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.

The Lyapunov function of integral type is introduced into a class of stochastic strict-feedback nonlinear systems with perturbations. By utilizing the approximation capability of neural networks, backstepping technique and Young's inequality, a simple and effective adaptive neural network state feedback controller is constructed. Under some conditions, by the Lyapunov method, it is shown that all signals in the closed-loop system are semi-globally uniformly
ultimately bounded in mean square or the sense of four-moment. Simulation results are given to illustrate the effectiveness of the proposed control scheme.