Eliminating Speed Fluctuations in Textile Machine Motors Using Model Predictive Control and Proportional Integral Control with Tension Dynamics Integration

Textile manufacturing processes require a stable motor speed to ensure consistent yarn quality, reduce fabric defects, and prevent material breakage. However, traditional PI-based Field-Oriented Control (FOC) often struggles to handle rapid load changes, resulting in speed fluctuations that directly impact product quality. This study presents a new hybrid control strategy that combines Model Predictive Control (MPC) with FOC to eliminate speed ripple in textile machine motors during disturbances. MATLAB was used to model a Permanent Magnet Synchronous Motor (PMSM) drive and the dynamics of textile web tension, assessing speed stability, torque response, and tension uniformity. The simulation results show that traditional PI-FOC exhibits a speed ripple of ±4.887 rad/s, the proposed FOC-MPC reduces the speed ripple significantly to about ±1.876 rad/s, Torque ripple improves from about 4 N·m in PI-FOC to about 2 N·m in MPC-FOC, while tension fluctuation decreases from 14% to 3.5%, indicating notable improvements in process stability, the maximum tension deviation for PI was 38.7436 N, while for MPC it was 18.8268 N. Additionally, a composite metric shows overall process performance by combining speed and tension data. PI scores 0.3247, while MPC scores 0.3746, marking about a 15.5% improvement. Making this approach ideal for high-speed textile operations. The results confirm that MPC-FOC offers better speed tracking, stronger disturbance rejection, and improved product quality. This provides a practical path for industrial use in textile winding, spinning, and warping machines.