Implementation of Fuzzy Logic Controller for Maximum Power Point Tracking (MPPT) Control

In this paper, we investigate the application of fuzzy logic controllers for regulating Maximum Power Point Tracking (MPPT) systems. The study delves into the fundamental operating principles of fuzzy logic controllers and demonstrates their implementation methodology for this specific control challenge. Key implementation aspects include designing membership functions for input variables (typically voltage/current errors) and output variables (duty cycle adjustments), followed by developing rule bases using linguistic variables like "positive big," "negative small" etc. We further examine the critical importance of MPPT systems and their extensive applications in renewable energy domains, particularly in solar photovoltaic systems where they maximize power extraction under varying environmental conditions. The research concludes by analyzing performance optimization strategies through fuzzy logic controllers, focusing on algorithm tuning parameters like scaling factors and rule weight adjustments to better meet the dynamic requirements of modern renewable energy systems. Implementation examples may include real-time duty cycle modulation using PWM signals based on fuzzy inference system outputs.