基于PID型代价函数的永磁同步电机模型预测电流控制

Model Predictive Current Control for Permanent Magnet Synchronous Motors Based on PID-Type Cost Function

有限集模型预测控制(FCS-MPC)存在控制性能依赖于模型参数准确度的问题。为此,在永磁同步电机FCS-MPC电流控制场合,提出一种比例-积分-微分(PID)型代价函数,包括用以消除稳态电流误差的积分误差代价和具有降低电流方均根误差功能的微分误差代价。在PID型代价函数概念中,可将传统的给定跟踪型代价函数归类为比例误差代价。实验结果证明,采用PID型代价函数的FCS-MPC,能在较大参数变化范围将平均控制误差降为零,并抑制电流纹波,降低FCS-MPC对模型参数的依赖性,同时保留FCS-MPC动态响应快的优点。

The performance of the finite-control-set model predictive control(FCS-MPC)depends on the accuracy of model parameters.Therefore,this paper proposed a PID-type cost function for the FCS-MPC in the current control of the permanent magnet synchronous motors,including the integral cost term to eliminate the steady-state current error and the differential cost term to reduce the root-mean-square current error.In the concept of the PID-type cost function,the traditional reference-tracking cost can be categorized as a proportional cost.Experimental results show that the FCS-MPC current control with the PID-type cost function can reduce the steady-state current error to zero and suppress the current ripple in a wide parameter range.Therefore,the parameter independency of the FCS-MPC can be improved while retaining the advantage of fast dynamic response of the FCS-MPC.