Adaptive control for stochastic nonlinear systems based on the integral-type Lyapunov function

Based on the backstepping technique, introducing the integral-type Lyapunov function and utilizing the approximation capability of neural networks, an adaptive neural network control scheme was proposed for a class of stochastic strict-feedbagk nonlinear systems with unknown virtual control gain. Compared with existing literatures, the proposed approach relaxes the requirements of the control system and cancels the restriction of the unknown function, By the Lyapunov method, it is shown that all error variables in the closed-loop system are bounded in probability. Simulation results illustrate the effectiveness of the proposed control scheme.