Robust Adaptive Sliding Mode Control Based on Iterative Learning for Quadrotor UAV

Abstract

In order to improve the anti-disturbance ability and reduce the sensitivity to faults for the quadrotor UAV, the robust sliding mode adaptive control strategy based on iterative learning is designed in this paper. Firstly, the dynamic model of the quadrotor UAV is established. Secondly, the iterative learning observer is designed to track the states of the UAV system, and the convergence analysis of the observer is given. Thirdly, for the attitude system of the quadrotor UAV, a robust adaptive sliding mode control strategy based on iterative learning is proposed, and the stability is proved by the Lyapunov theory. Finally, by the simulation for the UAV attitude system, the validity of the iterative learning observer and robust adaptive sliding mode control strategy based on iterative learning is verified.

KEYWORDS:

• Fault-tolerant control
• Iterative learning
• Observer
• Quadrotor UAV
• Robust adaptive control
• Sliding mode control

ACKNOWLEDGEMENTS

This work is supported by the National Natural Science Foundation of China under grant 61573230, and supported by Research Development Project of Beijing Information Science and Technology University under grant 5211910950.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Natural Science Foundation of China: [grant number 61573230].

Notes on contributors

Xingjian Fu

Xingjian Fu received the PhD degree in School of Automation, University of Science and Technology Beijing, China, in 2005. Currently, he is an associate professor at Beijing Information Science and Technology University. He has published about 80 journal related and conference papers. He was supported by the High-Caliber Young Talents Project of Beijing Municipal Education Commission in 2014. He is a committee member of the Mechanical Industry Automation Branch of the China Mechanical Engineering Society, a member of the China Automation Society. His research interests include intelligent control, robust fault-tolerant control and motion body control.

Jiahui He

Jiahui He received the BSc degree in School of Automation, University of Science and Technology Beijing, China, in 2018. He is currently a postgraduate student in School of Automation, Beijing Information Science and Technology University, China. His research interests include ILC, UAVs. Email: [email protected]