Generalized Model Predictive Control Algorithm for a Five-Phase Induction Motor

This paper proposes a Generalized Predictive Control (GPC) approach for the inner current-control loop of a multiphase induction motor drive. The method is based on a CARIMA model, which inherently provides integral action, allowing steady-state error rejection without the need for state or disturbance observers. In contrast to state-space Model Predictive Control (MPC), the proposed formulation enables the straightforward inclusion of system delays and yields an analytical solution when constraints are not considered, reducing computational complexity. Additionally, it is shown that the GPC is able to cope with modelling errors due to different dynamics at different operating points. The effectiveness of the approach is evaluated on a five-phase induction machine, showing competitive performance and improved robustness against modelling uncertainties.