Improved Model Predictive Torque Control with Reduced Active Prediction Vectors for Voltage Source Inverter Driven Induction Motor Drives

High-performance control, precise torque regulation, and minimal stator current total harmonic distortion (THD) of induction motor drives (IMDs) have always been considered an industrial concern. The conventional finite control set model predictive control (FCS-MPC) strategy suffers from high computational complication, increased torque ripple, and stator current THD, which is employed to drive the voltage source inverter (VSI) based IMD. This paper proposes an optimized method of selecting prediction vectors to minimize the computational cost of the traditional FCS-MPC for a two-level VSI-based IMD. By minimizing the number of prediction vectors from six to three utilizing the proposed strategy, the cost function is assessed for only four vectors. The proposed improved model predictive control (MPC) is based on finite control set predictive torque control (FCS-PTC). The proposed improved MPC strategy also prioritizes the selection of the zero vector by avoiding the phase arm that carries the high current.