A kind of nonlinear adaptive inverse control systems based on fuzzy neural networks

被引：0
|
作者：
Liu, XJ [1 ]
Yi, JQ [1 ]
Zhao, DB [1 ]
Wang, W [1 ]
机构：
[1] Chinese Acad Sci, Inst Automat, Lab Complex Syst & Intelligence Sci, Beijing 100080, Peoples R China
来源：
PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2004年
关键词：
model reference adaptive control; adaptive inverse control; FNN; inverse model; adaptive disturb -ance canceler;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A model reference adaptive inverse control system (MRAICS) based on fuzzy neural networks (FNN), which comprises adaptive disturbance canceler and feedback compensation, is presented in this paper. The feedback compensation can counteract the MRAIC system's direct current zero-frequency drift. The adaptive disturbance canceler can best erase disturbances. Nonlinear filters based on FNN are used in the nonlinear plant modeling, the design of the controller and adaptive disturbance canceller. The nonlinear filters can deal with nonlinear system and result in fast convergence. Simulation result shows that the approach is effective.
引用
收藏
页码：946 / 950
页数：5
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