Multiobjective switching state selector for finite-states model predictive control based on fuzzy decision making in a matrix converter

Finite-states model predictive control is a rising alternative in the control of power converters and drives. Successful application to different topologies and applications such as two-level voltage source inverters, neutral-point-clamped and cascaded H-bridge inverters, and matrix converters has shown its potential in power converters. However, when multiple control objectives are desired, weighting factors are required to appropriately select the switching states. The selection of these factors is a time-consuming and complex task. In this work, the standard selection stage is replaced by a fuzzy decision-making strategy, considering, as a case study, the control of both load and supply currents in the direct matrix converter (DMC). As a result, weighting-factor selection is avoided, and a simple selection scheme is obtained for this application. In addition, a more natural design approach to the state selection is opened for other applications. Simulation and experimental results are presented to validate the approach in an experimental DMC prototype.