Two-Vector-Based Model Predictive Torque Control Without Weighting Factors for Induction Motor Drives

Abstract

Conventional model predictive torque control (MPTC) suffers from weighing factor tuning work and relatively high torque ripple, due to the different units of torque and stator flux and the limited number of voltage vectors. This paper proposes an improved MPTC without the use of weighting factor. The torque and flux magnitude references are converted into an equivalent reference vector of stator flux, hence eliminating the weighting factor of stator flux in conventional MPTC. Furthermore, two voltage vectors are applied during one control period to achieve better steady-state performance. Different from prior method using an active vector and a zero vector, the selected voltage vectors may be two nonzero vectors in the proposed method, which provides more opportunities to reduce both torque and flux ripples. The durations of the selected voltage vectors are determined based on the principle of stator flux error minimization. Both simulation and experimental results are presented to validate the effectiveness of the proposed method.