Robust adaptive unscented Kalman filter with gross error detection and identification for power system forecasting-aided state estimation

DOI10.1016/j.jfranklin.2023.07.022zbMath1521.93192OpenAlexW4384816684MaRDI QIDQ6053907

Zheng Qiang Zhang, Zhen-hui Zhang, Sheng Zhao, Fuhua Li, Zhi-hui Hong, Quanfang Li, Shipei Huang

Publication date: 27 September 2023

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2023.07.022

Mathematics Subject Classification ID

Sensitivity (robustness) (93B35) Estimation and detection in stochastic control theory (93E10)

Cites Work

• Stochastic stability of a modified unscented Kalman filter with stochastic nonlinearities and multiple fading measurements
• Three-stage unscented Kalman filter for state and fault estimation of nonlinear system with unknown input
• Maximum correntropy unscented Kalman and information filters for non-Gaussian measurement noise
• Digital synthesis of non-linear filters
• Robust stable iterated unscented Kalman filter based on maximum correntropy criterion
• Outlier-robust Kalman filters with mixture correntropy
• Enhancing performance of generalized minimum variance control via dynamic data reconciliation

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