Adaptive Model Predictive Control for Switching Frequency Reduction of Transformerless Inverter-based Systems

Abstract

In this paper, an adaptive finite control set model predictive control (AFCS-MPC) for switching frequency reduction of transformerless inverters is proposed. The new control method improves the conventional finite control set model predictive control (FCS-MPC)  applications in PV system control. The AFCS-MPC does not require using weighting factors as well as no need for external modulation. The idea of the proposed control strategy is to implement a long prediction horizon during steady-state or in the case of a small variation between the reference and controlled variable. On the other hand, in the case of a large dynamic change between the reference and controlled variable, the controller predicts only the first step. In this manner, the controller guarantees the performance of FCS-MPC with a reduced switching frequency. The proposed control method is capable of reducing the average switching frequency of the conventional finite control set model predictive control as per numerous simulation observations. Simulation results are presented using PSCAD/EMTDC platform to verify the performance of the proposed method compared to the standard FCS-MPC.