旋转型饮品灌装机智能自校正控制

Intel igent Self-tuning Control of Rotary Drinks Filler

为了提高液体灌装机灌装精度,提高灌装效率,以补灌工艺为研究对象,提出一种基于RBF神经网络PID的液体灌装自校正控制方法。介绍灌装机的基本结构、工艺流程以及自动补灌基本原理。基于RBF神经网络PID设计一种二次补灌控制器,阐述神经网络结构和学习算法,可实现PID控制器比例、积分、微分系数的实时调整,用于提高补灌电机的运动精度。通过仿真可知,该算法相比于传统PID控制超调量更小,系统能以较快速度实现精确灌装,灌装精度明显高于单纯PID控制。

In order to improve the filling accuracy and efficiency of liquid filling machine, a self-tuning control method of liquid filling based on RBF neural network PID was proposed. The basic structure, technological process and basic principle of automatic filling machine were introduced. Based on RBF neural network PID, a secondary recharge irrigation controller was designed. The structure and learning algorithm of the neural network were described. Real-time adjustments of the proportion, integral and differential coefficients of the PID controller could be realized to improve the motion accuracy of the recharge irrigation motor. The simulation results showed that the algorithm had smaller overshoot than the traditional PID control, and the system could achieve accurate filling at a faster speed. The filling accuracy was significantly higher than that of the simple PID control.