基于神经网络的一类非仿射非线性系统自适应控制  

NEURAL NETWORK BASED ADAPTIVE CONTROL FOR A CLASS OF NONAFFINE NONLINEAR SYSTEMS

作　　者：李树荣[1] 杨青[1] 郭淑会[1] 

机构地区：[1]石油大学(华东)信息与控制工程学院,东营257061

出　　处：《系统科学与数学》2007年第2期161-169,共9页Journal of Systems Science and Mathematical Sciences

基　　金：国家"973"项目(2004CB31800)资助.

摘　　要：针对一类带有不确定性的非仿射非线性系统,利用Backstepping设计方法,设计了一种神经网络自适应控制器．该控制器可以实现跟踪特性．基于Lyapunov函数,得出稳定的权学习算法．并利用Lyapunov稳定性理论证明了闭环系统是一致最终有界的．仿真结果表明,这种控制器具有良好的鲁棒性和跟踪特性．An adaptive neural network control scheme is designed for a class of nonaffine nonlinear systems with uncertainty. The designing method is based on backsteppmg sc.heme. The tracking performance can be realized. A stable weight learning algorithm is obtained by using a Lyapunov function. It is proven that the closed-loop system is uniformly ultimately bounded（UUB） by using Lyapunov theory. Simulation results verify the good：tracking performance and robustness of the newly designed controller for non-affine systems.

关 键 词：神经网络 自适应控制 BACKSTEPPING 非线性系统. 

分 类 号：O231.2[理学—运筹学与控制论]