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闪速炉的神经网络冰镍质量模型与稳态优化控制研究
引用本文:万维汉,万百五,杨金义.闪速炉的神经网络冰镍质量模型与稳态优化控制研究[J].自动化学报,1999,25(6):800-804.
作者姓名:万维汉  万百五  杨金义
作者单位:1.西安交通大学系统工程研究所,西安;
基金项目:国家“八六三”计划及金川有色金属公司科研基金
摘    要:提出了基于神经元网络技术的软测量方法,建立复杂工业过程(闪速炉)模型.针对 生产工艺的要求,分别建立了生产工艺指标模型和产品产量模型,开辟了复杂工业过程产品 质量建模的新领域.在建模基础上,对闪速炉进行了稳态优化控制研究,结果表明该方法具有 较好的节能效果.最后给出了将来在线优化控制的建议.

关 键 词:软测量技术    神经网络产品质量建模    稳态优化控制    闪速炉
收稿时间:1997-9-10

STUDY OF NEURAL NETWORK QUALITY MODELS AND STEADY-STATE OPTIMIZING CONTROL FOR NICKEL FLASH SMELTING FURNACE
WAN Weihan,WAN Baiwu,YANG Jinyi.STUDY OF NEURAL NETWORK QUALITY MODELS AND STEADY-STATE OPTIMIZING CONTROL FOR NICKEL FLASH SMELTING FURNACE[J].Acta Automatica Sinica,1999,25(6):800-804.
Authors:WAN Weihan  WAN Baiwu  YANG Jinyi
Affiliation:1.Systems Engineering Institute,Xi'an Jiaotong University,Xi'an;Jinchuan Non-ferrous Metals Complex,Jinchang
Abstract:The paper proposes an approach that uses soft\|sensing method to set up the neural network models of the complex industrial process\_\_nickel flash smelting furnace.They are technological index quality models and yield model for the furnace.This opens up a new application field of neural network modeling.The paper also gives a study of steady\|state optimizing control for the furnace.The results show that the modeling and optimization provide better effect in saving energy consumption.Finally,the paper suggests how to implement on\|line steady\|state optimizing control to the furnace in the future.
Keywords:Soft\|sensing technique  neural network quality modeling  steady\|state optimizing control  nickel flash smelting furnace  
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