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Related Experiment Video

Updated: Nov 27, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Adaptive Extended Kalman Filter with Correntropy Loss for Robust Power System State Estimation.

Zhiyu Zhang1, Jinzhe Qiu1, Wentao Ma1

  • 1School of Automation and Information Engineering, Xi'an University of Technology, Xi'an 710048, China.

Entropy (Basel, Switzerland)
|December 3, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a robust adaptive extended Kalman filter using correntropy loss for power system state estimation (SE). The novel method enhances accuracy and reliability, even with non-Gaussian noise, improving grid monitoring.

Keywords:
adaptive update mechanismcorrentropy lossextended Kalman filternon-Gaussian noisespower system robust state estimation

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Area of Science:

  • Electrical Engineering
  • Control Systems
  • Signal Processing

Background:

  • Real-time power system state estimation (SE) is crucial for grid enhancement.
  • Traditional Kalman filters assume Gaussian noise, which is often violated in practice.
  • Non-Gaussian noise and unknown noise statistics challenge conventional SE methods.

Purpose of the Study:

  • To develop a robust SE algorithm for power systems facing non-Gaussian noise.
  • To improve the accuracy and reliability of state estimation under practical operating conditions.
  • To address the limitations of standard Kalman filters in real-world power system applications.

Main Methods:

  • A novel adaptive extended Kalman filter (EKF) incorporating correntropy loss is proposed.
  • Correntropy is utilized to enhance the algorithm's robustness against non-Gaussian noise and outliers.
  • An adaptive mechanism for updating measurement and process noise covariance matrices is integrated.

Main Results:

  • The proposed EKF with correntropy loss demonstrated improved robustness in simulations.
  • The adaptive covariance update mechanism enhanced the accuracy of the state estimation.
  • Feasibility and robustness were verified on IEEE 14-bus and IEEE 30-bus test systems.

Conclusions:

  • The novel adaptive EKF with correntropy loss is effective for power system SE.
  • The method offers a robust solution for handling non-Gaussian noise in power grids.
  • This approach enhances the reliability of real-time grid monitoring and control.