Abstract: [Objective] Aiming at the problem of control performance degradation due to parameter mismatch in finite-control-set model predictive current control (FCS-MPCC) of permanent magnet synchronous motor, the model reference adaptive system (MRAS) is used to identify the motor parameters to improve the parameter robustness of FCS-MPCC. [Methods] Firstly, the parameter mismatch robustness of FCS-MPCC was analyzed. Then, in order to solve the problem of under-ranking of three parameters identified by the traditional MRAS method, only the two parameters of inductance and flux linkage, which have a greater influence, were identified, so as to make the FCS-MPCC have a stronger parameter robustness. Finally, the impact of the resistance parameters mismatch of the MRAS model on the identification results and the performance of the motor control was analyzed. [Results] In order to verify the effectiveness of the proposed method, simulation analysis was carried out based on Matlab/Simulink platform. MRAS can accurately recognize the actual values of inductance and flux linkage with high recognition accuracy when the model resistance parameters were set correctly. Although FCS-MPCC and MRAS still need to set the resistance parameters, and the mismatch of the resistance parameters has a large impact on the identification results of the flux linkage parameters of MRAS, but because FCS-MPCC has a certain degree of robustness to the parameter changes, this effect was reflected in the FCS-MPCC has little impact. [Conclusion] FCS-MPCC selects the voltage vectors whose cost function is the minimum one, which can weaken effects of parameters mismatch and make FCS-MPCC robustness. As effect of resistance parameters mismatch is weak, only inductance and flux linkage are needed to be identified, so as to avoid the problem of under-ranking. Resistance parameters affect a significant impact on MRAS-based inductance and flux linkage identification, but demonstrate minimal influence on FCS-MPCC.