Implementation of Artificial Neural Network Controller for Double-Input Boost Converter

Yonis. M. Buswig (Universiti Malaysia Sarawak)
Al-Khalid bin Hj Othman (Universiti Malaysia Sarawak)
Norhuzaimin bin Julai (Universiti Malaysia Sarawak)
Sim Sy Yi (Faculty of Engineering Technology)
W. M. Utomo (University of Narotama Surabaya)
A.J.M.S. Lim (Faculty of Civil and Environmental Engineering)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 11, No 2: August 2018

This paper describes the design of an artificial neural network (ANN) control with power sharing control abilities of a new proposed double-input boost power converter (DIBC). The goal of this research is to model and design a high effectiveness and great performance double-input power converter for renewable energy applications. First, an artificial neural network controller design which is flexible versus a variable input voltage resource and variable load (to achieve the line regulation test and load regulation test) is proposed. Lastly, the suggested concept has been validated through experimentally on the laboratory prototype by using DSP TMS320F28335 real-time digital control. The experimental outcomes emphasize the authenticity of the suggested topology, which can be promising a novel topology that includes double-input power converter appropriate for renewable energy application systems.