基于改进麻雀算法的卷绕张力控制系统

Winding Tension Control System Based on Improved Sparrow Algorithm

为了在卷绕系统中建立稳定的张力控制系统,课题组使用自抗扰控制器设计了控制系统。提出采用麻雀算法(SSA)优化整定自抗扰控制器的参数。针对SSA以跳跃的方式寻优、已陷入局部最优和原点收敛性强的缺点,提出基于粒子群算法(PSO)的改进麻雀算法(PGSSA);该方法引入了PSO的速度算子,修改麻雀算法的发现者和跟随者的位置来更新公式,增强麻雀算法的全局搜索能力。由于麻雀算法的种群多样性比较差,提出引入遗传算法的交叉和变异操作,以保证种群的多样性,避免PGSSA过早陷入局部最优。选择复卷机的收卷过程作为控制对象模型,利用MATLAB/Simulink软件平台,分别采用PGSSA和SSA对ADRC控制器和PID控制器参数进行仿真。结果表明:PGSSA的收敛速度和精度都优于SSA。ADRC控制器对扰动的反应速度和抑制能力、阶跃响应的性能指标优于PID控制器。

In order to establish a stable tension control system in the winding system, the control systen was designed using active disturbance rejection controller. It was proposed to optimize and tune the parameters of the auto disturbance rejection controller using the sparrow search algorithm(SSA). Aiming at the shortcomings of SSA seeking optimization by jumping, falling into local optimality and strong convergence of the origin, the improved sparrow search algorithm(PGSSA) based on particle swarm optimization(PSO) was proposed. The PSO speed operator was introduced and the positions of the discoverers and followers of the sparrow search algorithm was modified to update the formula and enhance the global search capability of the sparrow search algorithm. Because of the relatively poor population diversity of the sparrow search algorithm, it was proposed to introduce the crossover and mutation operations of the genetic algorithm to ensure the diversity of the population and prevent the PGSSA from falling into the local optimum prematurely. The winding process of the rewinder in the winding system was taken as the control object model. Using MATLAB/Simulink software platform, PGSSA and SSA were adopted for the simulation of the ADRC controller and PID controller parameters respectively. The results show that the convergence speed and accuracy of PGSSA are better than SSA, and the ADRC controller has better performance indexes than the PID controller in terms of response speed and suppression ability to disturbances.