A Backstepping Sliding Mode Control of a Quadrotor UAV Using a Super-Twisting Observer
Source abstract
Abstract
This study addresses robust trajectory tracking for quadrotor unmanned aerial vehicles (QUAVs) under partial state measurements and bounded external disturbances. To this end, a control framework is introduced that integrates backstepping sliding mode control (BSMC) with a super-twisting observer (STO). In this scheme, only position and attitude are directly measured while the STO reconstructs the linear and angular velocities in real time. The estimated states are then fed into the control law, enabling accurate trajectory tracking and robust performance without full-state feedback or explicit disturbance compensation. The approach is validated through three simulation scenarios: nominal full-state feedback, observer-based control without disturbances, and observer-based control under bounded time-varying perturbations. Quantitative metrics confirm consistent tracking accuracy and closed-loop stability across all scenarios. These results demonstrate the effectiveness of the integrated BSMC–STO framework for QUAV operations in sensor-limited and disturbance-prone environments.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Adaptive Control of Nonlinear Systems · Aerospace Engineering and Control Systems · Vehicle Dynamics and Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Departamento de Ingeniería Electrónica, TecNM-Centro Nacional de Investigación y Desarrollo Tecnológico (CENIDET), Cuernavaca 62490, Morelos, Mexico
References (40)
Show source-provided references
1. Telli, K., Kraa, O., Himeur, Y., Ouamane, A., Boumehraz, M., Atalla, S., and Mansoor, W. (2023). A Comprehensive Review of Recent Research Trends on Unmanned Aerial Vehicles (UAVs). Systems, 11.10.3390/systems11080400 ↗
2. A Review of Quadrotor Unmanned Aerial Vehicles: Applications, Architectural Design and Control Algorithms10.1007/s10846-021-01527-7 ↗
3. Recent Advances in Unmanned Aerial Vehicles: A Review10.1007/s13369-022-06738-0 ↗
4. PID Control of Quadrotor UAVs: A Survey10.1016/j.arcontrol.2023.100900 ↗
5. Rinaldi, M., Primatesta, S., and Guglieri, G. (2023). A Comparative Study for Control of Quadrotor UAVs. Appl. Sci., 13.10.3390/app13063464 ↗
6. Ishibashi, Y., Lichota, P., Jacewicz, M., Yuan, X., Xu, J., and Li, S. (2025). Design and Simulation Verification of Model Predictive Attitude Control Based on Feedback Linearization for Quadrotor UAV. Appl. Sci., 15.10.3390/app15095218 ↗
7. Jiang, B., Li, B., Zhou, W., Lo, L.-Y., Chen, C.-K., Wen, C.-Y., Chahl, J., and Wing, M. (2022). Neural Network Based Model Predictive Control for a Quadrotor UAV. Aerospace, 9.10.3390/aerospace9080460 ↗
8. Adaptive Control of Quadrotor Unmanned Aerial Vehicle with Time-Varying Uncertainties10.1109/ACCESS.2023.3243835 ↗
9. Robust adaptive backstepping fast terminal sliding mode controller for uncertain quadrotor UAV10.1016/j.ast.2019.105306 ↗
10. Thanh, H.L.N.N.N., Huynh, T.T., Vu, M.T., Mung, N.X., Phi, N.N., Hong, S.K., and Vu, T.N.L. (2022). Quadcopter UAVs Extended States/Disturbance Observer-Based Nonlinear Robust Backstepping Control. Sensors, 22.10.3390/s22145082 ↗
11. Design of a Fixed-Wing UAV Controller Based on Adaptive Backstepping Sliding Mode Control Method10.1109/ACCESS.2021.3130296 ↗
12. Borja-Jaimes, V., Coronel-Escamilla, A., Escobar-Jiménez, R.F., Adam-Medina, M., Guerrero-Ramírez, G.V., Sánchez-Coronado, E.M., and García-Morales, J. (2024). Fractional-Order Sliding Mode Observer for Actuator Fault Estimation in a Quadrotor UAV. Mathematics, 12.10.3390/math12081247 ↗
13. Ahn, H., Hu, M., Chung, Y., and You, K. (2023). Sliding-Mode Control for Flight Stability of Quadrotor Drone Using Adaptive Super-Twisting Reaching Law. Drones, 7.10.3390/drones7080522 ↗
14. Higher Order Sliding Mode Controller for a Quadrotor UAV with a Suspended Load10.1016/j.ifacol.2022.04.100 ↗
