Performance of Classical and Fuzzy MPPT Controllers in PV Pumping Systems under Fast Weather Variations

Abstract

This study examines four MPPT strategies for a solar pumping application subjected to rapid and simultaneous fluctuations in irradiance and temperature. These variations influence the torque and rotational speed of the Permanent Magnet DC (PMDC) motor. The conventional Incremental Conductance (IC) and Perturb and Observe (P&O) algorithms, which use reference-voltage generation, are compared with Takagi-Sugeno (FL-TS) and Mamdani (FL-Mamdani) fuzzy controllers. The conversion chain includes a photovoltaic array, a boost converter, and a PMDC motor that drives a centrifugal pump. All controllers and system components were modelled and simulated using MAT-LAB/Simulink. The results show that the fuzzy controllers provide improved robustness and faster tracking. Fuzzy MPPT structures typically use the gradient of the power-voltage characteristic, E = d P /d V , and its variation as input variables. The proposed formulation instead employs the gradient of the power-current characteristic, E = d P /d I , and its variation, thereby improving stability and dynamic response. Response times of 85.69 ms and 61.07 ms are obtained with FL-Mam and FL-TS, respectively, compared with 320.06 ms for IC and 276.63 ms for P&O. The boost converter also achieves an efficiency of approximately 97%.