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Adaptive Artificial Neural Network Based Control Strategy for Shunt Active Power Filter” IEEE International Conference on Electrical Power and Energy Systems (ICEPES), December 14-16, 2016, MANIT Bhopal, India.

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dc.contributor.author Bansal, Hari Om
dc.contributor.author Ajmera, Pawan K.
dc.date.accessioned 2023-02-15T09:14:51Z
dc.date.available 2023-02-15T09:14:51Z
dc.date.issued 2016
dc.identifier.uri https://ieeexplore.ieee.org/document/7915929
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9241
dc.description.abstract Shunt active power filter (SAPF) is used to mitigate the current harmonics and to improve the power factor. In this paper, Adaptive linear-neuron (ADALINE) based phase lock loop (PLL) controlling scheme is presented for SAPF. ADALINE networks estimate the fundamental supply frequency. This scheme detects the phase information of the supply voltage and also used for parallel computing as it provides faster convergence. This algorithm is trained by least-mean squares (LMS) rule which offers low computational burden on the system. In this work, ADALINE is tuned using particle swarm optimization (PSO) technique to improve the dynamic performance of the system. The results obtained are compared with conventional PLL control technique and are found to be significantly better. The performance of the proposed ADALINE based control algorithm is validated using MATLAB/Simulink. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject EEE en_US
dc.subject Adaptive linear neuron en_US
dc.subject Particle Swarm Optimization en_US
dc.subject Synchronous reference frame theory en_US
dc.subject Shunt active power filter en_US
dc.title Adaptive Artificial Neural Network Based Control Strategy for Shunt Active Power Filter” IEEE International Conference on Electrical Power and Energy Systems (ICEPES), December 14-16, 2016, MANIT Bhopal, India. en_US
dc.type Article en_US


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