An Impact of Model Accuracy on Control Performance in Finite Control Set Model Predictive Current Control for Reluctance Synchronous Motor

The paper presents a finite control set model pre-dictive current control FCS-MPC for reluctance synchronous motor (RSM). Three approaches with different complexity and accuracy of motor models were utilized in the predictive control scheme. Considered algorithms were implemented in a prototype drive with an ARM-Cortex microprocessor and SiC-based voltage source inverter. The Min-Max and Alpha-Betha optimization algorithms was used to reduce the microcontroller resources during the implementation of control schemes. Experimental tests were conducted to indicate the behavior of the developed control algorithms. Angular velocity regulation, load torque compensation, total harmonic distortion, and torque ripple are analyzed.