Investigation and Analysis of Fuzzy Logic Controller Method on DC-DC Buck-Boost Converter
DOI:
10.29303/jppipa.v11i1.9744Published:
2025-02-08Issue:
Vol. 11 No. 1 (2025): JanuaryKeywords:
Buck – boost, DC-DC converter, Fuzzy logic controller, Mamdani, SugenoResearch Articles
Downloads
How to Cite
Downloads
Metrics
Abstract
This study evaluates the performance of PID, Mamdani FLC, and Sugeno FLC controllers on a DC-DC Buck-Boost Converter to determine their suitability for various control applications. The Buck-Boost Converter, operating in conventional configuration, was modeled using MATLAB/Simulink with parameters: input voltage (12 V), output voltage (24 V), resistor (6.5 Ω), capacitor (1.5 µF), and inductor (10 µH). The converter's switching frequency was set at 20 kHz to ensure stability under varying load and input conditions. PID control was implemented using the Ziegler-Nichols tuning method, while fuzzy controllers utilized Gaussian membership functions and 3×3 fuzzy rule bases. Mamdani employed the centroid defuzzification method, whereas Sugeno used weighted average defuzzification. The simulation tested performance metrics, including rise time, overshoot, output stability, and voltage ripple, under conditions of load and input voltage variations. Results show that PID achieved the fastest rise time (72.452 ms) but exhibited higher sensitivity to input changes. Sugeno provided the most stable output with minimal ripple, while Mamdani demonstrated greater adaptability but less stability compared to Sugeno. Statistical analysis confirmed significant differences in rise time but no differences in overshoot across methods. These findings highlight the strengths of each method, with Sugeno being optimal for stability and precision, PID for fast response, and Mamdani for complex fuzzy logic applications.
References
Abdulla, S. C. (2022). Comparative Assessment of PID, Fuzzy Logic and ANFIS Controllers in an Automatic Voltage Regulator of A Power System. Jordan Journal of Electrical Engineering, 8(4), 379. https://doi.org/10.5455/jjee.204-1664025424
Ahmed, T. (2020). Analysis and Design of A Fuzzy Controller and Performance Comparison between the PID Controller and Fuzzy Controller. International Journal of Scientific & Technology Research, 9(10), 271–277. Retrieved from www.ijstr.org
Al-attwani, S. H. M., Teke, M., Bektaş, E., Yaseen, E. S. Y., Bektaş, Y., & Civelek, Z. (2024a). The Comparison Study of PI and Sliding Mode Control Techniques for Buck-Boost Converters. Nigde Omer Halisdemir University Journal of Engineering Sciences, 13(4), 1435–1442. https://doi.org/10.28948/ngumuh.1459414
Al-Attwani, S. H. M., Teke, M., Yaseen, E. S. Y., Bektaş, E., & Gökşenli, N. (2024b). Enhancing Buck-Boost Converter Efficiency and Dynamic Responses with Sliding Mode Control Technique. Journal of Techniques, 6(2), 48–57. https://doi.org/10.51173/jt.v6i2.2530
Andrianto, R., Purnomo, N., & Irawan, Y. (2024). Application of Fuzzy Logic Mamdani in IoT-Based Air Quality Monitoring Systems. Indonesian Journal of Computer Science, 13(5). https://doi.org/10.33022/ijcs.v13i5.4291
Benzaouia, S., Rabhi, A., Benzaouia, M., Oubbati, K., & Pierre, X. (2024). Design, Assessment and Experimental Implementation of a Simplified FLC for Hybrid Energy Storage System. Journal of Energy Storage, 84, 110840. https://doi.org/10.1016/j.est.2024.110840
Bhattacharya, S. C., & Kumar, S. (1997). Renewable Energy Technologies in Asia: A Review of Current Status. Second ASEAN Renewable Energy Conference, 5(2), 1–9. https://doi.org/10.51594/estj/v5i2.800
Cai, H. (2023). Full Results of the T Test and/or ANOVA Test for Figures. https://doi.org/10.5281/zenodo.7731191
Devita, R., & Defit, S. (2024). Accurately Determining Labor Test Results Using the Rough Set Method. Jurnal Penelitian Pendidikan IPA, 10(4), 1723–1730. https://doi.org/10.29303/jppipa.v10i4.7069
Dewi, S., Surjoputro, A., & Suhartono, S. (2023). Use of TRIZ Applications to Achieve Systematic Innovation Through Innovative Problem Solving in Hospitals. Jurnal Penelitian Pendidikan IPA, 9(9), 644–654. https://doi.org/10.29303/jppipa.v9i9.4921
