Based on Backpropagation Neural Network and Adaptive Linear Active Disturbance Rejection Control for Attitude of a Quadrotor Carrying a Load

Abstract

A control method combining Backpropagation (BP) neural network and Adaptive Linear Active Disturbance Rejection Control (ALADRC) is proposed for the attitude control problem of quadrotor aircraft. The proposed controller can observe and compensate the total disturbance in the working process of the quadrotor system. At the same time, it has a good ability to suppress the disturbance of the quadrotor load mass change. In addition, adaptive control and BP neural network are used to adjust the controller parameters in real time to solve the problem of difficult parameter tuning. Finally, the stability of the system is proved based on Lyapunov theory. The simulation results show that the quadrotor system can still track the altitude and attitude angle commands stably in the presence of disturbances, and has strong adaptability to load mass changes, so that the quadrotor can still complete the given tasks in the presence of multi-source disturbances.

Keywords

• Backpropagation neural network
• attitude control
• total disturbance
• adaptive control
• parameter tuning