Improvised multi-objective model predictive control of matrix converter using fuzzy logic and space vectors for switching decisions

Abstract

Finite control set model predictive control (FCS-MPC) has lately received noteworthy attention in the control of power converters. Such converters have a finite number of switching states, which ensure a small sample space of predictions and minimum computational burden. Although unanimously popular in most converters, multi-objective FCS-MPC (Mo-FCS-MPC) is a particularly attractive choice in the control of matrix converters (MCs), as it enables attainment of multiple objectives with relative ease. Conventionally, a weighing factor-based approach is undertaken in the implementation of Mo-FCS-MPC wherein a cost-function is framed such that each of its constituent objectives, is assigned a relative weight according to its significance. However, the tuning of weights is empirical in nature and hence tedious. This study proposes an improvised technique for implementing Mo-FCS-MPC in MCs while simultaneously meeting a number of objectives such as load current, source current, and input power factor control. Sector information from space vectors of reference output voltages and reference input currents, coupled with a fuzzy decision-making criterion is used to make the final switching decision, hence eliminating the conventional weighing factor-based approach. The inclusion of space vector modulation into predictive control enhances the quality of both loads as well as source current waveforms.