Error minimization based on multi-objective finite control set model predictive control for matrix converter in DFIG

Abstract

Matrix Converter (MC) has many advantages such as capability of bi-directional energy conversion, no need for DC bus and high value filters. However, modulation methods are very difficult and require high computational effort. Therefore, Multi-objective Finite Control Set Model Predictive Control (MFCS-MPC) has been implemented to simplify the complexity of this topology. However, the weakness of this control method is using mathematical model and affected by parameter mismatches due to the external disturbances, frequency and temperature variations. In this study, past errors of rotor current are added to the cost function and the weighting factors are adjusted with the Fuzzy Decision Making (FDM) approach. Due to the combination of these two methods, a robust system is obtained that can operate even in model-plant mismatch. The proposed algorithm is implemented using the TMS320F28335 Digital Signal Processor (DSP), a 32-bit floating-point processor operating at 150 MHz. Results obtained from simulation and experimental setup are compared with the current literature studies and the performance of the proposed method is confirmed.