A Model-Free Predictive Control Method for Grid-Tied Inverter Based on Discrete Space Vector

Model-based predictive control that highly depends on system parameters has been widely investigated. In contrast, model-free predictive current control (MFPCC) can be performed based on input or output measured data, rather than on any system model information, hence eliminating the influence of parameter uncertainties. In such a strategy, the current gradients due to each of the possible voltage vectors are stored and used to predict future currents. In this paper, a model free predictive control method based on discrete space vector modulation is used, which increases the effective vector control set by constructing a virtual vector which is composed of linear combination of real vectors. The THD of grid connected current is reduced. Simulation and experimental results confirmed the effectiveness of the proposed method.