Proceedings of the 2017 International Conference on Computational Science and Engineering (ICCSE 2017)

Study on Robust Fault Detection For Linear Discrete Time-Varying Systems With Measurement Missing

Authors
Chun-peng Wang, Jian Guo
Corresponding Author
Chun-peng Wang
Available Online July 2017.
DOI
https://doi.org/10.2991/iccse-17.2017.6How to use a DOI?
Keywords
Robust fault detection filter, Missing measurements, filtering, Linear discrete time-varying systems, Linear matrix inequality
Abstract
In this study, the robust fault detection problem is investigated for a class of linear discrete time-varying systems with multiple measurement packet dropouts. The missing measurements are modeled as a linear function of the stochastic variable satisfying Bernounlli random binary distribution. A robust fault detection filter based on filtering is designed to make residual error system be exponentially mean-square stable and satisfy a prescribed disturbance attenuation level. A sufficient condition is derived in terms of linear matrix inequalities. Numerical examples are given to illustrate the effectiveness of the proposed method. The simulation result has showed the effectiveness and applicability of the obtained approach.
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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
July 2017
ISBN
978-94-6252-404-0
ISSN
2352-538X
DOI
https://doi.org/10.2991/iccse-17.2017.6How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Chun-peng Wang
AU  - Jian Guo
PY  - 2017/07
DA  - 2017/07
TI  - Study on Robust Fault Detection For Linear Discrete Time-Varying Systems With Measurement Missing
PB  - Atlantis Press
SP  - 30
EP  - 35
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccse-17.2017.6
DO  - https://doi.org/10.2991/iccse-17.2017.6
ID  - Wang2017/07
ER  -