Fault detection and accommodation via neural network and variable structure control

被引：1

作者：

Yang H. ^{[1
,2
]}

Jiang B. ^{[1
]}

机构：

[1] College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing

[2] LAGIS-CNRS, UMR 8146, Université des Sciences et Technologies de Lille

来源：

Journal of Control Theory and Applications | 2007年 / 5卷 / 3期

基金：

中国国家自然科学基金;

关键词：

Fault accommodation; Fault detection; Neural network; Variable structure control;

D O I：

10.1007/s11768-005-5204-7

中图分类号：

学科分类号：

摘要：

This paper proposes a novel idea that classifies faults into two different kinds: serious faults and small faults, and treats them with different strategies respectively. A kind of artificial neural network (ANN) is proposed for detecting serious faults, and variable structure (VS) model-following control is constructed for accommodating small faults. The proposed framework takes both advantages of qualitative way and quantitative way of fault detection and accommodation. Moreover, the uncertainty case is investigated and the VS controller is modified. Simulation results of a remotely piloted aircraft with control actuator failures illustrate the performance of the developed algorithm. © 2007 Editorial Board of Control Theory & Applications.

引用

页码：253 / 260

页数：7

共 16 条

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