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针对一类动力学未知或难以建模的采样非线性系统，提出了一种基于神经网络的跟随控制器稳定自适应控制方法．控制器采用径向基函数神经网络近似对象的动力学非线性，神经网络参数的自适应规律由稳定理论得到．文中给出了系统稳定性和跟随误差收敛性的证明，并通过仿真实例揭示了所提方法的性能．
Aiming at a kind of sampling nonlinear system with unknown or hard to model dynamics, a new adaptive control method based on neural network is proposed. The controller adopts the radial basis function neural network to approximate the dynamic nonlinearity of the object, and the adaptive rule of the neural network parameters is obtained from the stability theory. The proof of system stability and following error convergence is given in this paper, and the performance of the proposed method is revealed through simulation examples.