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A Robust Fault Detection Method using a Zonotopic Kaucher Set-membership Approach

Authors: Schwab, Stefan; Puig Cayuela, Vicenç; Hohmann, Soeren;

A Robust Fault Detection Method using a Zonotopic Kaucher Set-membership Approach

Abstract

This paper presents a robust fault detection method using a zonotopic Kaucher set-membership method. The fault detection approach is based on checking the consistency between the model and the data. Consistency is given if there is an intersection between the feasible parameter set and the nominal parameter set. To allow efficient computation the feasible set is approximated by a zonotope. Due to the usage of Kaucher interval arithmetic the results are mathematically guaranteed. The proposed approach is assessed using an illustrative application based on a well-known four-tank case study. The study shows that it is possible to detect even small errors in a noisy setting Peer Reviewed

Countries
Spain, Germany
Keywords

ddc:620, :Informàtica::Automàtica i control [Àrees temàtiques de la UPC], set-membership approach, 620, Robust fault detection, Errors de sistemes (Enginyeria) -- Models matemàtics, Àrees temàtiques de la UPC::Informàtica::Automàtica i control, Kaucher arithmetic, System failures (Engineering), Engineering & allied operations, info:eu-repo/classification/ddc/620

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
10
Top 10%
Average
Top 10%
35
34
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gold