一种改进永磁同步电机双矢量模型预测控制策略

永磁同步电机（PMSM）传统的模型预测控制（MPC）策略在一个控制周期内通过遍历计算，因只施加一个电压矢量，使得控制效果并不理想，并且算法计算量也比较大。针对此问题，在已有的两种MPC方法的基础上，提出一种优化方法，使得在保持良好的动静态性能的同时，开关频率也保持在较低水平。该方法通过扇区判断减少计算量，离散过程采用精度更高的龙格-库塔的离散方式，采用拉格朗日乘子法计算占空比。最后通过搭建模型仿真，与已有的两种双矢量MPC方法相比，验证了所提方法的有效性。

An Improved Dual-Vector Model Predictive Control Strategy for Permanent Magnet Synchronous Motor

The traditional model predictive control (MPC) of permanent magnet synchronous motor (PMSM) applies only one voltage vector through ergodic calculation in a control cycle, which makes the control effect is not ideal, and the algorithm has a large amount of calculation. In order to solve this problem, an optimization method is proposed based on the existed two MPC methods, which achieves good dynamic and static performance while reducing switching frequency. This method reduces calculation by judging the sector. Runge-Kutta discrete method with higher precision is used in the discrete process. Lagrange multiplier method is used to calculate duty ratio. Finally, the effectiveness of the proposed method is verified by comparison with the existed two dual-vector MPC methods through model simulation.