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中文摘要：
针对一类带有未知虚拟控制增益的随机严格反馈非线性系统，基于后推设计，引入积分型Lyapunov函数，并利用神经网络的逼近能力，提出了一种自适应神经网络控制方案．与现有研究结果相比，放宽了对控制系统的要求，取消了对于未知函数的限制条件．通过Lyapunov方法证明了闭环系统的所有误差信号依概率有界．仿真结果验证了所给控制方案的有效性．
英文摘要：
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.
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