Robust Dynamic State Estimation for DFIG via the Generalized Maximum Correntropy Criterion Ensemble Kalman Filter-Reference-Cited by-同舟云学术

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Robust Dynamic State Estimation for DFIG via the Generalized Maximum Correntropy Criterion Ensemble Kalman Filter

Published:2023 Issue: Volume:72 Page:1-13
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Ma Wentao¹^ORCID,Wang Chenyu¹^ORCID,Dang Lujuan²,Zhang Xinyu³^ORCID,Chen Badong²^ORCID

Affiliation:

1. School of Electrical Engineering, Xi’an University of Technology, Xi’an, China

2. Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China

3. Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an University of Technology, Xi’an, China

Funder

National Key Research and Development Program of China

Joint Fund Project of the National Natural Science Foundation of China

National Natural Science Foundation of China

Key Laboratory Project of Shaanxi Provincial Education Department Scientific Research Projects

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10298275.pdf?arnumber=10298275

Reference43 articles.

1. Dynamic State Estimation of Power Systems by $p$ -Norm Nonlinear Kalman Filter

2. Maximum Correntropy Square-Root Cubature Kalman Filter for Non-Gaussian Measurement Noise

3. Square Root Unscented Kalman Filter With Modified Measurement for Dynamic State Estimation of Power Systems

4. UKF Based on Maximum Correntropy Criterion in the Presence of Both Intermittent Observations and Non-Gaussian Noise

5. Event-Triggered Approach to Dynamic State Estimation of a Synchronous Machine Using Cubature Kalman Filter

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1. Composite Disturbances Nonlinear Filtering for Simultaneous State and Unknown Input Estimation Under Non-Gaussian Noises;IEEE Transactions on Instrumentation and Measurement;2024

2. Robust Forecasting-Aided State Estimation Method of Distribution Network Based on Res-Autoformer and Unscented Particle Filter;2024

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