Spindle speed control algorithm for spinning machine optimized GPC-PID based on PSO

Abstract

Aimed at the problem of severed heads caused by the large fluctuation of yarn tension in the winding process of the spinning machine, the spindle speed control method of GPC-PID optimized by particle swarm optimization(PSO) algorithm was proposed. First, the generalized predictive control PID (GPC-PID) algorithm was introduced to control the spindle speed, and the PID parameters were adjusted in real time to control the spinning speed. Then, PSO algorithm was introduced to improve the prediction accuracy of GPC-PID. Finally, through simulation experiments, the conventional GPC-PID control was compared with the GPC-PID control optimized by PSO algorithm. The results show that under the control of GPC-PID algorithm optimized by PSO algorithm, the speediness and stability of the system are improved, the spindle speed and torque are effectively controlled, the yarn tension fluctuation is small, and the breakage rate in the spinning process is reduced, which proves the superiority of particle swarm optimization GPC-PID control algorithm.

Keywords

• spindle speed of spinning machine
• yarn tension
• pid algorithm
• generalized predictive control algorithm
• particle swarm optimization algorithm
• brushless dc motor