Model Predictive Current Control for PMSM Based on Fuzzy PID Cost Function
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 condi-tion 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.
finite-control-set model predictive controlcost functionfuzzy controlpermanent magnet synchronous motor
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