Model predictive control (MPC) has received widespread attention as its clear concept and ease of implementation, and this method can simultaneously control multiple nonlinear objectives utilizing a cost function. However, the control accuracy of traditional cost function still lacks rigorous validation. To provide effective theoretical support, this paper proposes a novel visualization evaluation scheme for a detailed analysis of cost function in the form of the sum of the moduli. The analysis results revealed that the cost function did not achieve the ideal control effect of MPC. Then, based on this results, an improved MPC strategy for permanent magnet synchronous motor (PMSM) is further proposed in this paper. This strategy eliminates control errors by transforming the cost function from the traditional αβ two-phase form to the abc three-phase form, thereby improving the control accuracy of MPC. The simulation comparison results validate the effectiveness of the improved MPC strategy.

Model predictive control (MPC), permanent magnet synchronous motor (PMSM), cost function, visualization evaluation.