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Adaptive Backstepping Current Control of Active Power Filter Using Neural Compensator
A backstepping-based adaptive controller with neural compensator is designed for harmonic suppression in a three-phase active power filter (APF). The fundamental rule of backstepping method is to take some state variables as “virtual controls” and then design intermediate controller. An adaptive neu...
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Published in: | Mathematical problems in engineering 2019-01, Vol.2019 (2019), p.1-9 |
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container_title | Mathematical problems in engineering |
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creator | Fang, Yunmei Fei, Juntao |
description | A backstepping-based adaptive controller with neural compensator is designed for harmonic suppression in a three-phase active power filter (APF). The fundamental rule of backstepping method is to take some state variables as “virtual controls” and then design intermediate controller. An adaptive neural controller using radial basis function (RBF) is derived to estimate the APF system nonlinearity and strengthen the current’s tracking property and power grid quality. Simulations studies indicate the proposed backstepping-based adaptive neural controller has good current tracking behavior and increased power quality. |
doi_str_mv | 10.1155/2019/5130738 |
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subjects | Active control Adaptive control Adaptive filters Basis functions Control algorithms Control systems design Controllers Design Neural networks Nonlinear systems Quality Radial basis function State variable Tracking |
title | Adaptive Backstepping Current Control of Active Power Filter Using Neural Compensator |
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