Fault Detection and Estimation for a class of nonlinear systems based on neural network observer

被引：0
|
作者：
Wang, Ruonan [1 ]
Jiang, Bin [1 ]
Liu, Jianwei [1 ]
机构：
[1] Nanjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing 210016, Jiangsu, Peoples R China
来源：
2016 IEEE CHINESE GUIDANCE, NAVIGATION AND CONTROL CONFERENCE (CGNCC) | 2016年
关键词：
neural network; observer; fault estimation; aircraft;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper deals with the fault detection and estimation scheme for a class of nonlinear systems. An adaptive observer is designed where the unknown nonlinear term can be approximated and the fault is estimated based on radial basis function (RBF) neural network, respectively. The stability of the designed observer is also proved. Finally, simulation results based on an aircraft are presented to evaluate the performance of the proposed observer and the effectiveness of the fault estimation.
引用
收藏
页码：1216 / 1219
页数：4
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