Predictive Current Control of a PMSM Three-Level Dual-Vector Model Based on Self-Anti-Disturbance Techniques

Finite control set-model predictive control (FCS-MPC) has become a hotspot for power electronics applications and research in recent years due to its conceptual simplicity, ease of handling system constraints and excellent multivariable control capability. However, the traditional FCS-MPC vector selection direction is more fixed and the steady-state performance of the system is poor, while the speed outer loop uses PI control and the speed regulation effect is easily influenced by the motor parameters and cannot solve the problem of fast and overshoot free at the same time. To address these problems, a three-level two-vector model predictive current control method for permanent magnet synchronous motors is proposed based on a self-anti-disturbance technique. For the speed outer loop, a first-order linear active disturbance rejection control is used instead of the traditional PI control, which solves the problem of overshooting and speed incompatibility and improves the robustness of the system; for the current inner loop, the idea of dual-vector model prediction is introduced to expand the selection range of the voltage vector, making the selection of the voltage vector more accurate, while a vector partitioning strategy is used to reduce the computational burden. The control system is modelled and simulated using MATLAB/Simulink. Simulation and test results show that the method has good parameter robustness, fast dynamic response and satisfactory steady-state performance.