A Theoretical Framework of Robust H-Infinity Unscented Kalman Filter and Its Application to Power System Dynamic State Estimation | Zendy

Junbo Zhao | Zendy; Lamine Mili | Zendy

Open Access

A Theoretical Framework of Robust H-Infinity Unscented Kalman Filter and Its Application to Power System Dynamic State Estimation

Author(s) -

Junbo Zhao,

Lamine Mili

Publication year - 2019

Publication title -

ieee transactions on signal processing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.638

H-Index - 270

eISSN - 1941-0476

pISSN - 1053-587X

DOI - 10.1109/tsp.2019.2908910

Subject(s) - kalman filter , control theory (sociology) , h infinity methods in control theory , estimator , robustness (evolution) , mathematics , extended kalman filter , outlier , unscented transform , gaussian , filter (signal processing) , computer science , invariant extended kalman filter , statistics , artificial intelligence , biochemistry , chemistry , control (management) , physics , quantum mechanics , computer vision , gene

This paper presents a new theoretical framework that, by integrating robust statistics and robust control theory, allows us to develop a robust dynamic state estimator of a cyber-physical system. This state estimator combines the generalized maximum-likelihood-type (GM) estimator, the unscented Kalman filter (UKF), and the H-infinity filter into a robust H-infinity UKF filter in the Krein space, w...

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