PID控制器
温度控制
退火(玻璃)
超调(微波通信)
模拟退火
控制理论(社会学)
模糊逻辑
真空炉
模糊控制系统
计算机科学
过程控制
材料科学
控制工程
算法
过程(计算)
工程类
冶金
控制(管理)
人工智能
操作系统
电信
作者
Jintao Meng,Haitao Gao,Mi-Xue Ruan,Hai Guo,Xiaojie Zhou,Di Zhang
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2023-11-29
卷期号:18 (11): e0293823-e0293823
被引量:7
标识
DOI:10.1371/journal.pone.0293823
摘要
As is well known, the metal annealing process has the characteristics of heat concentration and rapid heating. Traditional vacuum annealing furnaces use PID control method, which has problems such as high temperature fluctuation, large overshoot, and long response time during the heating and heating process. Based on this situation, some domestic scholars have adopted fuzzy PID control algorithm in the temperature control of vacuum annealing furnaces. Due to the fact that fuzzy rules are formulated through a large amount of on-site temperature data and experience summary, there is a certain degree of subjectivity, which cannot ensure that each rule is optimal. In response to this drawback, the author combined the technical parameters of vacuum annealing furnace equipment, The fuzzy PID temperature control of the vacuum annealing furnace is optimized using genetic algorithm. Through simulation and comparative analysis, it is concluded that the design of the fuzzy PID vacuum annealing furnace temperature control system based on GA optimization is superior to fuzzy PID and traditional PID control in terms of temperature accuracy, rise time, and overshoot control. Finally, it was verified through offline experiments that the fuzzy PID temperature control system based on GA optimization meets the annealing temperature requirements of metal workpieces and can be applied to the temperature control system of vacuum annealing furnaces.
科研通智能强力驱动
Strongly Powered by AbleSci AI