Simplified Finite Control Set Model Predictive Control Strategy Based on Historical Data

Recently, the finite control set model predictive control (FCS-MPC) strategy has been widely used in power electronics and motor drives. However, the implementation of the traditional FCS-MPC strategy needs to traverse all possible switch combinations, which greatly increases the computational burden of the system. In order to address this problem, this paper proposes a simplified FCS-MPC strategy based on historical data to enhance the performance of the system. In the proposed strategy, the historical data of the optimal vector in the last fundamental frequency period is stored and it is then utilized as the reference when selecting the optimal vector in the current fundamental frequency period. Also, the optimal vector is selected from the adjacent vectors and the zero vector. A simulation model of a three-phase LCL-type grid-connected inverter is established to verify the performance of the proposed control strategy.