基于模糊-遗传算法的粗纱机出料传动系统PID参数优化方法

PID parameter optimization method for discharge transmission system of roving machine based on fuzzy genetic algorithm

目前常规的粗纱机出料传动系统PID参数优化方法主要通过结合被控对象的稳态增益情况构建出优化函数,实现PID参数优化整合,忽略了实际运行工况下的干扰成分,导致参数优化效果不佳。对此,提出基于模糊-遗传算法的粗纱机出料传动系统PID参数优化方法。首先结合PID的系统阶跃响应曲线,以被控量的偏差变化率作为主要参数选取性能指标;然后通过引入负荷扰动模块以及频率干扰模块,对PID调节模块进行建模分析;最后结合模糊-遗传算法对最优适应度值进行求解,从而实现PID参数的有效优化,并对提出的方法进行优化效果检验。最终测试结果表明,采用提出的方法对PID参数进行优化整合时,控制输出曲线与理论输出曲线的拟合程度更高,具备较为理想的优化效果。

At present,the conventional PID parameter optimization method for the discharge transmission system of the roving machine mainly constructs an optimization function by combining the steady-state gain of the controlled object to achieve PID parameter optimization integration.However,due to the neglect of interference components under actual operating conditions,the parameter optimization effect was not satisfactory.A fuzzy genetic algorithm based PID parameter optimization method for the discharge transmission system of the roving machine was proposed.Firstly,the performance indexes were selected by combining the system step response curve of the PID controller with the deviation change rate of the controlled quantity as the main parameter.Then the PID regulation module was modeled and analyzed by introducing the load disturbance module and the frequency disturbance module,and finally the optimal fitness value was solved by combining the fuzzy-genetic algorithm,so as to realize the effective optimization of the PID parameters.In the experiment,the optimization effect of the proposed method was tested.The final test results show that when the proposed method was used to optimize and integrate the PID parameters,the control output curve fits better with the theoretical output curve,and has a more ideal optimization effect.