一种全局稳定的非线性神经网络系统自适应调节器  

A globally stable adaptive regulator of nonlinear continuous system using neural networks

作　　者：刘晓华[1] 冯恩民[1] 

机构地区：[1]大连理工大学应用数学系,辽宁大连116024

出　　处：《大连理工大学学报》2002年第6期737-740,共4页Journal of Dalian University of Technology

基　　金：山东省自然科学基金资助项目(Y2000G08).

摘　　要：对于一类连续时间的非线性动态系统x=f(x)+Bu+d,当系统中的非线性函数f(x)满足线性增长条件时,首先证明了f(x)中的x落入一紧集中,然后根据神经网络的逼近性质,给出了自适应调节器的设计方法.利用Lyapunov稳定性理论,证明了控制算法是全局稳定的,闭环系统状态是一致最终有界的.For a class of nonlinear dynamical system, when the nonlinear function f(x) satisfies linear growth condition, it was first proved that x falls into a compact set, then the adaptive regulator is proposed based on the approximation capability of neural networks. According to the Lyapunov stability theory, the algorithm is proved to be globally stable, uniformly ultimate boundedness of closed\|loop system is guaranteed.

关 键 词：全局稳定 自适应调节器 神经网络 非线性系统 自适应控制 

分 类 号：TP273.2[自动化与计算机技术—检测技术与自动化装置]