Improving the Efficiency of Fuzzy Logic Controller Using Genetic Algorithms in order to Control (DC-DC) Converters

Authors

  • Ahed Zina Tishreen University

Abstract

DC-DC converter circuits effectively convert the DC input voltage into a regulated output voltage more efficiently than linear regulators or magnetic transformers. The electronic switches of these converters are controlled to obtain the desired regulated output voltage value.

In recent years, the concept of using Artificial Intelligence systems to control electrical circuits and their practical applications has expanded, as Fuzzy Logic Controller (FLC) is one of the most famous types of these systems because it uses inferential logic to simulate the work of the human brain by formulating the fuzzy rule and following the membership of the system’s input and output and converting the output into a numerical value that controls it’s in turn the duty cycle of the converter.

The research proposes the use of Genetic Algorithms (GA) that simulate the principle of natural inheritance (the survival of the fittest principle) to improve the accuracy of the fuzzy controller and thus the efficiency of the step-down converter (Buck) by finding the ideal values for its coefficients in order to obtain the closest value for the reference voltage by improving the parameters of the gain constants and changing the shape of membership.

The results of the research using MATLAB show the improvement provided by the Genetic-Fuzzy controller (GA-FLC) compared to the fuzzy logic controller in terms of the response parameters and output curves of the Buck converter.

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Published

2023-07-18

How to Cite

1.
زينه ع. Improving the Efficiency of Fuzzy Logic Controller Using Genetic Algorithms in order to Control (DC-DC) Converters. Tuj-eng [Internet]. 2023Jul.18 [cited 2024Dec.23];45(3):203-16. Available from: https://journal.tishreen.edu.sy/index.php/engscnc/article/view/14833

Issue

Vol. 45 No. 3 (2023): Tishreen University Journal of Research and Scientific Studies - Engineering Sciences Series

Section

Articles

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