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Robust distributed extended Kalman filter based on adaptive multi-kernel mixture maximum correntropy for non-Gaussian systems
Duc Viet Nguyen, Haiquan Zhao, Jinhui Hu +1
As one of the most advanced variants in the correntropy family, the multi-kernel correntropy criterion demonstrates superior accuracy in handling non-Gaussian noise, particularly w…
Distributed Cubature Kalman Filter based on MEEF with Adaptive Cauchy Kernel for State Estimation
Duc Viet Nguyen, Haiquan Zhao, Jinhui Hu
Nowadays, with the development of multi-sensor networks, the distributed cubature Kalman filter is one of the well-known existing schemes for state estimation, for which the influe…
Dynamic State Estimation of Power System Utilizing Cauchy Kernel-Based Maximum Mixture Correntropy UKF over Beluga Whale-Bat Optimization
Duc Viet Nguyen, Haiquan Zhao, Jinhui Hu
Non-Gaussian noise, outliers, sudden load changes, and bad measurement data are key factors that diminish the accuracy of dynamic state estimation in power systems. Additionally, u…
Adaptive Robust Unscented Kalman Filter for Dynamic State Estimation of Power System
Duc Viet Nguyen, Haiquan Zhao, Jinhui Hu +1
Non-Gaussian noise and the uncertainty of noise distribution are the common factors that reduce accuracy in dynamic state estimation of power systems (PS). In addition, the optimal…