This study designs a novel nonlinear adaptive controller (NAC) of photovoltaic inverter in order to generate the maximum energy of solar power under different condition. Inverter nonlinearities, uncertain grid/inverter parameters, as well as inverter modelling uncertainties are aggregated into a perturbation. Then, a linear extended state observer (ESO), is applied for estimate the perturbation online. Meanwhile, a state feedback controller is used to calculate the perturbation in the real-time. Particularly, its optimal control parameters are effectively and efficiently tuned by a novel meta-heuristic algorithm, called democratic joint operations algorithm (DJOA), such that a satisfactory control property could be resulted in. Case studies verifies the effectiveness and advantages of NAC compared to conventional linear control, e.g., PID controller, and typical nonlinear control, e.g., feedback linearization controller (FLC), under solar irradiation variation and temperature variation.

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