Weighting-Factor-Less Model Predictive Control with Multi-Objectives for 3-Level Hybrid ANPC Inverter Drives

Hybrid active neutral point clamped (HANPC) inverter has been recently considered in motor drive applications, while its control with multiple objectives remains quite complicated. The finite set model predictive control (MPC) is very attractive for multilevel inverter drives due to its powerful ability to handle multi-objective optimization. However, tuning the weighting factors (WF) with multiple objectives in MPC is quite challenging and time costing. In this paper, a WF-less MPC method for HANPC inverter-fed PMSM drives is proposed. The new control strategy achieves precise current tracking, neutral point potential balance, switching frequency reduction, and switching loss minimization. The algorithm works as a 3-stage procedure to achieve the best decision at each stage, and a current extrapolation method is introduced to enhance the control performance. The effectiveness of the proposed method is validated experimentally on a 3-level HANPC-inverter-fed permanent magnet synchronous motor (PMSM) drive.