基于模糊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 PMSM Based on Fuzzy PID Cost Function

针对永磁同步电机控制中有限集模型预测电流控制在参数失配时稳定性能和动态性能有所下降的问题,提出一种基于模糊PID型代价函数的模型预测电流控制方法。该控制方法设计了一种包含比例、积分和微分项的代价函数,将传统的电流误差作为比例项实现转速的跟踪,电流误差的积分作为积分项用来消除预测误差,预测电流的差值作为微分项减小转速纹波。同时使用加入了滤波器的模糊控制对PID参数进行动态调整。该控制方法可以在参数失配的情况下降低转速振荡,提高动态响应能力,降低参数失配对控制器性能的影响,同时保留在参数匹配时的各项性能。仿真与实验结果表明,该方法较传统有限集模型预测电流控制在参数失配时有更快的响应速度、更小的转速振荡和更好的负载突变响应。

In the control of permanent magnet synchronous motor,the stability and dynamic performance of the finite set model predictive current control decrease when the parameters are mismatched.A model predictive current control method based on fuzzy PID cost function is proposed.A cost function containing proportional,integral and differential terms is designed.The traditional current error is used as a proportional term to realize the speed tracking.The integral of the current error is used as an integral term to eliminate the prediction error.The difference of the predicted current is used as a differential term to reduce the speed ripple.At the same time,fuzzy control with filter is used to adjust PID parameters dynamically.This control method can reduce the speed oscillation under the condition of parameter mismatch,improve the dynamic response ability,reduce the influence of parameter mismatch on the performance of the controller,and retain the performance under the condition of parameter adaptation.Simulation and experimental results show that the proposed method has faster response speed,smaller speed oscillation and better response to load change than the traditional finite set model when parameters are mismatched.