Model predictive control has become a powerful and versatile control strategy, particularly effective in controlling multiphase machines. One of its key advantages is the ability to address multiple control objectives by incorporating constraints directly into the cost function. However, this feature typically necessitates the challenging task of tuning weighting factors to balance competing objectives effectively. This paper proposes a sequential model predictive torque control strategy for six-phase induction machines, eliminating the need for weighting factors. The proposed approach simplifies the control design process while maintaining high performance. Simulation and experimental results demonstrate the method's effectiveness, showing accurate torque, flux tracking, and appropriate stator currents regulation in the $\alpha -\beta$ and $x-y$ planes. These results highlight the potential of the proposed control strategy for practical implementation in advanced multiphase drive systems.

The direct matrix converter (DMC) is considered to be an exciting power converter topology option for electric motor drives in industrial applications (elevators, hoists and cranes) and applications where size and weight are critical (e.g., the aerospace industry). Several control techniques have been developed to exploit the DMC’s benefits and achieve the desired performance with classic control techniques, such as field-oriented control and direct torque control, and more sophisticated ones, such as model predictive control and sliding mode control (SMC). SMC is attractive due to its robustness and fast response. However, this control strategy suffers from a phenomenon called chattering. Thus, a solution based on the exponential reaching law (ERL) is implemented to resolve this issue. The proposed method was validated using simulation and experimental results from tests on a three-phase induction machine.

Finite-control-set model predictive control (FCS-MPC) has become widely accepted in multiphase drives due to its adaptability and robust dynamic response. However, multiphase machines, characterized by low secondary plane ($x-y$) impedance, which is absent in their three-phase counterparts, often exhibit poor current quality under conventional FCS-MPC strategies. This paper proposes a novel predictive torque control (PTC) scheme based on virtual vectors to improve ($x-y$) current regulation by ensuring zero average ($x-y$) voltage generation. The proposed method is compared with classic PTC, which cannot achieve proper ($x-y$) current regulation because it uses a single switching state during the sampling period. Experimental validation includes a detailed comparison of torque and flux behavior, ($x-y$) current mean square error, and total harmonic distortion of the fundamental stator currents, demonstrating the effectiveness of the proposed control approach under various operating conditions. Experimental results confirm reductions of approximately 79.7% in computational burden and 98.4% in copper losses when using PTC-VV compared to classic PTC. An asymmetrical six-phase induction machine is used as the case study.

Finite-control-set model predictive control (FCS-MPC) has achieved superiority in managing multiphase induction machines due to its quick dynamic response, control flexibility, and overall good performance. Its advantages, including simplicity, computational efficiency, compensation for system perturbations, and effective handling of multivariable problems, have made it a competitive alternative in various industrial applications. Nevertheless, FCS-MPC has some limitations. It is highly dependent on the accuracy of the predictive model’s parameters. Unfortunately, the estimation of magnetizing inductance, the most critical factor, especially in the weakening field region, has not been studied yet. Focusing on this gap, this article proposes a technique to estimate the magnetizing inductance in the field weakening zone for a six-phase asymmetrical induction machine driven by the FCS-MPC. Experimental tests have verified the effectiveness of the proposed method, considering stator currents and rotor speed tracking, as well as a reduction in the (x − y) currents.

This paper presents a comparative analysis of three-level (3L-NPC) and five-level (5L-NPC) Neutral-Point-Clamped converters using Finite Control Set Model Predictive Control (FCS-MPC) for reactive power compensation. The research addresses a critical gap by providing a direct performance comparison under identical operating conditions, supported by simulation and experimental validation of a 3L-NPC prototype. The study evaluates harmonic performance, dynamic response, and DC-link balance. Results demonstrate that the 5L-NPC topology significantly outperforms the 3L-NPC, achieving a simulated grid current Total Harmonic Distortion (THD) of 3.36% compared to 7.84% for the 3L-NPC. This 57.1% reduction in THD allows the 5L-NPC to comply with the IEEE Std. 519-2022 limit (<5%), whereas the 3L-NPC experimental results (9.9% THD) highlight the impact of practical non-idealities such as dead time and sensor noise. While the 5L-NPC offers superior power quality, it entails higher hardware complexity, evaluating 125 switching states compared to 27 in the 3L-NPC. These findings provide quantitative guidelines for selecting NPC topologies in high-performance grid compensation systems.