Photovoltaic (PV) power generation has been extensively used as a result of the limited petrochemical resources and the rise of environmental awareness. Nevertheless, PV arrays have a widespread range of voltage changes in a variety of solar radiation, load, and temperature circumstances, so a maximum power point tracking (MPPT) method must be applied to get maximum power from PV systems. Sliding mode control (SMC) is effectively used in PV power generation due to its robustness, design simplicity, and superior interference suppression. When the PV array is subject to large parameter changes/highly uncertain conditions, the SMC leads to degraded steady-state performance, poor transient tracking speed, and unwanted flutter. Therefore, this paper proposes a robust intelligent sliding mode MPPT-based high-performance pure sine wave inverter for PV applications. The robust SMC is designed through fast sliding regime, which provides fixed time convergence and a non-singularity that allows better response in steady-state and transience. To avoid the flutter caused by system unmodeled dynamics, an enhanced cuckoo optimization algorithm (ECOA) with automatically adjustable step factor and detection probability is used to search control parameters of the robust sliding mode, thus finding global optimal solutions. The coalescence of both robust SMC and ECOA can control the converter to obtain MPPT with faster convergence rate and without untimely trapping at local optimal solutions. Then the pure sine wave inverter with robust intelligent sliding mode MPPT of the PV system delivers a high-quality and stable sinusoidal wave voltage to the load. The efficacy of the proposed method is validated on a MPPT pure sine wave inverter system by using numerical simulations and experiments. The results show that the output of the proposed PV system can improve steady-state performance and transient tracking speed.
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