摘要
改进了原有的ε-滤波自适应逆控制系统,引入自适应扰动消除器和反馈补偿,构成一种新的自适应逆控制系统.反馈补偿能消除自适应逆控制系统中的直流零频漂移,自适应扰动消除器能最大限度地消除扰动.将神经网络引入自适应逆控制系统,采用基于径向基函数网络的非线性滤波器,对非线性系统进行建模、逆建模、控制器及自适应扰动消除器的设计.仿真结果验证了该方法的有效性.
An MRAIC system based on filtered-Ε algorithm, which comprises an adaptive disturbance canceler and feedback compensation, is presented. The feedback compensation can counteract the MRAIC system's direct current zero-frequency drift. The adaptive disturbance canceler can best erase disturbances. A nonlinear filter based on RBF networks is used in nonlinear plant modeling, inverse plant modeling, design of controllers and adaptive disturbance canceler. Simulation result shows the effectiveness of the method.
出处
《控制与决策》
EI
CSCD
北大核心
2004年第10期1175-1177,1182,共4页
Control and Decision
基金
中国科学院百人计划资助项目.
关键词
径向基函数网络
模型参考自适应逆控制
自适应扰动消除器
Adaptive control systems
Computer simulation
Interference suppression
Nonlinear filtering
Radial basis function networks
