Interval fuzzy modelling in fault detection for a class of processes with interval-type parameters

In the paper an application of the interval fuzzy model (INFUMO) in fault detection for a class of processes with uncertain interval-type parameters is presented. A confidence band for the process input-output data is obtained and approximated using a fuzzy model with interval parameters. The approx...

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Bibliographic Details
Published inEUROCON 2005 - The International Conference on "Computer as a Tool" Vol. 2; pp. 1867 - 1870
Main Author Oblak, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Algorithm design and analysis
Fault detection
Filtering
Fuzzy model
Fuzzy systems
interval model
Linear programming
Power system modeling
Robustness
Signal processing
Uncertain systems
Uncertainty
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Summary:In the paper an application of the interval fuzzy model (INFUMO) in fault detection for a class of processes with uncertain interval-type parameters is presented. A confidence band for the process input-output data is obtained and approximated using a fuzzy model with interval parameters. The approximation is based on fuzzy linear programming using l infin -norm as a measure of the modelling error. Applying high-pass filtering when obtaining the confidence band makes it possible to use arbitrary sets of identification input signals. An application of the INFUMO in detection of load change in a motor-generator system is presented to demonstrate the benefits of the proposed method
ISBN:9781424400492
142440049X
DOI:10.1109/EURCON.2005.1630345