探讨NFOA-RBF神经网络的食用盐包装封口温度控制系统

Explore the Edible Salt Packaging Sealing Temperature Control System of NFOA-RBF Neural Network

为了更好地提升食用盐包装机的工作效率,实现更高的封口温度控制精度,有必要对现有食用盐包装封口温度控制系统进行优化。鉴于传统温度PID控制系统自适应控制程度低的问题,有意识地引入RBF神经网络,以期实现温度PID控制系统的在线调节。同时,引入果蝇优化算法(NFOA),以期优化RBF神经网络初始值。通过仿真和实验,表明基于NFOA-RBF神经网络的食用盐包装封口温度控制系统精确度更高,稳定性更好,值得应用和推广。

In order to better improve the working efficiency of the edible salt packaging machine and achieve higher sealing temperature control accuracy,it is necessary to optimize the existing edible salt packaging sealing temperature control system.In view of the low degree of adaptive control of traditional temperature PID control system,RBF neural network is consciously introduced to realize the online regulation of temperature PID control system.At the same time,NFOA is introduced to optimize the initial value of RBF neural network.Through simulation and experiment,it showed that the sealing temperature control system of edible salt packaging based on NFOA-RBF neural network has higher accuracy and better stability,which is worthy of application and promotion.