In this paper, a neuro-sliding mode controller (SMC) has been designed for a quadrotor transporting a suspended payload. SMCs are very efficient under uncertain conditions. However, if the uncertain dynamics change over time, SMC gains need to be updated to maintain the tracking performance. This study proposes a neuro-SMC to control a quadrotor UAV carrying a suspended payload in the existence of time-varying uncertain dynamics. Once the accuracy of the proposed controller is demonstrated theoretically using the Lyapunov stability criterion, the effectiveness of the proposed controller is shown in simulation, which confirms the theoretical claims.

在本文中，神经滑模控制器（SMC）已被设计用于四旋翼飞机运输悬浮的有效载荷。SMC在不确定条件下非常有效。但是，如果不确定的动力学随时间变化，则需要更新SMC增益以保持跟踪性能。这项研究提出了一种神经SMC，用于在存在时变不确定动力学的情况下控制带有悬浮有效载荷的四旋翼无人机。一旦使用Lyapunov稳定性标准在理论上证明了所提出控制器的精度，则在仿真中就表明了所提出控制器的有效性，这证实了理论上的主张。