): 247-256.
[10] Cuong V N, Tuan A V, Jun H K. A Finite-Time Fault-Tolerant Control Using Non-Singular Fast Terminal Sliding Mode Control and Third-Order Sliding Mode Observer for Robotic Manipulators[J]. IEEE Access, 2021, 9: 31225 - 31235.
[11] Mahony R, Kumar V, Corke P. Multirotor aerial vehicles: Modeling, estimation, and control of quadrotor [J]. IEEE robotics & automation magazine, 2012, 19(3): 20-32.
[12] Tran X T, Kang H J. A novel adaptive finite-time control method for a class of uncertain nonlinear systems [J]. International Journal of Precision Engineering and Manufacturing, 2015, 16: 2647-2654.