| Issue |
E3S Web Conf.
Volume 309, 2021
3rd International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED-ICMPC 2021)
|
|
|---|---|---|
| Article Number | 01021 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.1051/e3sconf/202130901021 | |
| Published online | 07 October 2021 | |
A study of Comparative analysis of fuzzy logic controller and neural network for dc–dc buck converter
1 EEE Department, GRIET, Hyderabad
2 EEE Department, GRIET, Hyderabad.
This paper presents the comparative analysis between fuzzy logic controller and neural network for DC-DC Buck converter. The major drawback in the conventional buck converter is when the input voltage or load change, the output voltage also changes which reduces the overall efficiency of the buck converter. So here we are using non linear controllers for buck converter which respond quickly for perturbations and maintains the fixed load voltage even when there are non-linearity’s occurs compared to a linear controllers like P,PI,PID controllers which can’t withstand when perturbations occur. Simplicity, low cost and adaptability to the complex systems without mathematical modeling are the best features of Fuzzy Logic controller and neural networks. The Two implementations are analyzed in detail and simulated in MATLAB/SIMULINK environment and results presented. Proposed approach is implemented on DC to DC step down converter for an input of 230V and performance characteristics like maximum overshoot, settling time and efficiency of the converter are studied.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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