一种饲料粉碎机自动化加工控制技术研究  

Research on an automatic processing control technology for feed crusher

作　　者：贾红涛[1] JIA Hong-tao(Shangluo Vocational and Technical College,Shangluo 726000,China)

机构地区：[1]商洛职业技术学院,陕西商洛726000

出　　处：《粮食与饲料工业》2024年第2期46-52,共7页Cereal & Feed Industry

基　　金：商洛市科技局项目(2022-J-0010)。

摘　　要：针对传统锤片式饲料粉碎机存在粉碎能耗高和粉碎效果差,导致饲料生成率低的问题,提出一种基于神经网络的自适应PID粉碎机控制方法NN-PID。首先,确定神经网络结构和粉碎机相关参数;然后将神经网络算法输入至S函数中,通过MATLAB-Simulink图形化编程模块构建一个饲料粉碎机粉碎系统PID控制模型;最后通过仿真软件对构建的控制模型进行仿真验证。实验结果表明,在输入为R=1的阶跃信号时,通过该模型进行控制后,饲料粉碎机控制系统上升时间取值为0.662 s、峰值时间为0.987 s,最大超调量为0.044%,调整时间为1.447 s。相较于传统的T-PID模型和F-PID模型,该模型的控制准确性更高,稳定性和鲁棒性更强,在四个性能评价指标中的性能更为优越。由此说明,该模型可降低锤片式饲料粉碎机的粉碎能耗,提升粉碎效果和生产率,满足饲料粉碎机控制系统的自动化控制需求。In view of the problems of high energy consumption and poor crushing effect of traditional hammer feed grinder,a control method of NN-PID was proposed.Firstly,the structure of neural network and related parameters of crusher were determined.Then the neural network algorithm was input into S function,and a PID control model of feed crusher system was built by MATLAB-Simulink graphical programming module.Finally,the control model was verified by simulation software.The experimental results showed that when the input step signal was R=1,the rise time of the feed grinder control system was 0.662 s,the peak time was 0.987 s,the maximum overshoot amount was 0.044%,and the adjustment time was 1.447 s.Compared with the traditional T-PID model and F-PID model,this model had higher control accuracy,stronger stability and robustness,and better performance in the four performance evaluation indicators.It shows that this model can reduce the crushing energy consumption of the hammer chip feed grinder,improve the powder effect and crushing productivity,and meet the automatic control requirements of the feed grinder control system.

关 键 词：粉碎机 神经网络 PID控制 自动化 MATLAB-SIMULINK 

分 类 号：S816.9[农业科学—饲料科学] TP392[农业科学—畜牧学]