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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
Main Authors: Fang, Yunmei, Fei, Juntao
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Language:English
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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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