Liu, J., et al. (2021) A Backpropagation Neural Network Controller Trained Using PID for Digitally-Controlled DC-DC Switching Converters. 2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA), Chengdu, 1-4 August 2021, 946-951.
https://doi.org/10.1109/ICIEA51954.2021.9516423

has been cited by the following article:

• TITLE: Performance of the Boost Chopper, Comparative Study between PI Control and Neural Control to Regulate Its Output Voltage

  AUTHORS: Ibrahima Gueye, Mamadou Sall, Abdoulaye Kebe

  KEYWORDS: Chopper, PI Control, Neural Control

  JOURNAL NAME: Smart Grid and Renewable Energy, Vol.14 No.5, May 19, 2023

  ABSTRACT: In this study, we investigate the performance of a boost converter regulating its output voltage using two control methods: Proportional-Integral (PI) control and neural control. Both methods are implemented on a simulation platform (Matlab/Simulink) and evaluated in terms of accuracy, response speed, and robustness to disturbances. Indeed, the output voltage of converters exhibits imperfections that require a control method to optimize efficiency when applying a variable load. Results show that neural control offers superior performance in terms of accuracy and response time, with faster and more precise regulation of the output voltage. On the other hand, PI control proves to be more robust against disturbances. These findings can help guide the selection of the appropriate control method for a boost converter based on the specific requirements of each application.