Neural Networks Applied to the Control of a Four-Wire Shunt Active Power Filter

Marcelo G. Villalva; Ernesto Ruppert Filho

doi:10.18618/REP.2005.1.023030

Authors

Marcelo G. Villalva FEEC - UNICAMP CEP 13083 - 852 , Caixa Postal 6101 , Campinas - SP, Brasil
Ernesto Ruppert Filho FEEC - UNICAMP CEP 13083 - 852 , Caixa Postal 6101 , Campinas - SP, Brasil

DOI:

https://doi.org/10.18618/REP.2005.1.023030

Keywords:

Active Filter, adaline, neural network

Abstract

This paper presents a four-wire shunt active power filter fully controlled with neural networks. The paper is centered on a current compensation method based on adaptive linear elements (adalines), which are powerful and easy-to-use neural networks. The reader will find here an introduction about these networks, an explanatory section about the achievement of Fourier series with adalines, and the full description of an adaline-based selective current compensator. The paper also brings a discussion about the use of a feedforward neural network in the current controller of the active filter, as well as simulation and experimental results obtained with a prototype of a shunt active power filter.

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Author Biographies

Marcelo G. Villalva, FEEC - UNICAMP CEP 13083 - 852 , Caixa Postal 6101 , Campinas - SP, Brasil

graduated in electrical engineering at the University of Campinas (UNICAMP) in 2002. He received his master's degree and now pursues doctoral studies, both at UNICAMP.

Ernesto Ruppert Filho, FEEC - UNICAMP CEP 13083 - 852 , Caixa Postal 6101 , Campinas - SP, Brasil

graduated in electrical engineering at the University of Campinas (UNICAMP) and received his master's and his doctorate in 1971, 1974, and 1983 respectively. Since 1972 he has been with UNICAMP as a faculty member and as a researcher. His research interests include power electronics, superconductors, pwer systems, distributed generation, electric machines, and motor drives.

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