ArticleScientific reports2025
Hybrid fuzzy logic approach for enhanced MPPT control in PV systems.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Advanced PV-enabled heat generation system with precise thermal power regulation.Scientific reports · 2026Article
- Optimization of fuzzy logic controller in the converter of a standalone solar power system using the firefly algorithm.Scientific reports · 2026Article
- Current sensorless MPPT method with battery management for PV based single phase standalone system.Scientific reports · 2026Article
- MPPT algorithms for grid-connected solar systems including deep learning approaches.Scientific reports · 2026Article
- Fuzzy controller-driven pattern search optimization for a DC-DC boost converter to enhance photovoltaic MPPT performance.Scientific reports · 2025Article
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Authors and funding
9 authors.
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Abstract
This paper provides an in-depth analysis of photovoltaic (PV) system control within the MATLAB/Simulink environment, focusing on optimizing Maximum Power Point Tracking (MPPT) algorithms for enhanced efficiency under dynamic conditions. While conventional algorithms are widely used, their performance is limited under fluctuating conditions. To address this, we propose a novel hybrid approach combining Incremental Conductance with Fuzzy Logic Control (FLC), utilizing two innovative input variables: the sum of Conductance and Incremental Conductance (SInC) and its rate of change (CSI). The performance of the proposed algorithm, in comparison to other hybrid FLC methods, is evaluated through simulations using a boost converter under dynamic conditions, including abrupt irradiance changes and load variations. The results demonstrate that the proposed hybrid algorithm achieves superior performance, with an average MPPT efficiency of 97.7%, a convergence time of 53.5 ms, and an RMS of 97.8%, outperforming both conventional and other hybrid techniques. This work advances PV system control by providing a robust and adaptive solution for maximizing power extraction under diverse operating conditions.
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