摘要
针对高炉热风炉温度控制易波动问题,文章提出基于模糊神经网络控制算法对热风炉进行温度控制,具体采用补偿模糊神经网络控制算法,对输入制定一个折中的方案,仿真结果表明该方法能够满足高炉对温度控制的要求,达到了减少温度波动的目的。
In order to overcome the temperature fluctuation of hot blast stove,a fuzzy neural network is proposed to control the temperature.The compensatory fuzzy neural network makes a middle decision between the worst and the best condition.The simulation result is carried out that the method can meet the requirements of hot blast stove temperature control,and the temperature fluctuation of hot blast stove is decreased.
出处
《铜陵学院学报》
2011年第5期95-97,共3页
Journal of Tongling University
基金
安徽省高校省级自然科学基金资助项目<热风冲天炉自动化控制系统开发>(编号:KJ2008B131)研究成果
关键词
补偿模糊神经网络
热风炉
温度控制
compensatory fuzzy neural network
hot blast stove
temperature control
