Fuzzy-based self-tuning model predictive direct power control of grid-connected multilevel converters

This paper proposes a self-tuning model predictive direct power control (MPDPC) strategy for power flow control and power quality improvement in grid-connected power converters. At each sampling instant, a fuzzy logic controller is used to determine online the best weighting factor values for a given operating point. These values are then used to solve the multi-objective optimal control problem associated to the MPDPC. The optimal solution that minimizes the multi-objective cost function is chosen as the input (power switch state). The proposed method is examined through a case study and verified numerically via MAT LAB SIMULINK. A comparative study is conducted to demonstrate the effective performance of this approach. As a result of the proposed weighting factor online tuning, an improved performance in terms of total harmonic distortion and average switching frequency is attained when compared with fixed weighting factors.