Impact of Sequential Model Predictive Control on Induction Motor Performance: Comparison of Converter Topologies

Finite Set Model Predictive Control (FS-MPC) is a widely used technique in power electronic converter applications. One challenge FS-MPC implementation selecting appropriate weighting factors, as there currently no established methodology for finding the best values. An alternative approach to consider cost functions without by Sequential (SMPC). In this paper, performance of SMPC applied induction motors analyzed. The strategy involves sequentially evaluating simple considering limited number available switching states converter. This control parameter SMPC. parameter’s domains and selection criteria based on THD were investigation. topologies studied include Voltage Source Inverter (VSI) Neutral Point Clamped three-level (3L-NPC). Simulations performed PLECS software Hardware-in-the-Loop (HIL) tests using an RT Box valid parameters satisfy characteristics classical predictive control, such good variables tracking high dynamic response. For VSI converter, increasing results reduced harmonic distortion, while NPC optimal are achieved with values within specific range.