针对一类带有摄动的随机严格反馈非线性系统,引入积分型Lyapunov函数,利用神经网络的逼近能力,后推设计方法以及Young’s不等式,构造出一类简单有效的自适应神经网络状态反馈控制器,在一定条件下,通过Lyapunov方法,证明了闭环系统的所有信号在二阶或四阶矩意义下半全局一致终结有界.仿真结果验证了所提控制方案的有效性. For a class of stochastic strict feedback nonlinear systems with perturbation, an integral Lyapunov function is introduced. By using the approximation ability of neural network, backstepping design method and Young’s inequality, a simple and effective adaptive neural network state feedback control Under certain conditions, the Lyapunov method is used to prove that all signals in the closed-loop system are semi-globally uniformly terminated in the sense of second- or fourth-order moments. The simulation results verify the effectiveness of the proposed control scheme.