基于PSO的GPC-PID的细纱机锭速控制算法

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

针对细纱机在卷绕过程中由于纱线张力波动较大而导致的断头问题,提出了粒子群优化(particle swarm optimization,PSO)算法优化控制GPC-PID的锭子转速。首先,引入广义预测控制PID(GPC-PID)算法来控制锭子转速,并实时对PID进行参数整定,从而实时控制细纱机锭速。然后,引入PSO算法来提高GPC-PID的预测精度。最后,通过仿真实验,将常规的GPC-PID控制与PSO算法优化的GPC-PID控制进行比较。结果表明,锭子无刷直流电机在经PSO算法优化后的GPC-PID算法控制下,系统的快速性和稳定性都有一定提高,锭子的转速和转矩得到有效控制,纱线张力波动较小,降低了细纱卷绕过程中的断头率,证明了粒子群优化GPC-PID控制算法的优越性。

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.