Simplified Model Predictive Current Control for Dual Three-Phase PMSM with Low Computation Burden and Switching Frequency

Abstract

Finite-control-set model predictive control (FCS-MPC) has advantages of multi-objective optimization and easy implementation. To reduce the computational burden and switching frequency, this article proposed a simplified MPC for dual three-phase permanent magnet synchronous motor (DTP-PMSM). The novelty of this method is the decomposition of prediction function and the switching optimization algorithm. Based on the decomposition of prediction function, the current increment vector is obtained, which is employed to select the optimal voltage vector and calculate the duty cycle. Then, the computation burden can be reduced and the current tracking performance can be maintained. Additionally, the switching optimization algorithm was proposed to optimize the voltage vector action sequence, which results in lower switching frequency. Hence, this control strategy can not only reduce the computation burden and switching frequency, but also maintain the steady-state and dynamic performance. The simulation and experimental results are presented to verify the feasibility of the proposed strategy.