Model Predictive Control for Induction Motor Drives Based on Satisfactory Optimization

This paper introduces a novel Satisfactory Optimization Model Predictive Control (SOMPC) strategy for induction motors, aimed at addressing the issue of complex weight coefficient adjustments and achieving low switching frequency control. The characteristics of the three-level inverter drive system were studied, and a model predictive control strategy based on hierarchical priority was proposed, focusing on excitation current, torque current, and midpoint voltage as the main optimization indicators, with switching frequency as an auxiliary optimization indicator. Additionally, a method for evaluating the optimal switching state using the maximum lingering time in the low priority level was introduced. The proposed SOMPC strategy significantly reduces the system's switching frequency while maintaining minimal fluctuations in motor excitation and torque. Experimental results demonstrate that the induction motor, driven by the three-level inverter based on satisfactory optimization model predictive control, exhibits excellent dynamic and steady-state performances, with an average switching frequency around 400Hz.