Fuzzy MPPT operation-based model predictive flux control for linear induction motors

Abstract

This research focuses on a methodology for connecting the linear induction machine (LIM) using model predictive flux control (MPFC) fed by Kyocera solar cells. Additionally, it incorporates a fuzzy logic regulator (FLR) for maximum power point tracking (MPPT) control. The boost converter's characteristics are regulated using MPPT, allowing it to achieve a voltage gain of up to twice the input voltage. The finite state-model predictive flux control (FS-MPFC) is employed to synthesize the three-phase voltage source converter switching states. The paper proposes an improved FS-MPFC strategy for LIMs, eliminating the cost function's need for a weighting parameter. This is achieved by unifying its terms of traditional control methods and reducing the number of calculation steps. The validity and effectiveness of the introduced system are confirmed by extensive simulation results. The findings revealed that the system can accurately extract maximum power from the Kyocera solar cells and track the preset speed values. In addition, it can enhance performance by minimizing the thrust and primary flux under varying speed and load conditions.