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ANN预估补偿算法在炉电极控制系统中的实现
引用本文:王征,李磊. ANN预估补偿算法在炉电极控制系统中的实现[J]. 化工自动化及仪表, 2006, 33(1): 70-72
作者姓名:王征  李磊
作者单位:西安科技大学,电气与控制工程学院,西安,710054;西安科技大学,电气与控制工程学院,西安,710054
摘    要:针对电炉的执行机构的调节总是滞后于电弧炉实际状态变化的情况,在专家系统的基础上增加弧炉神经网络预估模型,通过它预估出电弧炉下一时刻的状态,并经过特定的优化程序(ANN预估补偿程序)对专家系统的输出做出优化补偿.系统的实际运行证明:神经网络预估补偿的电弧炉自适应控制是一种可行的电弧炉电极控制方法;在电弧炉的点弧过程中,电弧的稳定性有较大改进,提高了功率因数,降低了电耗.

关 键 词:神经网络  预估补偿  电极  权值  控制器
文章编号:1000-3932(2006)01-0070-03
收稿时间:2005-12-23
修稿时间:2005-12-23

Realizing of Electric Arc Furnace Electrode Control System Based on ANN
WANG Zheng,LI Lei. Realizing of Electric Arc Furnace Electrode Control System Based on ANN[J]. Control and Instruments In Chemical Industry, 2006, 33(1): 70-72
Authors:WANG Zheng  LI Lei
Abstract:The regulation of executing agency always lags behind when the actual state of electric arc furnace changes.The electric arc furnace neural network predicting model,which can predict the electric arc furnace's state for the next time,is added based on expert system.The output of expert system is optimized compensated by special optimized program(ANN Predicting Balance program).The operating result of system shows that adaptive control of electric arc furnace based on ANN is a feasible way of electrode controlling.In arc ignition process,it has apparent effect and improves the stability of arc,so that power factor is advanced and current drain is reduced.
Keywords:neural network  predicting compensation  electrode  factors  common controller
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