Finite Control Set Model Predictive Field-Oriented Control For Three-Phase Induction Motor Drives

Abstract

Field-oriented control is one of the well-established vector control strategies for induction motor drives. However, its cascaded structure and requirement of a modulator for constant switching frequency operations makes it complex and computationally expensive. Model predictive control (MPC) is a novel control strategy used for AC motor drives. In this paper, a finite control set model predictive control (FCS-MPC) based field-oriented control (FOC) is presented. The Finite control set model predictive field-oriented control (FCS-MPFOC) utilizes a cost function that quantifies the error between the reference and anticipated current values for all the potential voltage vectors of the voltage source inverter. The voltage vector that generates the lowest value of the cost function is directly implemented on the inverter to produce the drive voltage. The efficiency of the proposed method is authenticated by using a three-phase induction motor, fed via a two-level three-phase voltage source inverter in the MATLAB/Simulink environment under various speeds, load torque, and model parameter mismatch situations. In order to authenticate the performance of the proposed strategy, it is compared with traditional model predictive torque control. Simulation results show that the proposed method performed significantly well in total current harmonic distortion, flux and torque ripples, switching frequency, and parameter variations.