Fault Estimation and Accommodation for a Class of Nonlinear System Based on Neural Network Observer

被引:1
|
作者
Wang Ruonan [1 ]
Jiang Bin [1 ]
Liu Jianwei [1 ]
机构
[1] College of Automation Engineering,Nanjing University of Aeronautics and Astronautics
基金
中国国家自然科学基金; 中央高校基本科研业务费专项资金资助;
关键词
actuator fault; component fault; neural network; adaptive observer; fault tolerant controller;
D O I
10.16356/j.1005-1120.2018.02.318
中图分类号
TP277 [监视、报警、故障诊断系统];
学科分类号
0804 ; 080401 ; 080402 ;
摘要
The problem of fault estimation and accommodation of nonlinear systems with disturbances is studied using adaptive observer and neural network techniques.A robust adaptive learning algorithm based on switchingβsmodification is developed to realize the accurate and fast estimation of unknown actuator faults or component faults.Then a fault tolerant controller is designed to restore system performance.Dynamic error convergence and system stability can be guaranteed by Lyapunov stability theory.Finally,simulation results of quadrotor helicopter attitude systems are presented to illustrate the efficiency of the proposed techniques.
引用
收藏
页码:318 / 325
页数:8
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