Finite state model predictive control for 3×3 matrix converter based on switching state elimination

Model Predictive Control (MPC) with a finite control set has been successfully applied to several power converter topologies and research on predictive control techniques has increased over the last few years. This paper presents a novel model predictive control scheme for the three-phase Direct Matrix Converter based on switching state elimination. The conventional MPC solves a multi-objective optimization problem by minimizing a multi-objective cost function over a one-step horizon. The control performance is strongly affected by the weighting factors used in the cost function, and this is problematic, since no formal method to determine their values has been provided in the literature. A time consuming simulation-based tuning technique is typically used. The proposed method solves this difficulty by eliminating the weighting factors and using a switching state elimination method based on error constraints that have a clear physical interpretation.