IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society 2018
DOI: 10.1109/iecon.2018.8591798
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Harmonics Estimation of a Noisy Power System Signal Using Cubature Kalman Filter

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Cited by 6 publications
(1 citation statement)
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“…The unscented Kalman filter (UKF) is another popular filter that follows the unscented transform (UT) to capture the mean and covariance of a Gaussian density has been reported in [20]. Though the UKF shows better performance than the EKF by avoiding the complex calculations of Jacobian and Hessian matrices and making the filter algorithm easy to implement, still there are some unavoidable problems when compared with the cubature Kalman filter (CKF), such as, instability due to UT and computationally slower [21], [22]. Sharma et al [23] have applied the CKF for power system dynamic state estimation.…”
Section: Introductionmentioning
confidence: 99%
“…The unscented Kalman filter (UKF) is another popular filter that follows the unscented transform (UT) to capture the mean and covariance of a Gaussian density has been reported in [20]. Though the UKF shows better performance than the EKF by avoiding the complex calculations of Jacobian and Hessian matrices and making the filter algorithm easy to implement, still there are some unavoidable problems when compared with the cubature Kalman filter (CKF), such as, instability due to UT and computationally slower [21], [22]. Sharma et al [23] have applied the CKF for power system dynamic state estimation.…”
Section: Introductionmentioning
confidence: 99%