Effect of Harmonics' Modeling in Kalman Filter Performance
Journal Title: IOSR Journals (IOSR Journal of Electrical and Electronics Engineering) - Year 2018, Vol 13, Issue 1
Abstract
In many of applications, a correct estimation of the fundamental component of measured signal is required, several filters are implemented for this purpose such as Kalman filter. To estimate the fundamental component using kalman filter, you need only two variables to represent it in kalman model, the effect of modeling the harmonics on the accuracy of the kalman filter of the fundamental component estimation, was investigated in this paper. Where the results show that including the harmonics in the kalman model enhance the fundamental component estimation. Since we interest in estimating the fundamental component, there will be no need to estimate the individual values of the harmonics, especially that estimating one order of harmonics increases the number of state variables by , and most of the time the order of harmonis in the input signal can’t be recognized, so in this case it is more important to estimate the total harmonics in the signal, based on that a noval model of total harmonic components of the input signal is proposed, where the first 15 harmonics were modeled by using 6 state variables, and the results showed that the proposed model has better results than the conventional models.
Authors and Affiliations
Hisham Alrawashdeh, Jumana Alshawawreh
Keywords
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- DOI 10.9790/1676-1301021932.
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