A Robust Iterated Extended Kalman Filter for Power System Dynamic State Estimation

By Junbo Zhao, Marcos Netto, Lamine Mili. IEEE Transactions on Power Systems, 2017

419 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Civil and Structural Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/b686cc6549ccb4b66406269275649802b2e58093

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Marcos Netto
2. Junbo Zhao
3. Lamine Mili
4. Junjian Qi
5. C. Karlgaard

In Civil and Structural Engineering

1. Marcos Netto
2. Junbo Zhao
3. Lamine Mili
4. Bikash Chandra Pal
5. C. Karlgaard

In Electrical and Electronic Engineering

1. Bikash Chandra Pal
2. Vladimir Terzija
3. Junjian Qi
4. Innocent Kamwa
5. Zhenyu Huang
6. Ravindra Singh
7. Bei Gou
8. Rabih A. Jabr

Citations in the corpus

• Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work (2019, methodology): “To this end, the generalized maximum-likelihood (GM) iterated EKF (GM-IEKF) [89], [90] is proposed to deal with the observation and innovation outliers.”