Voltage Tracking of a Multi-Input Interleaved Buck-Boost DC-DC Converter Using Artificial Neural Network Control

Authors

  • Yonis. M. Buswig Universiti Malaysia Sarawak, 94300, Kota Samarahan, Sarawak.
  • Al-Khalid Othman Universiti Malaysia Sarawak, 94300, Kota Samarahan, Sarawak.
  • Norhuzaimin Julai Universiti Malaysia Sarawak, 94300, Kota Samarahan, Sarawak.
  • Sim Sy Yi Universiti Tun Hussein Onn Malaysia, 86400, Parit Raja, Johor.
  • Wahyu Mulyo Utomo Universiti Tun Hussein Onn Malaysia, 86400, Parit Raja, Johor.
  • Alvin John Lim Meng Siang Universiti Tun Hussein Onn Malaysia, 86400, Parit Raja, Johor.

Keywords:

Multi-Input Converter, Algorithm BackPropagation, Artificial Neural Network Control, Tracking Voltage Variations,

Abstract

This paper proposes an artificial neural network (ANN) voltage tracking of multi-input interleaved buck-boost DC-DC converter. A back-propagation algorithm topology is implemented in this paper. The control unit is implemented to ameliorate the performance of the proposed multi-input converter during transient dynamic response and steady-state operation mode. The neural network controller unit design, which is adaptive against output voltage command tracking and reference voltage variations is proposed. The proposed design has been verified through the MATLAB software. The simulation outcomes emphasized the validity and reliability of the proposed neural network technique, which would be a promising an efficient control method that ensures multi-input converter suitable for electric vehicle and renewable energy application systems.

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Published

2018-03-01

How to Cite

Buswig, Y. M., Othman, A.-K., Julai, N., Yi, S. S., Utomo, W. M., & Lim Meng Siang, A. J. (2018). Voltage Tracking of a Multi-Input Interleaved Buck-Boost DC-DC Converter Using Artificial Neural Network Control. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-12), 29–32. Retrieved from https://jtec.utem.edu.my/jtec/article/view/3822

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