Robust adaptive backstepping sliding mode attitude control of quadrotor UAV based on RBF network
The robust backstepping sliding mode RBF network adaptive controller was proposed for the quadrotor unmanned aerial vehicle(UAV)attitude system with disturbance.Based on the backstepping sliding mode control,the RBF network was used to approximate and compensate the ideal control law.The minimum parameter learning method of the neural network was adopted,and the weight upper bound of the neural network was estimated as estimated value of the neural network.The adaptation law was used to replace the adjustment of neural network weights,and Lyapunov theorem was used to prove the stability of system.The simulation results show that compared with the backstepping sliding mode control method,the proposed method has shorter adjustment time and better tracking accuracy in the case of disturbance.It is verified that the proposed method has better anti-interference and robustness.
万方数据
维普
