Weighting-Factorless Sequential Model Predictive Torque Control of a Six-Phase AC Machine

Model predictive control is an exciting control technique that has been applied successfully to multiphase induction machines. The possibility to include several constraints by using only the cost function is one of its main attractive characteristics. However, this latter implies the nontrivial task of adequately tuning the weighting factors to fulfil multiple control objectives properly. This paper proposes a sequential model predictive torque control of a six-phase induction machine that avoids using the weighting factor. Simulation studies are provided to show the effectiveness of this proposal showing good reference tracking of the torque, flux and stator alpha - ss and x - y currents.

Automated summary

Model predictive control is a promising technique for multiphase induction machines, offering the advantage of including various constraints through the cost function. However, tuning the weighting factors to achieve multiple control objectives is a challenging task. This paper presents a sequential model predictive torque control approach for a six-phase induction machine that eliminates the need for weighting factors. Simulation studies demonstrate the effectiveness of this proposal in achieving accurate reference tracking for torque, flux, and stator alpha - ss and x - y currents.