Robot manipulator controller based on fuzzy neural and CMAC network

被引：5
|
作者：
Liu, H [1 ]
Liu, D [1 ]
Yang, YX [1 ]
Jing, X [1 ]
机构：
[1] Xian Univ Technol, Sch Automat & Informat Engn, Xian, Peoples R China
来源：
2003 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-5, PROCEEDINGS | 2003年
关键词：
uncertainty; fuzzy neural network; CMAC; slide mode control;
D O I：
10.1109/ICMLC.2003.1264533
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new controller is proposed to deal with the uncertainty in robot manipulator dynamic system. This controller is composed of Fuzzy Neural Network (FNN) controller which replaces computed torque controller, Cerebellar model articulation (CMAC) controller which compensates control error online and slide mode controller which compensates fuzzy neural network fit error to enhance robustness of the control system. It is shown that this controller outperforms conventional fuzzy controller by improving learning ability that the conventional fuzzy system does not have with simulations of a two-link manipulator.
引用
收藏
页码：525 / 529
页数：5
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