A tractable fault detection and isolation approach for nonlinear systems with probabilistic performance

Open access
Date
2016-03Type
- Journal Article
Citations
Cited 27 times in
Web of Science
Cited 29 times in
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ETH Bibliography
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Abstract
This article presents a novel perspective along with a scalable methodology to design a fault detection and isolation (FDI) filter for high dimensional nonlinear systems. Previous approaches on FDI problems are either confined to linear systems or they are only applicable to low dimensional dynamics with specific structures. In contrast, shifting attention from the system dynamics to the disturbance inputs, we propose a relaxed design perspective to train a linear residual generator given some statistical information about the disturbance patterns. That is, we propose an optimization-based approach to robustify the filter with respect to finitely many signatures of the nonlinearity. We then invoke recent results in randomized optimization to provide theoretical guarantees for the performance of the proposed filer. Finally, motivated by a cyber-physical attack emanating from the vulnerabilities introduced by the interaction between IT infrastructure and power system, we deploy the developed theoretical results to detect such an intrusion before the functionality of the power system is disrupted. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000095072Publication status
publishedExternal links
Journal / series
IEEE Transactions on Automatic ControlVolume
Pages / Article No.
Publisher
IEEEOrganisational unit
03751 - Lygeros, John / Lygeros, John
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Citations
Cited 27 times in
Web of Science
Cited 29 times in
Scopus
ETH Bibliography
yes
Altmetrics