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Fault Detection and Isolation for Nonlinear System via ESO

by Maryam Naghdi, Mohamad Ali Sadrnia, Javad Askari
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 88 - Number 16
Year of Publication: 2014
Authors: Maryam Naghdi, Mohamad Ali Sadrnia, Javad Askari
10.5120/15434-3663

Maryam Naghdi, Mohamad Ali Sadrnia, Javad Askari . Fault Detection and Isolation for Nonlinear System via ESO. International Journal of Computer Applications. 88, 16 ( February 2014), 8-13. DOI=10.5120/15434-3663

@article{ 10.5120/15434-3663,
author = { Maryam Naghdi, Mohamad Ali Sadrnia, Javad Askari },
title = { Fault Detection and Isolation for Nonlinear System via ESO },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 88 },
number = { 16 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 8-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume88/number16/15434-3663/ },
doi = { 10.5120/15434-3663 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:07:44.921238+05:30
%A Maryam Naghdi
%A Mohamad Ali Sadrnia
%A Javad Askari
%T Fault Detection and Isolation for Nonlinear System via ESO
%J International Journal of Computer Applications
%@ 0975-8887
%V 88
%N 16
%P 8-13
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper fualt detection of nonlinear systems is accomplished by using extended state observer (ESO). Then, the fuzzy logic system is used to isolate faults. The major of observr-based fault detection methods relies on the accurate mathematical model of the system, but in the real world the accurate model may not be available. The ESO is different from conventional observers, it does not require a detailed model of the system, it provide vital information for fault detection with only partial information of the plant. The ESO can agument unknown dynamics combined with unknown external disterbance as extended state and estimate it in real time by using given input-output data. This paper presents a new sensor fault detection and isolation (FDI) via ESO and fuzzy logic system. A two-tank system is used as a case study. The simulation results confirm the effectiveness and simplicity of the fault detection and isolation by using proposed FDI technique.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Extended state observer Fuzzy logic system Nonlinear system Fault detection and isolation.

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