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Application of Artificial Neural Networks for Shunt Active Power Filter Control | IEEE Journals & Magazine | IEEE Xplore

Application of Artificial Neural Networks for Shunt Active Power Filter Control


Abstract:

Artificial neural network (ANN) is becoming an attractive estimation and regression technique in many control applications due to its parallel computing nature and high l...Show More

Abstract:

Artificial neural network (ANN) is becoming an attractive estimation and regression technique in many control applications due to its parallel computing nature and high learning capability. There has been a lot of effort in employing the ANN in shunt active power filter (APF) control applications. Adaptive Linear Neuron (ADALINE) and feed-forward multilayer neural network (MNN) are the most commonly used ANN techniques to extract fundamental and/or harmonic components present in the nonlinear currents. This paper aims to provide an in-depth understanding on realizing ADALINE and feed-forward MNN-based control algorithms for shunt APF. A step-by-step procedure to implement these ANN-based techniques in MATLAB/Simulink environment is provided. Furthermore, a detailed analysis on the performance, limitation, and advantages of both methods is presented in the paper. The study is supported by conducting both simulation and experimental validations.
Published in: IEEE Transactions on Industrial Informatics ( Volume: 10, Issue: 3, August 2014)
Page(s): 1765 - 1774
Date of Publication: 08 May 2014

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