Measurement of synchronous machine parameters using Kalman filter based fuzzy logic estimator

This paper presents a new Kalman filter/fuzzy logic approach for estimating synchronous machine parameters from short circuit tests. The technique uses on-line noisy measurements of the short circuit current for estimating direct axis reactances, and time constant synchronous machine parameters. The...

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Published inMeasurement : journal of the International Measurement Confederation Vol. 43; no. 10; pp. 1327 - 1335
Main Authors Al-Hamadi, H.M., EL-Naggar, K.M.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.12.2010
Subjects
Dynamical systems
Dynamics
Estimating
Estimation
Fuzzy logic
Kalman filter
Kalman filters
Mathematical models
Short circuit currents
Short circuit test
Synchronous machine parameters
Synchronous machines
Fuzzy logic
Short circuit test
Estimation
Kalman filter
Synchronous machine parameters
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Summary:This paper presents a new Kalman filter/fuzzy logic approach for estimating synchronous machine parameters from short circuit tests. The technique uses on-line noisy measurements of the short circuit current for estimating direct axis reactances, and time constant synchronous machine parameters. The approach is based on expressing short circuit current as a discrete time linear dynamic system model suitable for the Kalman filter to estimate the parameters. Fuzzy rule-based logic is used to tune-up measurement noise levels by adjusting the covariance matrix. The results show a better convergence using fuzzy logic than those solely using the Kalman filter.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
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content type line 23
ISSN:0263-2241
1873-412X
DOI:10.1016/j.measurement.2010.07.012