Fuzzy decoupling PID control for vibration-slow shear crusher
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摘要: 针对振动慢剪破碎机碎矿过程多变量、强耦合、大时滞的特点,提出了一种基于自适应粒子群算法优化的模糊解耦PID控制方法。在对振动慢剪破碎机动态模型进行对角矩阵解耦的基础上,分别对给料量和振动电动机频率进行模糊PID控制,并引入自适应粒子群优化算法对模糊PID控制的隶属函数参数进行动态优化,从而实现主电动机工作电流及合格矿料产率精确、稳定、快速控制。仿真及试验结果表明,该方法具有响应速度快、调节时间短、超调量小的特点。Abstract: A fuzzy decoupling PID control method based on adaptive particle swarm optimization (APSO) was proposed for the characteristics of multivariable, strong coupling and large time delay in the ore crushing process of vibration-slow shear crusher. Based on diagonal matrix decoupling of dynamic model for vibration-slow shear crusher, fuzzy PID control of ore feeding quantity and vibration motor frequency is carried out respectively, and dynamic optimization of membership function parameters of fuzzy PID control is conducted by introducing APSO algorithm, so as to achieve accurate, stable and fast control of main motor operating current and qualified mineral yield. The simulation and experimental results show that the method has characteristics of fast response, short adjustment time and small overshoot.
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