四旋翼姿态的反步滑模RBF网络自适应控制

Backstepping Sliding Mode RBF Network Adaptive Attitude Control for Quadrotor Unmanned Aerial Vehicle

针对外界存在常值干扰力矩和变值干扰力矩的四旋翼无人机姿态系统,提出一种将反步滑模控制和RBF网络自适应算法相结合的控制方法。此方法在反步滑模控制方法的基础上,利用RBF网络的逼近特性补偿外界干扰,由Lyapunov方法构造RBF网络权值的自适应律,并通过Lyapunov稳定性定理证明四旋翼无人机姿态系统的稳定性。仿真结果表明,当外界存在常值干扰力矩和变值干扰力矩时,相比于反步滑模控制,该控制方法随外界干扰的波动范围更小,误差和超调量更小,验证了反步滑模RBF网络自适应控制方法抑制干扰的能力更强。

For the quadrotor unmanned aerial vehicle system with constant interference torque and variable value interference torque,a control method is put forward combining the backstepping sliding mode control method with the RBF network adaptive algorithm.Based on the backstepping sliding mode control method,RBF network approximation feature is used to compensate for external disturbances.The Lyapunov method is used to construct the adaptive law of RBF network weights,and the stability of quadrotor unmanned aerial vehicle attitude system is proved by Lyapunov stability theorem.Through simulation experiments,the results show that when there is constant interference torque and variable value interference torque,compared with the backstepping sliding mode control,the control method of this paper has smaller fluctuation range with external interference,and the error and overshoot are smaller.It is verified that the backstepping sliding mode RBF network adaptive control method has stronger ability in interference suppression.