A Cascade Fuzzy Maximum Power Point Tracking Algorithm for a Single Phase Photovoltaic Boost DC/DC Converter

Abdullah H. Mughal; Abdulrahman Aliyu; Mohammed Abbas; Waleed M. Hamanah; Luai M. Alhems

doi:10.1109/PEDS63958.2025.11144845

A Cascade Fuzzy Maximum Power Point Tracking Algorithm for a Single Phase Photovoltaic Boost DC/DC Converter

Abdullah H. Mughal
, Abdulrahman Aliyu
, Mohammed Abbas
, Waleed M. Hamanah^*
, Luai M. Alhems

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This paper presents an innovative Cascade Fuzzy Logic Controller (CFLC) specifically designed for DC/DC boost converters in Maximum Power Point Tracking (MPPT) applications. Utilizing MATLAB simulations, we compare the performance of the CFLC against traditional Fuzzy Logic Controller (FLC) and Perturb and Observe (P&O) algorithms. The results indicate that the CFLC outperforms both FLC and P&O methods, demonstrating enhanced response times, minimal overshoot, superior maximum power point efficiency, and improved stability under varying irradiance conditions. This comparative analysis highlights the CFLC's robustness and adaptability, particularly in dynamic environmental scenarios. Additionally, an evaluation of the boost converter output voltage corroborates the CFLC's effectiveness in maintaining optimal voltage levels, thereby maximizing energy conversion efficiency.

Original language	English
Title of host publication	IEEE Power Electronics and Drive Systems, PEDS 2025
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331530501
DOIs	https://doi.org/10.1109/PEDS63958.2025.11144845
State	Published - 2025
Externally published	Yes
Event	15th IEEE International Conference on Power Electronics and Drive Systems, PEDS 2025 - Penang, Malaysia Duration: 21 Jul 2025 → 24 Jul 2025

Publication series

Name	Proceedings of the International Conference on Power Electronics and Drive Systems
ISSN (Print)	2164-5256
ISSN (Electronic)	2164-5264

Conference

Conference	15th IEEE International Conference on Power Electronics and Drive Systems, PEDS 2025
Country/Territory	Malaysia
City	Penang
Period	21/07/25 → 24/07/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 11 Sustainable Cities and Communities

Keywords

Artificial Intelligence
Fuzzy Logic
MPPT
Photovoltaic System
Renewable energy
Smart Cities

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/PEDS63958.2025.11144845

Cite this

Mughal, A. H., Aliyu, A., Abbas, M., Hamanah, W. M., & Alhems, L. M. (2025). A Cascade Fuzzy Maximum Power Point Tracking Algorithm for a Single Phase Photovoltaic Boost DC/DC Converter. In IEEE Power Electronics and Drive Systems, PEDS 2025 (Proceedings of the International Conference on Power Electronics and Drive Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PEDS63958.2025.11144845

Mughal, Abdullah H. ; Aliyu, Abdulrahman ; Abbas, Mohammed et al. / A Cascade Fuzzy Maximum Power Point Tracking Algorithm for a Single Phase Photovoltaic Boost DC/DC Converter. IEEE Power Electronics and Drive Systems, PEDS 2025. Institute of Electrical and Electronics Engineers Inc., 2025. (Proceedings of the International Conference on Power Electronics and Drive Systems).

@inproceedings{c245874e2e78429ba826728ae9d6dd4a,

title = "A Cascade Fuzzy Maximum Power Point Tracking Algorithm for a Single Phase Photovoltaic Boost DC/DC Converter",

abstract = "This paper presents an innovative Cascade Fuzzy Logic Controller (CFLC) specifically designed for DC/DC boost converters in Maximum Power Point Tracking (MPPT) applications. Utilizing MATLAB simulations, we compare the performance of the CFLC against traditional Fuzzy Logic Controller (FLC) and Perturb and Observe (P\&O) algorithms. The results indicate that the CFLC outperforms both FLC and P\&O methods, demonstrating enhanced response times, minimal overshoot, superior maximum power point efficiency, and improved stability under varying irradiance conditions. This comparative analysis highlights the CFLC's robustness and adaptability, particularly in dynamic environmental scenarios. Additionally, an evaluation of the boost converter output voltage corroborates the CFLC's effectiveness in maintaining optimal voltage levels, thereby maximizing energy conversion efficiency.",

keywords = "Artificial Intelligence, Fuzzy Logic, MPPT, Photovoltaic System, Renewable energy, Smart Cities",

author = "Mughal, \{Abdullah H.\} and Abdulrahman Aliyu and Mohammed Abbas and Hamanah, \{Waleed M.\} and Alhems, \{Luai M.\}",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 15th IEEE International Conference on Power Electronics and Drive Systems, PEDS 2025 ; Conference date: 21-07-2025 Through 24-07-2025",

