Adaptive motion control using neural network approximations

被引:77
作者
Huang, SN [1 ]
Tan, KK [1 ]
Lee, TH [1 ]
机构
[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 119260, Singapore
关键词
adaptive control; compensation; friction; neural networks; uncertainty;
D O I
10.1016/S0005-1098(01)00192-3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we present a new adaptive technique for tracking control of mechanical systems in the presence of friction and periodic disturbances. Radial Basis Functions (RBFs) are used to compensate for the effects of nonlinearly occurring parameters in the friction and periodic disturbance model. Theoretical analysis, such as stability and transient performance, is provided. Furthermore, the performance of the adaptive RBF controller and its non-adaptive counterpart are compared. (C) 2001 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:227 / 233
页数:7
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