Uncertainty Analysis of a Fault Detection and Isolation Scheme for Multi-Agent Systems

Diagnostic techniques in model-based fault detection and isolation approaches are often based on residuals. If the residuals become greater than a certain threshold then an alarm can be triggered. However, disturbances, such as those caused by model uncertainty, affect the behavior of the residuals...

Full description

Bibliographic Details
Main Author: Schwarz, Thoralf A.
Format: Others
Language:English
Published: KTH, Reglerteknik 2012
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104013
id ndltd-UPSALLA1-oai-DiVA.org-kth-104013
record_format oai_dc
spelling ndltd-UPSALLA1-oai-DiVA.org-kth-1040132013-01-08T13:44:59ZUncertainty Analysis of a Fault Detection and Isolation Scheme for Multi-Agent SystemsengSchwarz, Thoralf A.KTH, Reglerteknik2012Diagnostic techniques in model-based fault detection and isolation approaches are often based on residuals. If the residuals become greater than a certain threshold then an alarm can be triggered. However, disturbances, such as those caused by model uncertainty, affect the behavior of the residuals and therefore the performance of the diagnostic system. Fault detection becomes a matter of security when applied in multi-agent systems, since their distributed nature offers adversaries possibilities to attack the system. This thesis considers disturbances caused by model uncertainty which is often encountered during implementation. Their influence on a model-based fault detection and isolation scheme in multi-agent systems is analyzed and an evaluation technique for the residuals is proposed. Different attack scenarios are considered and their influence on the residuals will be discussed. Finally, experimental results circumstantiate the proposed approaches. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104013EES Examensarbete / Master Thesis ; XR-EE-RT 2012:024application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
description Diagnostic techniques in model-based fault detection and isolation approaches are often based on residuals. If the residuals become greater than a certain threshold then an alarm can be triggered. However, disturbances, such as those caused by model uncertainty, affect the behavior of the residuals and therefore the performance of the diagnostic system. Fault detection becomes a matter of security when applied in multi-agent systems, since their distributed nature offers adversaries possibilities to attack the system. This thesis considers disturbances caused by model uncertainty which is often encountered during implementation. Their influence on a model-based fault detection and isolation scheme in multi-agent systems is analyzed and an evaluation technique for the residuals is proposed. Different attack scenarios are considered and their influence on the residuals will be discussed. Finally, experimental results circumstantiate the proposed approaches.
author Schwarz, Thoralf A.
spellingShingle Schwarz, Thoralf A.
Uncertainty Analysis of a Fault Detection and Isolation Scheme for Multi-Agent Systems
author_facet Schwarz, Thoralf A.
author_sort Schwarz, Thoralf A.
title Uncertainty Analysis of a Fault Detection and Isolation Scheme for Multi-Agent Systems
title_short Uncertainty Analysis of a Fault Detection and Isolation Scheme for Multi-Agent Systems
title_full Uncertainty Analysis of a Fault Detection and Isolation Scheme for Multi-Agent Systems
title_fullStr Uncertainty Analysis of a Fault Detection and Isolation Scheme for Multi-Agent Systems
title_full_unstemmed Uncertainty Analysis of a Fault Detection and Isolation Scheme for Multi-Agent Systems
title_sort uncertainty analysis of a fault detection and isolation scheme for multi-agent systems
publisher KTH, Reglerteknik
publishDate 2012
url http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-104013
work_keys_str_mv AT schwarzthoralfa uncertaintyanalysisofafaultdetectionandisolationschemeformultiagentsystems
_version_ 1716527707581317120