摘要
由于干熄焦生产过程复杂多变,因此很难获得系统更具说服力的数据和运算形式,所以在传统的基础上现行的种种PID控制所达到的程度并不令人满意。为了克服上述缺陷,提出了基于BP神,经网络的干熄焦CO自适应控制新方法。该方法通过BP神经网络对PID控制参数Kp,Kt和Kd进行在线优化控制,使得CO浓度控制在有效合理的区间范围内,从而达到了最佳性能指标,取得了良好的控制效果.
Due to the complicated and changeable production process of dry quenching,it is difficult to obtain the accurate mathematical model of the system.So the traditional PID control can not achieve the satisfactory control effect.In order to overcome the above defects,a new adaptive control method based on BP neural network is proposed.The method using BP neural network to realize the online optimization control of the PID control parameters Kp,Ki and Ka,which makes the CO concentration control within the scope of the effective and reasonable interval. Therefore,the best performance index is achieved and a good control effect is obtained.
作者
卢敏
邹骏
黄斌
LUMin;ZOUJun;HUANGBin(Coke-oven Plant,Guangxi Liuzhou Iron and Steel Group Company Limited,Liuzhou 545002,Guangxi,China;Department of Mechatronics Engineering,Liuzhou Vocational and Technical College,Liuzhou 545002,Guangxi,China)
出处
《中国冶金》
CAS
北大核心
2018年第11期53-56,共4页
China Metallurgy
基金
柳州市科学研究与技术开发计划资助项目(2017BB20201)
2017年度广西高校中青年教师基础能力提升资助项目(2017KY1048)