Dharavath, A., & Pradabane, S. (2024). Design and Analysis of a Novel Bidirectional DC-DC Converter with Ultra-Conversion Ratio and Reduced Current Stress. International Journal of Circuit Theory and Applications, n/a(n/a). https://doi.org/https://doi.org/10.1002/cta.4308
Duong, H. Q., Nguyen, Q. H., Nguyen, D. T., & Nguyen, L. V. (2022). PSO Based Hybrid PID-FLC Sugeno Control for Excitation System of Large Synchronous Motor. Emerging Science Journal, 6(2), 201–216. https://doi.org/10.28991/ESJ-2022-06-02-01
Ennajih, E., Allali, H., Jarmouni, E., & Ennaoui, I. (2024). Comparing Fuzzy Logic and Backstepping Control for a Buck Boost Converter in Electric Vehicles. International Journal of Power Electronics and Drive Systems, 15(2), 883–891. https://doi.org/10.11591/ijpeds.v15.i2.pp883-891
Eswaraiah, B., & Balakrishna, K. (2024). Design and Development of Different Adaptive MPPT Controllers for Renewable Energy Systems: A Comprehensive Analysis. Scientific Reports, 14(1), 21627. https://doi.org/10.1038/s41598-024-72861-7
Fayaz, M., Ullah, I., & Kim, D. (2019). An Optimized Fuzzy Logic Control Model Based on a Strategy for the Learning of Membership Functions in an Indoor Environment. Electronics, 8(2). https://doi.org/10.3390/electronics8020132
Flatley, P. (2023). Advancements in Renewable Energy Technologies: A Comprehensive Review. American Engineering Journal, 1, 1. Retrieved from http://americanengineeringjournal.com
Gaozhong, Z., Shulin, L., & Bin, W. (2024). Output Ripple Voltage Analysis of Quadratic Buck–Boost Converters with Switched Inductor Network in the Entire Dynamic Range. IETE Journal of Research, 70(7), 6539–6551. https://doi.org/10.1080/03772063.2023.2284954
Hashemzadeh, S. M., Hosseini, S. H., Babaei, E., & Sabahi, M. (2022). Design and Modelling of a New Three Winding Coupled Inductor Based High Step-Up DC–DC Converter for Renewable Energy Applications. IET Power Electronics, 15(13), 1322–1339. https://doi.org/10.1049/pel2.12307
Ibrahim, W. I., Hamid, M. I., Mohamed, M. R., Ghazali, M. R., & Ismail, R. M. T. R. (2023). Sensorless Fuzzy Logic Controller (FLC) Based Maximum Power Point Tracking (MPPT) Algorithm for Hydrokinetic Energy Harnessing. IET Conference Proceedings. https://doi.org/10.1049/icp.2022.2649
Kamis, N. N., Ahmad, S., Embong, A. H., & Sulaeman, E. (2022). Error Driven Fuzzy Logic Controller (FLC) for Spherical Mobile Robot: Simulation & Experimental Performance Analysis. IOP Conference Series: Materials Science and Engineering, 1244(1), 12005. https://doi.org/10.1088/1757-899X/1244/1/012005
Kodaloğlu, F. A., & Kodaloğlu, M. (2023). Fuzzy Logic Control (FLC) for a Yarn Conditioning System. International Journal of Engineering and Innovative Research, 5(3), 170–179. https://doi.org/10.47933/ijeir.1226464
Kumar, K. A., Sreeja, N. S., & L, N. B. (2024). A Fuzzy Logic Approach for Ripple Minimization and Power Factor Correction in LED Lighting Systems. 2024 IEEE 4th International Conference on Sustainable Energy and Future Electric Transportation (SEFET), 1–6. https://doi.org/10.1109/SEFET61574.2024.10718106
Kumar, N. K. (2024). F-Test and Analysis of Variance (ANOVA) in Economics. Mikailalsys Journal of Mathematics and Statistics, 2(3), 102–113. https://doi.org/10.58578/mjms.v2i3.3449
Lainfiesta, M., & Zhang, X. (2020). Frequency Stability and Economic Operation of Transactive Multi-Microgrid Systems with Variable Interconnection Configurations. Energies, 13(10). https://doi.org/10.3390/en13102485
Lin, H-T. (2023). Symmetric Trapezoidal Approximations of Fuzzy Numbers Under a General Condition. Soft Computing. https://doi.org/10.21203/rs.3.rs-1905887/v1
Maity, S., Ghosh, S., Pal, R., Saha, S., Samanta, S., Guha, S., Mondal, R., Sau, R., Pan, S., Das, A., & Maity, J. (2019). Performance Analysis of Fuzzy Logic Controlled DC-DC Converters. International Conference on Communication and Signal Processing, 165–171. https://doi.org/10.1109/ICCSP.2019.8698113
Makoundi, D., Dieu, C., Shuting, W., Bolin, Z., & Makoundi, D. (2024). Design of a Variable Voltage Buck-Boost DC-DC Converter Based on PWM for Micro-Grid Load. Saudi Journal of Engineering and Technology, 9(9), 451–458. https://doi.org/10.36348/sjet.2024.v09i09.004
