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Artificial-Neural-Network-Based Phase-Locking Scheme for Active Power Filters.

Authors :
Qasim, Mohammed
Kanjiya, Parag
Khadkikar, Vinod
Source :
IEEE Transactions on Industrial Electronics; Aug2014, Vol. 61 Issue 8, p3857-3866, 10p
Publication Year :
2014

Abstract

This paper presents a phase-locking control scheme based on artificial neural networks (ANNs) for active power filters (APFs). The proposed phase locking is achieved by estimating the fundamental supply frequency and by generating a phase-locking signal. The nonlinear-least-squares-based approach is modified to estimate the supply frequency. To improve the accuracy of frequency estimation, when the supply voltage contains harmonics that are not known, a prefiltering stage is introduced. In shunt APF applications, not only the information of frequency is sufficient but also the phase information of the supply voltage is required to generate a unit template that is phase-locked to the supply voltage. Therefore, in this paper, an adaptive-linear-neuron-based scheme is proposed to extract the phase information of the supply voltage. The estimated system frequency and phase information are then utilized to generate a phase-locking signal that assures a perfect synchronization with the fundamental supply voltage. To demonstrate the effectiveness of the proposed approach, the synchronous reference frame ( d-q theory) shunt APF control method with the proposed ANN-based phase-locking scheme is adopted. The performance of the proposed ANN-based approach is verified experimentally with different supply systems and load conditions. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
02780046
Volume :
61
Issue :
8
Database :
Complementary Index
Journal :
IEEE Transactions on Industrial Electronics
Publication Type :
Academic Journal
Accession number :
94359278
Full Text :
https://doi.org/10.1109/TIE.2013.2284132