Residual selection for fault detection and isolation using convex optimization

DOI10.1016/j.automatica.2018.08.006zbMath1406.93092OpenAlexW2887500168WikidataQ129353653 ScholiaQ129353653MaRDI QIDQ1716515

Daniel Jung, Erik Frisk

Publication date: 5 February 2019

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-151295

zbMATH Keywords

convex optimizationfault detection and isolationmodel-based diagnosisfeature selectioncomputer-aided design tools

Mathematics Subject Classification ID

Convex programming (90C25) Sensitivity (robustness) (93B35) Application models in control theory (93C95) Design techniques (robust design, computer-aided design, etc.) (93B51)

Related Items (1)

Data-driven fault detection for large-scale network systems: a mixed optimization approach

Uses Software

• Fault Diagnosis Toolbox

Cites Work

• Sensor placement for fault location identification in water networks: a minimum test cover approach
• A method for quantitative fault diagnosability analysis of stochastic linear descriptor models
• Information criteria for residual generation and fault detection and isolation
• 10.1162/153244303322753616
• Diagnosis and Fault-Tolerant Control
• CONTINUOUS INSPECTION SCHEMES

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