15. High-Order Sliding Mode Observer-Based Trajectory Tracking Control for a Quadrotor UAV with Uncertain Dynamics10.1007/s11071-020-06050-2 ↗
16. Fixed-Time Distributed Adaptive Formation Control for Multiple QUAVs with Full-State Constraints10.1109/TAES.2023.3237784 ↗
17. Implementation of Super-Twisting Control: Super-Twisting and Higher Order Sliding-Mode Observer-Based Approaches10.1109/TIE.2016.2523913 ↗
18. Attitude Trajectory Tracking of Quadrotor UAV Using Super-Twisting Observer-Based Adaptive Controller10.1177/0954410020966476 ↗
19. Observer-Based Super Twisting Design: A Comparative Study on Quadrotor Altitude Control10.1016/j.isatra.2020.10.026 ↗
20. An adaptive fast super-twisting disturbance observer-based dual closed-loop attitude control with fixed-time convergence for UAV10.1016/j.jfranklin.2022.01.043 ↗
21. Zhang, Y., Fu, Y., Han, Z., and Wang, J. (2025). Super-twisting algorithm backstepping adaptive terminal sliding-mode tracking control of quadrotor drones subjected to faults and disturbances. Drones, 9.10.3390/drones9020082 ↗
22. Adaptive Neural Network-Based Fixed-Time Control for Trajectory Tracking of Robotic Systems
23. Adaptive Disturbance Observer-Based Fixed-Time Tracking Control for Uncertain Robotic Systems10.1109/TIE.2024.3366204 ↗
24. A Novel Faster Fixed-Time Adaptive Control for Robotic Systems With Input Saturation10.1109/TIE.2023.3281701 ↗
25. Adaptive Backstepping and Sliding Mode Control of a Quadrotor10.1007/s40430-024-05188-z ↗
26. Shevidi, A., and Hashim, H.A. (2024). Adaptive Backstepping and Non-Singular Sliding Mode Control for Quadrotor UAVs with Unknown Time-Varying Uncertainties. arXiv, Available online: https://arxiv.org/pdf/2407.07175.10.23919/ACC60939.2024.10644494 ↗
27. Adaptive Backstepping Sliding Mode Control for Quadrotor UAV
28. Li, J., Wan, L., Li, J., and Hou, K. (2023). Adaptive Backstepping Control of Quadrotor UAVs with Output Constraints and Input Saturation. Appl. Sci., 13.10.3390/app13158710 ↗
29. Adaptive Nonsingular Fast Terminal Sliding Mode Control Based Finite-Time Disturbance Observer for a Quadrotor System
30. Path Following of QAUV Using Attitude-Velocity Coupling Model10.1016/j.oceaneng.2024.116885 ↗
31. Hernández-Pérez, M.A., Delgado-Reyes, G., Borja-Jaimes, V., Valdez-Martínez, J.S., and Cervantes-Bobadilla, M. (2023). An Adaptation of a Sliding Mode Classical Observer to a Fractional-Order Observer for Disturbance Reconstruction of a UAV Model: A Riemann–Liouville Fractional Calculus Approach. Mathematics, 11.10.3390/math11244876 ↗
32. Al-Mahturi, A., Santoso, F., Garratt, M.A., and Anavatti, S.G. (2021). Modeling and Control of a Quadrotor Unmanned Aerial Vehicle Using Type-2 Fuzzy Systems. Unmanned Aerial Systems: Theoretical Foundation and Applications, Elsevier. Advances in Nonlinear Dynamics and Chaos (ANDC).10.1016/B978-0-12-820276-0.00009-1 ↗
33. Real-Time Stabilization and Tracking of a Four-Rotor Mini Rotorcraft10.1109/TCST.2004.825052 ↗
34. Dynamic Event-Triggered Robust Optimal Attitude Control of QUAV Using Reinforcement Learning10.1109/TAES.2023.3294893 ↗
35. Madani, T., and Benallegue, A. (2007, January 9–13). Sliding Mode Observer and Backstepping Control for a Quadrotor Unmanned Aerial Vehicles. Proceedings of the American Control Conference, New York, NY, USA.10.1109/ACC.2007.4282548 ↗
36. Generalized Super-Twisting Observer for Nonlinear Systems10.3182/20110828-6-IT-1002.03665 ↗
37. Higher-Order Sliding-Mode Observer for State Estimation and Input Reconstruction in Nonlinear Systems10.1002/rnc.1198 ↗
38. Position and Attitude Control of Multi-Rotor Aerial Vehicles: A Survey10.1016/j.arcontrol.2019.08.004 ↗
39. Appointed Fixed Time Observer-Based Sliding Mode Control for a Quadrotor UAV under External Disturbances10.1109/TAES.2021.3101562 ↗
40. Quadrotor Trajectory Tracking Based on Backstepping Control and Radial Basis Function Neural Networks10.1016/j.rico.2023.100335 ↗