Fault detection and accommodation in non-linear systems using fuzzy-neural networks

被引：0
|
作者：
Ji, Zhicheng [1 ]
Zhu, Rongjia [1 ]
Shen, Yanxia [1 ]
机构：
[1] So Yangtze Univ, Control Sci & Engn Res Ctr, Wuxi 214122, Peoples R China
来源：
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS | 2006年 / 13卷
关键词：
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A fault detection and accommodation methods based on RBF fuzzy neural networks for non-linear systems was presented. The fault parameters adaptive updating method was used to detect malfunction, fuzzy neural networks was used to adjust the fault parameters for tracking the faults. Fault compensation control input was introduced for fault accommodation. The theory analysis and simulation results show that when the parameters fault happed, the systems can still preserve certain performance by fault accommodation control, and the applicability and validity of RBF (Radial Basis Function) fuzzy neural networks in fault time-varying system accommodation control was proved.
引用
收藏
页码：972 / 976
页数：5
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