目的 提高定量称量包装机的包装精度。方法 在传统包装机械的基础上，基于PLC设计一种定量称量包装控制系统。结合RBF神经网络和PID控制方法，提出一种定量称量包装控制策略，以实现闭环控制。利用RBF神经网络的快速自学习能力调整PID控制的比例、积分、微分系数。以PLC为核心设计控制系统硬件结构并给出人机界面组成。结果 通过多次实验，包装精度得到大幅提高，最大相对误差不超过0.6%。结论 文中方法提高了定量称量包装机的精度、可靠性和可操作性。

The work aims to improve the packing precision of quantitative weighing packaging machine. A quantitative weighing packaging control system was designed with the programmable logic controller (PLC) based on traditional packaging machines. Combining RBF neural network and PID control method, a quantitative weighing packaging control strategy was proposed in order to realize the closed-loop control. The proportion, integral and differential coefficient of PID control were adjusted rapidly with the RBF neural network self-learning ability. The control system hardware structure was designed with PLC as the core and the composition of human-machine interface was presented. A lot of experiments showed that the packaging precision was greatly improved and the maximum relative error was no more than 0.6%. The method described herein has enhanced the precision, reliability and maneuverability of quantitative weighing packaging machines.