Dynamic State Estimation of Power System Based on a Robust H-infinity Cubature Kalman Filter

A Novel Adaptive Robust Cubature Kalman Filter for Maneuvering Target Tracking with Model Uncertainty and Abnormal Measurement Noises

“…The CKF regards the estimation of nonlinear equations as the estimation of a probability distribution based on Bayesian estimation, which dramatically simplifies the nonlinear problem and can be well applied to high-dimensional nonlinear system filtering [ 26 ]. In order to apply H-infinity filtering to nonlinear systems, a cubature Kalman filter (HCKF) based on H-infinity filtering is proposed [ 16 , 27 ]. The algorithm steps are as follows:…”

“…The H-infinity filter is designed to minimize the impact of the worst disturbance on the estimation error by incorporating the H-infinity norm into the filter design. In [ 16 , 17 ], the H-infinity filter, which can be applied only to linear systems, is applied to nonlinear systems, maintaining the advantages of the CKF and H-infinity filter. However, various circumstances, including model uncertainty and external interference, will prevent information from fusing, lowering the H-infinity filter’s estimation accuracy.…”