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基于SVM的PVC汽提过程预测控制方法
  • ISSN号：1002-0411
  • 期刊名称：《信息与控制》
  • 时间：0
  • 分类：TP182[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—控制理论与控制工程]
  • 作者机构：[1]东北大学信息科学与工程学院,辽宁沈阳110004, [2]沈阳化工大学信息工程学院,辽宁沈阳110142, [3]辽河油田公司概预算管理中心,辽宁盘锦124010, [4]葫芦岛锦化化工工程设计有限公司技术工程部,辽宁葫芦岛125001
  • 相关基金：国家自然科学基金重点资助项目（61034005）; 教育部基本科研业务费项目研究生科研创新项目（N100604001）
作者： 高淑芝[1,2], 冯少华[3], 高宪文[1], 安文翔[1], 于利民[4]
关键词： 汽提塔, 支持向量机, 预测控制, 聚氯乙烯, stripper, support vector machine（SVM）, predictive control, polyvinyl chloride（PVC）
中文摘要：

针对汽提塔温度控制系统的非线性和参数时变的特性,采用支持向量机对汽提塔温度进行建模,结合非线性模型的实时线性化和广义预测控制隐式算法,提出了基于支持向量预测模型的广义预测控制算法.同时将该算法应用到聚氯乙烯汽提生产过程当中,并将模型在线校正和误差反馈校正相结合,根据实际情况进行了多种情况下的仿真,仿真结果表明了方法的有效性.

英文摘要：

According to the nonlinear characteristics and time-varying parameters of the stripper temperature control system,support vector machine（SVM） is used to set up a stripper temperature model.Generalized predictive control（GPC） based on SVM predictive model combining the real-time linearization of nonlinear model with the GPC implicit algorithm is proposed.Meantime,the algorithm is applied to the producing process of polyvinyl chloride（PVC） stripper,and the model online regulation is combined with the error feedback regulation.The simulations are made in several circumstances,and the simulation results show the effectiveness of the method.

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期刊信息
  • 《信息与控制》
  • 北大核心期刊（2011版）
  • 主管单位:中国科学院
  • 主办单位:中国自动化学会 中国科学院沈阳自动化研究所
  • 主编：王天然
  • 地址：沈阳市南塔街114号
  • 邮编：110016
  • 邮箱：xk@sia.cn
  • 电话：024-23970049
  • 国际标准刊号：ISSN：1002-0411
  • 国内统一刊号：ISSN：21-1138/TP
  • 邮发代号:
  • 获奖情况:
  • 全国优秀期刊三等奖,中科院优秀期刊三等奖,辽宁省优秀期刊一等奖
  • 国内外数据库收录:
  • 美国数学评论（网络版）,荷兰文摘与引文数据库,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:12960