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数据驱动闭环子空间预测控制方法研究与应用
  • ISSN号：1001-0920
  • 期刊名称：《控制与决策》
  • 时间：0
  • 分类：TP273[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置]
  • 作者机构：[1]东北大学信息科学与工程学院,沈阳110004
  • 相关基金：国家自然科学基金重点项目（61034005）;教育部基本科研业务费研究生科研创新项目（N100604001）.
作者： 刘昕明[1], 高宪文[1], 翁永鹏
关键词： 数据驱动方法, 闭环子空间辨识, 模型预测控制, 炭化室压力, data-driven method, closed-loop subspace identification, model predictive control, coking chambers pressure
中文摘要：

提出一种完全数据驱动的闭环子空间辨识及预测控制器设计方法。该方法完全由闭环系统的输入输出数据辨识子空间矩阵，通过子空间矩阵的拆分，排除了与扰动相关的模型输入，进而获取子空间矩阵参数的无偏估计；将辨识得到的闭环系统子空间矩阵描述直接作为预测模型，设计预测控制器；将其应用于某钢铁集团焦炉炭化室压力控制系统，取得了良好的控制效果。

英文摘要：

A full data-driven method of closed-loop subspace identification and predictive controller design is presented, in which the subspace matrix is completely identified through the input and output data of the closed-loop system. By splitting the subspace matrix and eliminating the input of the model correlated to disturbance, the unbiased estimators of the parameters of the subspace matrix are obtained. The predictive controller is designed by using the closed-loop system subspace matrix which is obtained by identifying directly as the forecasting model. The control method is applied to the pressure regulating system for the coking chamber of an iron and steel group, and good performence is obtained.

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期刊信息
  • 《控制与决策》
  • 北大核心期刊（2011版）
  • 主管单位:中华人民共和国教育部
  • 主办单位:东北大学
  • 主编：张嗣瀛 王福利
  • 地址：沈阳市东北大学125信箱
  • 邮编：110004
  • 邮箱：kzyjc@mail.neu.edu.cn
  • 电话：024-83687766
  • 国际标准刊号：ISSN：1001-0920
  • 国内统一刊号：ISSN：21-1124/TP
  • 邮发代号:8-51
  • 获奖情况:
  • 1997年被评为辽宁省优秀编辑部,1999年期刊影响因子在信息与系统类期刊中排名第二位
  • 国内外数据库收录:
  • 俄罗斯文摘杂志,美国数学评论（网络版）,德国数学文摘,荷兰文摘与引文数据库,美国工程索引,美国剑桥科学文摘,英国科学文摘数据库,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊（2004版）,中国北大核心期刊（2008版）,中国北大核心期刊（2011版）,中国北大核心期刊（2014版）,中国北大核心期刊（2000版）
  • 被引量:32961