一类带有死区模型的随机系统的自适应跟踪控制  

ADAPTIVE TRACKING CONTROL FOR A CLASS OF STOCHASTIC SYSTEMS WITH DEAD-ZONE MODEL

作　　者：朱柏城[1] 张天平[1] 王飞[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》2012年第11期1331-1342,共12页Journal of Systems Science and Mathematical Sciences

基　　金：国家自然科学基金(61174046;60904030和61175111);江苏省自然科学基金项目(BK2009184)资助课题

摘　　要：针对一类带有死区模型的随机严格反馈非线性系统,利用神经网络的逼近能力和后推设计方法,提出一种神经网络自适应跟踪控制方案.与已有文献相比,该方案取消了控制律和自适应律设计必须与神经网络节点数相关的条件.通过Lyapunov方法,证明了闭环系统的所有信号依概率有界,且误差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.By using the approximation capability of neural networks and the backstepping method, an adaptive neural network control scheme is proposed for a class of stochastic strict- feedback nonlinear systems with dead-zone model. Compared with the existing literature, the proposed approach eliminates the condition that the controller and adaptation law should be related to the nodes of neural network. By Lyapunov method, it is shown that all signals in the closed loop system are bounded in probability, and the error signals 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 DroDosed contr~~l .~ch^rn~

关 键 词：随机非线性系统 自适应控制 神经网络 后推 死区模型 

分 类 号：O231.3[理学—运筹学与控制论]