Cascaded Finite State Control for a Five-Phase Induction Machine

The area of Finite State Model Predictive Control (FSMPC) has seen a rapid development in recent years. In particular, its application to multiphase induction machine drives has received attention due to the specific advantages of such systems. The FSMPC method has been shown to be flexible thanks to the combination of a model and a cost function. However, the selection of the weighting coefficients in the cost function remains an obstacle for practitioners. Existing tuning methods for weighting coefficients require a large dataset obtained by extensive experimentation. In this paper, a cascaded structure providing a means for cost function self tuning is proposed. Tests are conducted with a five-phase induction machine connected to a mechanical load. The results show that, for each speed and load, the cascaded structure yields weighting coefficients with improved results.