摘要
为了保证在阴极炭块自动组装中把钢棒糊料定量加入炭块的燕尾槽内,提高阴极炭块组装的质量,从而进一步提高电解铝的质量和产量,降低工人的劳动强度,实现阴极炭块组装的自动化。本文在满足阴极炭块自动组装生产线工艺性要求的基础上,提出了基于BP神经网络对整条生产线上工作台匀速运动的控制,通过仿真结果可以看出,当负载变化时,BP神经网络的自适应PID控制具有调节时间短、超调和振荡小等特点,从而大大改善了系统的鲁棒性和跟踪性能,可以有效地降低工作台的速度波动,使工作台匀速运动,从而达到均匀给料的目的。
In order to ration the carbon paste m the groove of the cathode carbon block, to improve the assembly quality of the cathode carbon block, and to enhance the quality and output of electrolytic aluminium and reduce the labor intensity of workers,carry out the cathode carbon block assembly automation. The paper researches on self- adaptiving of PID in controlling uniform motion of worktable in the entire assembly line based on BP neural network. The simulation result showed when the load changes, there are a lot of characteristics such as short time of adjusting ultra- small oscillation in BP adaptive neural network PID control, thus it greatly improvea the robustness of the system and track performance and can effectively reduce the rate of speed fluctuation of worktable to achieve the purpose of uniform feeding carbon paste.
出处
《轻金属》
CSCD
北大核心
2009年第1期27-30,共4页
Light Metals
