Optimal Fuzzy logic controller based Genetic Algorithm for control maximum power point tracking for Boost Converter
This paper presents a study on Maximum Power Point Tracking (MPPT) employing a DC-DC boost converter in MATLAB. The approach utilizes a genetic algorithm to determine optimal values for the membership functions (MFs) and the configuration of rules in a Mamdani fuzzy inference system. The fuzzy syste...
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| Main Authors: | , , , , , |
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| Format: | Conference paper |
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Institute of Electrical and Electronics Engineers Inc.
2025
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| Summary: | This paper presents a study on Maximum Power Point Tracking (MPPT) employing a DC-DC boost converter in MATLAB. The approach utilizes a genetic algorithm to determine optimal values for the membership functions (MFs) and the configuration of rules in a Mamdani fuzzy inference system. The fuzzy system is designed to manage the error signal derived from comparing the reference voltage of the Perturb and Observe (P&O) controller with the photovoltaic (PV) voltage. Inputs to the fuzzy controller include the error and its rate of change, with the output controlling the Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) pulses. The optimization aims to minimize the Root Mean Square Error (RMSE) to identify the most effective MFs and rules for the fuzzy controller, ultimately enhancing the MPPT output of the boost converter. ? 2024 IEEE. |
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