基于多核并行计算的永磁同步电机有限集模型预测控制策略

Finite Control Set Model Predictive Control of Permanent Magnet Synchronous Motor Based on Multi-Core Parallel Computing

有限集模型预测控制算法存在较长程序执行时间与较短控制周期之间的矛盾,算法执行效率低于传统线性控制算法,进而影响开关频率与控制精度的进一步提高。针对此问题,结合近几年微控制器在多核心领域的发展,以永磁同步电机为被控对象,提出一种基于多核并行计算的有限集模型预测控制策略。由于算法对数据、时序依赖度高,与微控制器中多核心独立运行特点相矛盾,为此,该文设计了双核、四核控制策略架构,并提出数据交换策略和动态标志位。通过搭建实验系统,对所提方法的动稳态性能、附加约束兼容性、程序执行时间进行分析对比,证明了所提方法能够在保持原算法控制性能和控制特点的基础上,有效降低算法执行时间。

Finite control set model predictive control(FCS-MPC)has a contradiction between long program execution time and short control period,and its algorithm execution efficiency is lower than the traditional linear control algorithm,which further affect the improvement of the switching frequency and control accuracy.In order to solve this problem,combined with the development of multi-core microcontrollers in recent years,this paper proposed a multi-core parallel computing based FCS-MPC strategy for permanent magnet synchronous motor.FCS-MPC has a high dependence on data and timing,which contradicts the independent characteristics of multi-core microcontrollers.This paper designed the dual-core and quad-core control architectures,and proposed the data exchange strategy and dynamic flags.With the experimental system,the transient and steady state performance,the additional constraint compatibility,and the program execution time of the proposed method were analyzed and compared.It is proved that the proposed method can effectively reduce the execution time of FCS-MPC strategy while maintaining the performance and characteristics of the original algorithm.