year = "2025",

doi = "10.1109/PEDS63958.2025.11144845",

language = "English",

series = "Proceedings of the International Conference on Power Electronics and Drive Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "IEEE Power Electronics and Drive Systems, PEDS 2025",

address = "United States",

}

Mughal, AH , Aliyu, A , Abbas, M , Hamanah, WM & Alhems, LM 2025, A Cascade Fuzzy Maximum Power Point Tracking Algorithm for a Single Phase Photovoltaic Boost DC/DC Converter. in IEEE Power Electronics and Drive Systems, PEDS 2025. Proceedings of the International Conference on Power Electronics and Drive Systems, Institute of Electrical and Electronics Engineers Inc., 15th IEEE International Conference on Power Electronics and Drive Systems, PEDS 2025, Penang, Malaysia, 21/07/25. https://doi.org/10.1109/PEDS63958.2025.11144845

A Cascade Fuzzy Maximum Power Point Tracking Algorithm for a Single Phase Photovoltaic Boost DC/DC Converter. / Mughal, Abdullah H.; Aliyu, Abdulrahman ; Abbas, Mohammed et al.
IEEE Power Electronics and Drive Systems, PEDS 2025. Institute of Electrical and Electronics Engineers Inc., 2025. (Proceedings of the International Conference on Power Electronics and Drive Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Cascade Fuzzy Maximum Power Point Tracking Algorithm for a Single Phase Photovoltaic Boost DC/DC Converter

AU - Mughal, Abdullah H.

AU - Aliyu, Abdulrahman

AU - Abbas, Mohammed

AU - Hamanah, Waleed M.

AU - Alhems, Luai M.

PY - 2025

Y1 - 2025

N2 - This paper presents an innovative Cascade Fuzzy Logic Controller (CFLC) specifically designed for DC/DC boost converters in Maximum Power Point Tracking (MPPT) applications. Utilizing MATLAB simulations, we compare the performance of the CFLC against traditional Fuzzy Logic Controller (FLC) and Perturb and Observe (P&O) algorithms. The results indicate that the CFLC outperforms both FLC and P&O methods, demonstrating enhanced response times, minimal overshoot, superior maximum power point efficiency, and improved stability under varying irradiance conditions. This comparative analysis highlights the CFLC's robustness and adaptability, particularly in dynamic environmental scenarios. Additionally, an evaluation of the boost converter output voltage corroborates the CFLC's effectiveness in maintaining optimal voltage levels, thereby maximizing energy conversion efficiency.

AB - This paper presents an innovative Cascade Fuzzy Logic Controller (CFLC) specifically designed for DC/DC boost converters in Maximum Power Point Tracking (MPPT) applications. Utilizing MATLAB simulations, we compare the performance of the CFLC against traditional Fuzzy Logic Controller (FLC) and Perturb and Observe (P&O) algorithms. The results indicate that the CFLC outperforms both FLC and P&O methods, demonstrating enhanced response times, minimal overshoot, superior maximum power point efficiency, and improved stability under varying irradiance conditions. This comparative analysis highlights the CFLC's robustness and adaptability, particularly in dynamic environmental scenarios. Additionally, an evaluation of the boost converter output voltage corroborates the CFLC's effectiveness in maintaining optimal voltage levels, thereby maximizing energy conversion efficiency.

KW - Artificial Intelligence

KW - Fuzzy Logic

KW - MPPT

KW - Photovoltaic System

KW - Renewable energy

KW - Smart Cities

UR - https://www.scopus.com/pages/publications/105017002197

U2 - 10.1109/PEDS63958.2025.11144845

DO - 10.1109/PEDS63958.2025.11144845

M3 - Conference contribution

AN - SCOPUS:105017002197

T3 - Proceedings of the International Conference on Power Electronics and Drive Systems

BT - IEEE Power Electronics and Drive Systems, PEDS 2025

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 15th IEEE International Conference on Power Electronics and Drive Systems, PEDS 2025

Y2 - 21 July 2025 through 24 July 2025

ER -

Mughal AH , Aliyu A , Abbas M , Hamanah WM, Alhems LM. A Cascade Fuzzy Maximum Power Point Tracking Algorithm for a Single Phase Photovoltaic Boost DC/DC Converter. In IEEE Power Electronics and Drive Systems, PEDS 2025. Institute of Electrical and Electronics Engineers Inc. 2025. (Proceedings of the International Conference on Power Electronics and Drive Systems). doi: 10.1109/PEDS63958.2025.11144845

A Cascade Fuzzy Maximum Power Point Tracking Algorithm for a Single Phase Photovoltaic Boost DC/DC Converter

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this