为了降低机器人系统中各种不确定因素对控制系统的影响，提出了自适应神经网络反演控制方法。该控制方法基于反演设计方法，解决了系统的非匹配不确定性；引入了神经网络自适应控制律和鲁棒控制律，并适当调整控制器参数，实现了无需机器人精确模型信息的控制，也保证了系统的稳定性和收敛性，满足了机器人系统的控制要求。仿真实验验证了该控制方法的有效性。

A neural networks adaptive back stepping control method was put forward to reduce the influence of all kinds of uncertain factors on robot control system. The control method was based on back stepping and solved mismatched uncertainties of robotic system. Through introduction of neural network adaptive control law and robust control law, and adjusting the controller parameters appropriately, the control could be realized without accurate model of robot. The stability and convergence of the system were also proved and the control requirements of robotic system were met. The effectiveness of the control method was validated by simulation experiments.