Adaptive Intelligent Sliding Mode Control of a Photovoltaic Grid-Connected Inverter

Abstract

Adaptive intelligent sliding mode control methods are developed for a single-phase photovoltaic (PV) grid-connected transformerless system with a boost chopper and a DC-AC inverter. A maximum power point tracking (MPPT) method is implemented in the boost part in order to extract the maximum power from the PV array. A global fast terminal sliding control (GFTSMC) strategy is developed for an H-bridge inverter to make the tracking error between a grid reference voltage and the output voltage of the inverter converge to zero in a finite time. A fuzzy-neural-network (FNN) is used to estimate the system uncertainties. Intelligent methods, such as an adaptive fuzzy integral sliding controller and a fuzzy approximator, are employed to control the DC-AC inverter and approach the upper bound of the system nonlinearities, achieving reliable grid-connection, small voltage tracking error, and strong robustness to environmental variations. Simulation with a grid-connected PV inverter model is implemented to validate the effectiveness of the proposed methods.