针对表贴式永磁同步电机(PMSM)多步模型预测电流控制过程中运算量大的问题，提出一种成本函数优化计算的多步模型预测控制。成本函数优化计算采用事件触发机制，通过设置成本函数阈值动态精简多步预测的运算量。仿真结果表明：成本函数优化计算的多步模型预测电流控制性能良好，与传统方法完全等价，控制效果相当。基于STM32H743单片机平台，优化方法和传统方法单控制周期执行时间。试验结果表明：对于多步预测，优化算法可减少单控制周期执行时间，两步预测减小至77.71%，三步预测减小至53.95%，四步预测减小至39.76%，五步预测减少至33.48%，在控制性能与传统方法相当的条件下，提高系统实时性能。

Aiming at the problem of large amount of calculation in the process of multi-step model predictive current control of surface mounted permanent magnet synchronous motor (PMSM), a multi-step model predictive control with optimal calculation of cost function is proposed. The optimization calculation of cost function adopts the event trigger mechanism, and the calculation amount of multi-step prediction is dynamically reduced by setting the threshold of cost function. Simulation results show that the multi-step model predictive current control performance of cost function optimization calculation is good, which is completely equivalent to the traditional method, also the control effect is equivalent. Based on STM32H743 single chip microcomputer platform, the optimization method and traditional method single control cycle execution time. Experimental results show that for multi-step prediction, the optimization algorithm can reduce the single control cycle execution time, two-step prediction to 77.71%, three-step prediction to 53.95%, four-step prediction to 39.76% and five-step prediction to 33.48%. It is shown that the control performance is the same as traditional calculation method, but the real-time performance is improved.

西安市碑林区科技计划项目(GX2252)