Fast two‐vector‐based model‐free predictive current control of permanent magnet synchronous motor

Abstract

Finite control set model predictive control (FCS-MPC) is becoming an important control method in the high-performance control of permanent magnet synchronous motor (PMSM) because of its simple concept, easy implementation, and strong performance. However, the traditional FCS-MPC uses only one basic voltage vector in the whole control cycle, so its steady-state control performance is poor. In addition, FCS-MPC relies significantly on machine parameter correctness. The performance is significantly degraded if the controller parameters do not match the real machine parameters. This study proposed a PMSM fast two-vector model-free predictive control approach to address the abovementioned issues. The process employs no motor parameters and relies only on the system's inputs and outputs. In addition, this method combines the fast vector selection with the two-vector control method, which simplifies the computational effort while improving the steady-state control accuracy at the same time. MATLAB/Simulink built the control system model, the simulation and experimental studies were carried out. The simulation and experimental results confirm the effectiveness of this method.