Adaptive Sliding Mode Control for Attitude and Altitude System of a Quadcopter UAV via Neural Network

IEEE Access

Ngoc Phi Nguyen¹  Nguyen Xuan Mung¹  Sung Kyung Hong¹  Tuan Tu Huynh²  Ha Le Nhu Ngoc Thanh³  Ngoc Tam Lam⁴ 

[1] Department of Aerospace Engineering, Sejong University, Seoul, South Korea;Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan;HUTECH Institute of Engineering, Ho Chi Minh City University of Technology, Ho Chi Minh, Vietnam;School of Civil and Mechanical Engineering, Curtin University, Perth, WA, Australia;

关键词: Adaptive sliding mode;    neural networks;    quadrotor;    backpropagation;   

DOI  :  10.1109/ACCESS.2021.3064883

来源: DOAJ

【 摘 要 】

In this article, a sliding mode control based on neural networks is proposed for attitude and altitude system of quadcopter under external disturbances. First, the dynamic model of the quadcopter is considered under external disturbances. Sliding mode controllers are then integrated with neural network algorithm to achieve the time-varying sliding surface; their coefficients in sliding surface are adjusted through backpropagation law. The disturbance observer is also combined with sliding mode controllers to estimate and handle the external disturbances. Finally, the Lyapunov theory is applied to validate the stability of suggested control method. The performance of proposed sliding mode control has been evaluated using a numerical simulation. The results show that the attitude and altitude controller based on suggested algorithm has a better tracking performance and disturbance rejection.

【 授权许可】

Unknown