电加热炉温度控制器设计与仿真  

Design and simulation of temperature controller for electric heating furnace

作　　者：周建新 黄剑雄 ZHOU Jianxin;HUANG Jianxiong(College of Electrical Engineering,North China University of Science and Technology,Tangshan 063210,China)

机构地区：[1]华北理工大学电气工程学院,河北唐山063210

出　　处：《现代电子技术》2021年第20期83-87,共5页Modern Electronics Technique

基　　金：河北省教育厅重点项目(ZD2015059)。

摘　　要：针对工业上电加热炉存在非线性、大惯性、时滞等缺陷,传统的控制方法难以精确实现温度恒定的需求,文中提出改进蚁群算法的初始信息素分配原则,并引入免疫算法中抗体浓度调节机制,再利用改进后的蚁群算法对PID神经网络的权值进行整定,形成一种新型PID神经网络控制器对电加热炉进行控制。仿真结果表明,与传统的PID神经网络控制器相比,改进蚁群算法优化的PID神经网络控制器控制电加热炉,温度调节时间短,超调量小,抗干扰能力强。It is difficult for the traditional control method to achieve the requirement of constant temperature precisely because of the nonlinearity,large inertia and time delay existing in the industrial electric heating furnace.Therefore,the principle of initial pheromone distribution of the ant colony algorithm is improved in this paper,and the mechanism of antibody concentration regulation in immune algorithm is introduced.Then,the weight of PID neural network is adjusted by the improved ant colony algorithm,forming a new PID neural network controller to control the electric heating furnace.The simulation results show that,in comparison with the traditional PID neural network controller,the PID neural network controller optimized by the improved ant colony algorithm can control the electric heating furnace,and has advantages of shorter temperature regulation time,smaller overshoot and better anti⁃interference ability.

关 键 词：电加热炉 温度控制 蚁群算法改进 PID神经网络 权值调节 仿真实验 

分 类 号：TN377-34[电子电信—物理电子学] TP273[自动化与计算机技术—检测技术与自动化装置]