带有摄动的随机非线性系统的自适应神经网络控制  

ADAPTIVE NEURAL NETWORK CONTROL OF STOCHASTIC NONLINEAR SYSTEMS WITH PERTURBATIONS

作　　者：王飞[1] 张天平[1] 朱柏城[1] 

机构地区：[1]扬州大学信息工程学院自动化专业部,扬州225127

出　　处：《系统科学与数学》2011年第6期686-696,共11页Journal of Systems Science and Mathematical Sciences

基　　金：国家自然科学基金资助(项目批准号:60874045;60904030);江苏省自然科学基金项目资助(项目批准号:BK2009184);江苏省高校自然科学基础研究项目资助(项目批准号:09KJB510019;10KJB510027).

摘　　要：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 capabil- ity 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.

关 键 词：随机非线性系统 自适应控制 神经网络 后推 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]