针对一类带有未知非线性函数的严格反馈非线性时滞系统,设计了一种自适应神经网络控制器.选择径向基函数神经网络逼近未知的非线性函数.所提出的控制方案能保证闭环系统的所有信号是全局一致最终有界的.证明了跟踪误差信号将收敛于一个小紧集内.仿真实例验证了所提出方法的有效性. For a class of strictly feedback nonlinear time-delay systems with unknown nonlinear functions, an adaptive neural network controller is designed. The radial basis function neural network is chosen to approximate an unknown nonlinear function. The proposed control scheme can guarantee All the signals of the closed-loop system are globally uniform and ultimately bounded, which proves that the tracking error signal will converge into a small compact set. Simulation results show the effectiveness of the proposed method.