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A Non-Isolated High Gain DC-DC converter fed from 1.2kW PEMFC is designed to boost the fuel cell voltage. The Feed-forward Neural Network based MPPT controller algorithm is implemented to adjust the duty cycle of DC-DC converter in order make sure optimum power extraction from PEMFC whose result is compared with Fuzzy Logic Controller. The boosted DC voltage is inverteted to drive BLDC motor by three phase inverter. The inverter switches are triggered with switching pattern generated by SPWM technique according to the Hall sensor signals placed at stator of BLDC motor to find the position of rotor. The simulation anlysis has been carried out using MATLAB (R2017a)/Simulink platform and discussed the results.

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This paper presents the fuzzy-based Space Vector Pulse Width Modulation (SVPWM) for 5-level Neutral Point Clamped inverter with hybrid energy source fed grid connected system. The proposed scheme is energized using Photovoltaic and Wind energy system combination. The Neural Network-(NN) based Maximum Power Point Tracking algorithm (MPPT) has been implemented to track maximum power under different operating conditions. First, we proposed fuzzy-based SVPWM, which is developed for 5-level NPC inverter to provide voltage and current control, reduced THD, predetermined switching pattern, capacitor voltage unbalance minimization and maintain good control under nonlinearities and suspicions of PV-Wind energy connected hybrid system. Second, we proposed the inverter output voltage, which has been synchronized with grid connected system using split inductor (SI). The reference voltages for SVPWM implementation were obtained using feedback current control method. Third, we proposed different solar radiations, the proposed system has attained better performance by trailing maximum power from hybrid energy system. The simulation and experimental responses have been validated using Matlab/simulink and FPGA processor.