摘要
提出一种非线性系统的自适应神经跟踪控制方案 .通过利用RBF神经网络对未知非线性系统建模 ,并用一个滑模控制项消除网络建模误差和外部干扰的影响 ,从而能够保证闭环系统的全局稳定性和输出跟踪误差渐近收敛于零 .
A neural network based adaptive tracking control scheme is proposed for a class of nonlinear systems. Two RBF neural networks are used to approximate the unknown nonlinear system, and a sliding model control term is used to eliminate the effects of the network inherent approximation errors and external disturbance. This control scheme can ensure the global stability of closed loop system and the asymptotical convergence of output tracking error.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2001年第3期461-464,468,共5页
Control Theory & Applications
基金
supportedbytheFoundationofNationalDefenceEarlyResearchofScience&Technology ( 99J16.6.1BQ0 2 14 )andtheNationalNatu ralScienceF
关键词
神经网络
非线性系统
输出跟踪
逼近误差
自适应控制
neural networks
nonlinear systems
output tracking
approximate error
adaptive control
