Robust MPPT for Photovoltaics: Interval Type-2 Fuzzy Logic with Experimental Validation

Abstract

Solar photovoltaic systems require MPPT techniques that are robust to rapid irradiance, temperature, and shading variations, whereas conventional fuzzy logic, though effective for nonlinearity, struggles to manage uncertainty. This paper proposes an interval type-2 fuzzy logic controller for MPPT, validated through both MATLAB/Simulink simulations and real-time hardware experiments. By explicitly modeling uncertainty in its membership functions, the proposed controller achieves faster tracking and reduced steady-state oscillations compared to a type-1 fuzzy controller. Experimental tests conducted in Sialkot, Pakistan, demonstrate that the proposed controller increases daily average efficiency from 82.37% to 88.73%. The proposed approach significantly reduces root mean square error (RMSE), mean absolute error (MAE), and integrated error indices, while achieving coefficient of determination (R2) of 0.998 against reference maximum power. These results confirm the effectiveness of IT2-FLC for enhancing the reliability and efficiency of PV MPPT, making it a promising solution for practical renewable energy applications.