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Comparative Analysis of Fuzzy and Neural Controller for a Boost Converter

Authors:

Muhammad Waqas Qaisar,

Hassan Mujtaba,

Muhammad Tanveer Riaz,

Muhammad Shahid,

Ahmad Abdul Ghani,

Muhammad Abbas Khan,

Kashif HussainAuthors Info & Claims

EASE '23: Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering

Pages 414 - 422

https://doi.org/10.1145/3593434.3594238

Published: 14 June 2023 Publication History

Abstract

DC-DC converters are often used in electrical systems to keep the output voltage constant. Boost converters are utilized for a variety of purposes, including regenerative braking of direct current motors, portable device applications, and regulated power supplies. Buck converters, on the other hand, are used in sophisticated communications, data communication, and self-regulating power supplies. One of the most crucial elements in the power conversion process is managing the DC-DC converters. This study aims to find out which nonlinear controller, fuzzy or neural network, works best when the output load or boost converter characteristics change. So, in this, we create a boost converter controller using a fuzzy and neural network. The fuzzy controller for this study's converter employs a standard set of rules, whereas the neural network controller employs two hidden layer networks. MATLAB software is then used to reconstruct both controllers. The simulation results show that the fuzzy logic controller has a very long transient and settling period with no steady-state error in both transient and steady-state situations. On the other hand, the neural network controller has a short transient and settling period with a steady-state error.

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Cited By

Jin GMengesha KSon Y(2025)Integral Sliding Mode Control of a DC-DC Boost Converter with UncertaintiesJournal of Electrical Engineering & Technology10.1007/s42835-024-02136-8Online publication date: 11-Jan-2025
https://doi.org/10.1007/s42835-024-02136-8
Karthikeyan SHarish KBalaji SHarikrishnan RAnush C(2024)Modeling and Control of Solar Powered BLDC Motor System with PID and Sheppard Taylor Converter2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN)10.1109/ICPCSN62568.2024.00173(1043-1048)Online publication date: 3-May-2024
https://doi.org/10.1109/ICPCSN62568.2024.00173

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cover image ACM Other conferences

EASE '23: Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering

June 2023

544 pages

ISBN:9798400700446

DOI:10.1145/3593434

Copyright © 2023 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 14 June 2023

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EASE '23

EASE '23: The International Conference on Evaluation and Assessment in Software Engineering

June 14 - 16, 2023

Oulu, Finland

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Cited By

Jin GMengesha KSon Y(2025)Integral Sliding Mode Control of a DC-DC Boost Converter with UncertaintiesJournal of Electrical Engineering & Technology10.1007/s42835-024-02136-8Online publication date: 11-Jan-2025
https://doi.org/10.1007/s42835-024-02136-8
Karthikeyan SHarish KBalaji SHarikrishnan RAnush C(2024)Modeling and Control of Solar Powered BLDC Motor System with PID and Sheppard Taylor Converter2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN)10.1109/ICPCSN62568.2024.00173(1043-1048)Online publication date: 3-May-2024
https://doi.org/10.1109/ICPCSN62568.2024.00173

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