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数据驱动的复杂磨矿过程运行优化控制方法

代伟 柴天佑

代伟, 柴天佑. 数据驱动的复杂磨矿过程运行优化控制方法. 自动化学报, 2014, 40(9): 2005-2014. doi: 10.3724/SP.J.1004.2014.02005
引用本文: 代伟, 柴天佑. 数据驱动的复杂磨矿过程运行优化控制方法. 自动化学报, 2014, 40(9): 2005-2014. doi: 10.3724/SP.J.1004.2014.02005
DAI Wei, CHAI Tian-You. Data-driven Optimal Operational Control of Complex Grinding Processes. ACTA AUTOMATICA SINICA, 2014, 40(9): 2005-2014. doi: 10.3724/SP.J.1004.2014.02005
Citation: DAI Wei, CHAI Tian-You. Data-driven Optimal Operational Control of Complex Grinding Processes. ACTA AUTOMATICA SINICA, 2014, 40(9): 2005-2014. doi: 10.3724/SP.J.1004.2014.02005

数据驱动的复杂磨矿过程运行优化控制方法

doi: 10.3724/SP.J.1004.2014.02005
基金项目: 

国家科技支撑计划项目(2012BAF19C01)资助

详细信息
    作者简介:

    代伟 东北大学流程工业综合自动化国家重点实验室博士研究生.2009年获得东北大学硕士学位.主要研究方向为复杂工业过程运行优化控制方法研究以及软件实现.本文通信作者.E-mail:daiweineu@126.com

    通讯作者:

    代伟 东北大学流程工业综合自动化国家重点实验室博士研究生.2009年获得东北大学硕士学位.主要研究方向为复杂工业过程运行优化控制方法研究以及软件实现.本文通信作者.E-mail:daiweineu@126.com

Data-driven Optimal Operational Control of Complex Grinding Processes

Funds: 

Supported by National Key Technology Research and Development Program (2012BAF19C01)

  • 摘要: 针对赤铁矿磨矿过程的磨矿粒度(Grinding particle size,GPS)与控制回路输出之间的动态特性难以用数学模型描述,且磨矿粒度不能在线测量,并受矿石成分与性质频繁波动干扰,难以采用已有运行优化方法的难题,结合磨矿过程的特点,利用数据,采用神经网络,提出由回路预设定值优化、性能指标估计、优化设定值评价以及磨矿粒度软测量组成的数据驱动的磨矿过程运行优化控制方法. 该方法由磨矿粒度软测量估计矿浆粒度,通过回路预设定值优化模块求得使性能指标估计值接近最优值的回路预设定值,经优化设定值评估产生回路设定值,最后通过控制回路跟踪设定值,将矿浆粒度控制在目标值范围内并尽可能的接近目标值. 通过研制的运行优化与控制研究平台,采用实际运行数据进行仿真实验,表明所提方法的有效性.
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出版历程
  • 收稿日期:  2013-07-16
  • 修回日期:  2014-01-09
  • 刊出日期:  2014-09-20

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