Maximum Power Point Tracking for Brushless DC Motor-Driven Photovoltaic Pumping Systems Using a Hybrid ANFIS-FLOWER Pollination Optimization Algorithm

Maximum Power Point Tracking for Brushless DC Motor-Driven Photovoltaic Pumping Systems Using a Hybrid ANFIS-FLOWER Pollination Optimization Algorithm

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In this research paper, a hybrid Artificial Neural Network (ANN)-Fuzzy Logic Control (FLC) tuned Flower Pollination Algorithm (FPA) as a Maximum Power Point Tracker (MPPT) is employed to amend root mean square error (RMSE) of photovoltaic (PV) modeling.Moreover, Gaussian membership functions have been considered for fuzzy controller design.This paper interprets the Luo converter occupied brushless DC Síndrome de personalidade interictal na epilepsia do lobo temporal não-dominante: relato de caso Interictal personality syndrome in temporal lobe epilepsy: case report motor (BLDC)-directed PV water pump application.

Experimental responses certify the effectiveness of the suggested motor-pump system supporting diverse operating states.The Luo converter, a newly developed DC-DC converter, has high power density, better Evaluation of the ECOSSE Model for Estimating Soil Respiration from Eight European Permanent Grassland Sites voltage gain transfer and superior output waveform and can track optimal power from PV modules.For BLDC speed control there is no extra circuitry, and phase current sensors are enforced for this scheme.

The most recent attempt using adaptive neuro-fuzzy inference system (ANFIS)-FPA-operated BLDC directed PV pump with advanced Luo converter, has not been formerly conferred.