Digital Library of Zielona Góra contains 9 272 digital objects
Object
Title: A survey of robustness problems in quantitative model-based fault diagnosis
Contributor:
Korbicz, Józef (1951- ) - red. ; Cempel, Czesław - red.
Subtitle:
Analytical and Knowledge-Based Redundancy in Fault Detection and Diagnosis
Group publication title:
Abstract:
Quantitative model-based fault diagnosis has become a popular issue in safety-critical systems, e.g., aircraft, spacecraft, chemical processes and nuclear plants. The use of dynamic system model information has been widely recognized as an important approach to fault detection and isolation for the case when there are no repeated hardware units. A prerequisite for reliability in model-based fault diagnosis is robust performance with respect to uncertainties. ; This paper gives a tutorial discussion of the different problems in robustness and surveys the state of the art in robust solutions for quantitative model-based fault diagnosis. The state observer with disturbance de-coupling design has been recommended as a good solution for robustness in fault diagnosis. Further research topics in robust fault diagnosis have also been outlined.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
Resource Identifier:
Pages:
Source:
AMCS, volume 3, number 3 (1993) ; click here to follow the link
Language:
License CC BY 4.0:
Rights:
Biblioteka Uniwersytetu Zielonogórskiego
Object collections:
- Repository > Faculties > Faculty of Computer, Electrical and Control Engineering
- Repository > Types of work > Articles
- Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (1993)
Last modified:
Jul 14, 2025
In our library since:
Jul 7, 2020
Number of object content hits:
223
All available object's versions:
https://zbc.uz.zgora.pl/repozytorium/publication/63836
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| Edition name | Date |
|---|---|
| A survey of robustness problems in quantitative model-based fault diagnosis | Jul 14, 2025 |
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