Sequential Model Predictive Torque Control with Virtual Vectors Applied to Six-Phase Induction Machine

Due to their fault-tolerance capability, multiphase induction machines have been garnering increased attention, leading to the evolution of various high-performance control techniques. Many of these are adaptations of strategies from established three-phase induction machines. Finite Control Set Model Predictive Control (FCS-MPC) is known for its fast dynamic response and intuitive formulation. However, multivariable control becomes complex due to properly selecting weighting factors. To tackle this issue, this paper introduces sequential predictive control, avoiding the tuning of the FCS-MPC. Furthermore, it introduces virtual vectors to improve system performance by reducing the secondary plane currents that cause air gap losses. The effectiveness of the proposed control structure is validated through computational simulations.