Control strategy of winding system of spinning frame based on improved active disturbance rejection

Abstract

To ensure stable tension of the yarn during winding, reduce yarn breakage rate, and improve the quality of yarn, to address issues such as speed and torque fluctuations in the speed control of permanent magnet synchronous motor-driven winding systems, we employed the grey wolf optimizer (GWO) algorithm and proposed an improved self-disturbance control strategy. This strategy combines an enhanced gain-adjustable expanded state observer with an improved approaching rate sliding mode control. Firstly, sliding mode control was introduced on the basis of traditional active disturbance rejection rejection control, which effectively reduced the peak value problem and improved system robustness. Secondly, the approaching rate was improved to increase the sliding mode convergence speed. In addition, the GWO algorithm was employed to adjust the initial parameters of the sliding mode control and effectively reduce oscillation problems. Simulations were conducted to compare the performance of the self-tuning algorithm, sliding mode self-tuning algorithm, and sliding mode self-tuning algorithm optimized by the GWO algorithm. Compared with the traditional active disturbance rejection control, the permanent magnet synchronous motor under the control of the sliding mode active disturbance rejection algorithm based on GWO algorithm shortens the time for the motor speed to stabilize from 180 ms to 40 ms after driving the winding system to adjust the speed and the instantaneous average torque increment is reduced from 105 mN·m to 70 mN·m, a decrease of 33.33%. The results demonstrate that the proposed active disturbance rejection control strategy based on the GWO algorithm can enhance the speed regulation performance of the permanent magnet synchronous motor, effectively reduce speed and torque fluctuations during the control process, improve yarn quality, and reduce yarn breakage rate.

Keywords

• spinning frame winding system
• permanent magnet synchronous motor
• active disturbance rejection control
• improved sliding mode
• grey wolf optimizer algorithm