Cost function-based modulation scheme of model predictive control for VIENNA rectifier

Abstract

Finite control set model predictive control (FCS-MPC) has been widely used in the control of grid-connected converters with the advantages of fast dynamics, multi-objective control, and easy implement. However, the conventional FCS-MPC bears with variable switching frequency, high current ripple and computational burden. An improved current model predictive with the cost function-based modulation scheme (CFM-MPC) is proposed for a three-phase three-level VIENNA rectifier to improve the power quality. First, the mathematical model and voltage vector are given according to the principle of deadbeat control. Then, the voltage vector of different voltage vectors are selected according to the location of the voltage vector reference, and the switching action time of the selected are directly calculated by the inversely proportional with cost function value of the selected vectors. It remains the merits of both the conventional MPC and space vector pulse width modulation schemes to track the optimum voltage vector without increasing the computational burden. Finally, a comparative study with the proposed CFM-MPC and conventional FCS-MPC has been conducted to verify the superiority of the proposed scheme. The results show the proposed CFM-MPC has the advantages of lower power ripple, fixed switching frequency, lower total harmonic distortion and neutral point potential balance.