A Decentralized H-Infinity Unscented Kalman Filter for Dynamic State Estimation Against Uncertainties

The widely used traditional Kalman filter-type power system dynamic state estimator is unable to address the unknown and non-Gaussian system process and measurement noise as well as dynamical model uncertainties. To this end, this paper proposes a decentralized H-infinity unscented Kalman filter tha...

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Veröffentlicht in:	IEEE transactions on smart grid 2019-09, Vol.10 (5), p.4870-4880
Hauptverfasser:	Zhao, Junbo, Mili, Lamine
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer simulation decentralized estimation Dynamic state estimation extended Kalman filter Gaussian process H-infinity control H-infinity filter Kalman filters Mathematical model model uncertainties Noise measurement non-Gaussian noise Regression analysis Regression models Robust control robustness State estimation Statistical analysis Synchronous generators Uncertainty unscented Kalman filter Voltage measurement
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