Adaptive Global Fast Terminal Sliding Mode Control of Grid-connected Photovoltaic System Using Fuzzy Neural Network Approach - 2017 PROJECT TITLE :Adaptive Global Fast Terminal Sliding Mode Control of Grid-connected Photovoltaic System Using Fuzzy Neural Network Approach - 2017ABSTRACT:In this paper, an adaptive international quick terminal sliding mode control technique using fuzzy-neural-network (FNN) is proposed for a single-phase photovoltaic (PV) grid-connected transformerless system that is mainly composed of a lift chopper and a dc-ac inverter. A maximum power purpose tracking is accomplished in the boost half in order to extract the most power from the PV array. A global quick terminal sliding mode management strategy is proposed for an H-bridge inverter thus that the tracking error between a grid reference voltage and therefore the output voltage of the inverter will converge to zero in finite time. FNN is employed to estimate the uncertainties of the system in real time since uncertainties in the system are tough to get. The network weights are updated in keeping with the adaptive law in real time to adapt to the variations of system uncertainties, enhancing the robustness of the system. Finally, a PV grid-connected system model is constructed in Simulink to verify the effectiveness of the proposed adaptive global quick terminal sliding mode management method. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest A Unified Control and Power Management Scheme for PV-Battery-Based Hybrid Micro grids for Both Grid-Connected and Islanded Modes - 2017 Adaptive Sliding Mode Control of Standalone Single-Phase Micro grid Using Hydro, Wind and Solar PV Array Based Generation - 2017