Design and Implementation of a Voltage Tracking with Artificial Neural Network Controller for a Double-input Buck-Boost Converter
This paper proposes an Artificial Neural Network (ANN) control voltage tracking scheme of a double-input buckboost DC-DC converter. In this topology, a back-propagation algorithm topology is implemented. The controller is developed to improve the performance of the double-input converter during tran...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
UTeM
2017
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/19095/7/Design%20%26%20Implementation.pdf http://ir.unimas.my/id/eprint/19095/ http://journal.utem.edu.my/index.php/jtec/article/view/3155 |
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| Summary: | This paper proposes an Artificial Neural Network (ANN) control voltage tracking scheme of a double-input buckboost DC-DC converter. In this topology, a back-propagation algorithm topology is implemented. The controller is developed to improve the performance of the double-input converter during transient and steady-state operations. The neural network controller design, which is developed against output voltage command tracking is proposed. The proposed concept has been investigated and validated experimentally on a laboratory prototype using DSP TMS320F28335real time digital controller to verify the dynamic response of the proposed controller. The experimental results confirm the validity of the proposed neural network control technique, which is a promising an efficient control topology that ensures doubleinput converter suitable for electric vehicle and renewable energy applications. |
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