Weighting-factor-free sequential predictive torque control using virtual vectors in six-phase IM

Abstract

Finite-control-set model predictive torque control of multiphase induction machines is often limited by heuristic tuning of weighting factors and inadequate secondary-plane current regulation. To address these limitations, this paper proposes a weighting-factor-free sequential model predictive torque control strategy with virtual voltage vector synthesis (SMPTC-VV) for six-phase induction machine drives supplied by dual two-level voltage source inverters. The proposed scheme employs a sequential optimisation structure that removes weighting factors from the cost function formulation. Virtual voltage vectors are incorporated to suppress non-torque-producing currents in the x−y plane, enabling simultaneous regulation of electromagnetic torque, stator flux, and secondary-plane currents. Experimental validation under steady-state and dynamic conditions, including ±25% magnetising inductance mismatch, demonstrates accurate torque and flux regulation, fast transient response, and improved current quality. The proposed strategy achieves improvements of 10.08% and 53.41% in THDα, and 54.26% and 69.21% in THDa, compared to SMPTC and classical PTC, respectively. In addition, flux regulation is improved by 28.03% and 31.13% relative to SMPTC and classical PTC, respectively, while non-torque-producing x−y currents are improved by 75.40% and 82.58% with respect to SMPTC and classical PTC. The computational effort is limited to 966 floating-point operations per sampling period, corresponding to improvements of 50.66% and 75.66% relative to SMPTC and classical PTC, respectively. The results demonstrate an efficient and experimentally validated predictive torque control solution for high-performance multiphase drives.