Mazibukol, N., Akindejil, K. T., & Sharma, G. (2022). Implementation of a Fuzzy Logic Controller (FLC) for Improvement of an Automated Voltage Regulators (AVR) Dynamic Performance. 2022 IEEE PES/IAS PowerAfrica, 1–5. https://doi.org/10.1109/PowerAfrica53997.2022.9905407
Raghavendra, K. V. G., Zeb, K., Muthusamy, A., Krishna, T. N. V., Kumar, S. V. S. V. P., Kim, D.-H., Kim, M.-S., Cho, H.-G., & Kim, H.-J. (2020). A Comprehensive Review of DC–DC Converter Topologies and Modulation Strategies with Recent Advances in Solar Photovoltaic Systems. Electronics, 9(1), 31. https://doi.org/10.3390/electronics9010031
Razali, N. S. I., Gunawan, T. S., Yusoff, S. H., Habaebi, M. H., Ibrahim, S. L., & Sapihie, S. N. M. (2023). Voltage Instability and Voltage Regulating Distribution Transformer Assessment Under Renewable Energy Penetration for Low Voltage Distribution System. Indonesian Journal of Electrical Engineering and Informatics, 11(3), 673–684. https://doi.org/10.52549/ijeei.v11i3.4857
Restiani, Y., & Purwadi, J. (2024). Support Vector Machine for Classification : A Mathematical and Scientific Approach in Data Analysis. Jurnal Penelitian Pendidikan IPA, 10(11), 9896–9903. https://doi.org/10.29303/jppipa.v10i11.8122
Sharma, N. M. K. T. A. G. (2022). Modeling and Performance Analysis of an Automatic Voltage Regulator (AVR) Using Model Predictive Controller (MPC). 2022 IEEE PES/IAS PowerAfrica. https://doi.org/10.1109/powerafrica53997.2022.9905313
Simo, A., Dzitac, S., Frigura-Iliasa, F. M., Frigura-Iliasa, M., Meianu, D., & Ionescu, V. M. (2022). Fuzzy-Logic Controller for Smart Drives. Procedia Computer Science, 214(C), 1396–1403. https://doi.org/10.1016/j.procs.2022.11.322
Sugiharto, B., Harkim, H., Simanungkalit, R. V., Siregar, I., & Andriani, M. (2023). Artificial Intelligence (AI) Architecture for Integrated Smart Digital Banking System. Jurnal Penelitian Pendidikan IPA, 9(10), 876–882. https://doi.org/10.29303/jppipa.v9i10.4645
Téllez-Velázquez, A., & Miranda-Luna, R. (2023). Comparative Analysis of Clustering Methods for Fuzzy Classifiers Simplification. Computación Y Sistemas, 27(1). https://doi.org/10.13053/cys-27-1-4530
Voskoglou, M. G. (2022). Fuzzy Logic in Control Theory. Digital Transformation Technology, 217–228. https://doi.org/10.1007/978-981-16-2275-5_13
Wahyuni, D., Sumarminingsih, E., & Astutik, S. (2022). Fuzzy Sugeno Method for Opinion Classification Regarding Policy of PPKM and Covid-19 Vaccination. Jurnal Penelitian Pendidikan IPA, 8(5), 2210–2215. https://doi.org/10.29303/jppipa.v8i5.1958
Yang, X.-S. (2024). Modeling and Simulation by Simulink®. Elsevier BV. https://doi.org/10.1016/b978-0-44-314084-6.00016-4
Yin, X.-X., & Hadjiloucas, S. (2023). Digital Filtering Techniques Using Fuzzy-Rules Based Logic Control. Journal of Imaging, 9. https://doi.org/10.3390/jimaging9100208
Yuan, F., Hao, R., You, X., & Xiang, P. (2023). A High Voltage Gain Soft-Switching Bidirectional DC-DC Converter with Wide Range Using Resonant Network. IEEE Transactions on Power Electronics, 38(11), 14099–14114. https://doi.org/10.1109/TPEL.2023.3309012
Zangeneh, M., Aghajari, E., & Forouzanfar, M. (2020). A Review on Optimization of Fuzzy Controller Parameters in Robotic Applications. Iete Journal of Research, 1–10. https://doi.org/10.1080/03772063.2020.1787878
Author Biographies
I Ketut Wiryajati, Mataram University
I Nyoman Wahyu Satiawan, Mataram University
I Made Budi Suksmadana, Mataram University
Bagas Briantara Putra Wiwaha, Mataram University
License
Copyright (c) 2025 I Ketut Wiryajati, I Nyoman Wahyu Satiawan, I Made Budi Suksmadana, Bagas Briantara Putra Wiwaha

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with Jurnal Penelitian Pendidikan IPA, agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY License). This license allows authors to use all articles, data sets, graphics, and appendices in data mining applications, search engines, web sites, blogs, and other platforms by providing an appropriate reference. The journal allows the author(s) to hold the copyright without restrictions and will retain publishing rights without restrictions.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in Jurnal Penelitian Pendidikan IPA.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).