Research on SRM control strategy for looms based on multi-algorithm fusion.

This article focuses on addressing the torque pulsation problem in Switched Reluctance Motors (SRMs) used to drive the main spindle of rapier looms, which affects speed stability and fabric quality. It proposes a loom-specific SRM control strategy based on multi-algorithm fusion, integrating fuzzy control, particle swarm optimization, and simulated annealing algorithms to optimize the Torque Sharing Function (TSF) and incorporate voltage chopping control. Experimental results demonstrate that this multi-algorithm fusion strategy reduces torque pulsation to below 10%, achieves a speed rise time under 0.1 seconds, and maintains a relative speed error below 0.05%, outperforming traditional PID, angle-position, and single TSF control methods. The study concludes that the proposed control strategy enhances speed stability and disturbance rejection without increasing hardware costs, providing a cost-effective solution for improving SRM-driven loom spindle performance.