2.765

2022影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

一种基于初始闭环系统的性能评估方法

谢磊 冯皓 张建明

谢磊, 冯皓, 张建明. 一种基于初始闭环系统的性能评估方法. 自动化学报, 2013, 39(5): 649-653. doi: 10.3724/SP.J.1004.2013.00649
引用本文: 谢磊, 冯皓, 张建明. 一种基于初始闭环系统的性能评估方法. 自动化学报, 2013, 39(5): 649-653. doi: 10.3724/SP.J.1004.2013.00649
XIE Lei, FENG Hao, ZHANG Jian-Ming. A New Approach to Performance Assessment Based on Initial-closed-system. ACTA AUTOMATICA SINICA, 2013, 39(5): 649-653. doi: 10.3724/SP.J.1004.2013.00649
Citation: XIE Lei, FENG Hao, ZHANG Jian-Ming. A New Approach to Performance Assessment Based on Initial-closed-system. ACTA AUTOMATICA SINICA, 2013, 39(5): 649-653. doi: 10.3724/SP.J.1004.2013.00649

一种基于初始闭环系统的性能评估方法

doi: 10.3724/SP.J.1004.2013.00649
详细信息
    通讯作者:

    张建明

A New Approach to Performance Assessment Based on Initial-closed-system

  • 摘要: 基于初始闭环系统的输出方差和最小方差指标, 提出了一种新的性能评估方法. 在过程时滞变化的情况下, 基于最小方差指标的评估可能会得到错误的结论, 而新的方法可以避免这一缺点. 扩展的性能指标以控制器投运后的初始状态作为零基准, 能够更准确地反映操作工系统性能的变化, 能够很好地替代最小方差指标. 利用交互矩阵可将扩展指标推广到多变量系统的评估中, 本文将这一算法应用于精馏塔过程的评估. 精馏塔过程的仿真示例验证了方法的有效性, 表明过程时滞变化时用扩展指标来进行评估更能反映系统性能的变化.
  • [1] Harris T J. Assessment of control loop performance. The Canadian Journal of Chemical Engineering, 1989, 67(5): 856 -861[2] Tyler M L, Morari M. Performance monitoring of control systems using likelihood methods. Automatica, 1996, 32(8): 1145-1162[3] Harris T J, Boudreau F, Macgregor J F. Performance assessment of multivariable feedback controllers. Automatica, 1996, 32(11): 1505-1518[4] Huang B, Shah S L. Practical issues in multivariable feedback control performance assessment. Journal of Process Control, 1998, 8(5-6): 421-430[5] Huang B, Shah S L, Fujii H. The unitary interactor matrix and its estimation using closed-loop data. Journal of Process Control, 1997, 7(3): 195-207[6] Xu F W, Huang B, Tamayo E C. Performance assessment of MIMO control systems with time-variant disturbance dynamics. Computers and Chemical Engineering, 2008, 32(9): 2144-2154[7] Bezergianni S, Georgakis C. Controller performance assessment based on minimum and open-loop output variance. Control Engineering Practice, 2000, 8(7): 791-797[8] Wang X, Huang B, Chen T. Multirate minimum variance control design and control performance assessment: a data-driven subspace approach. IEEE Transactions on Control Systems Technology, 2007, 15(1): 65-74[9] Bezergianni S, zkan L. On the assessment of multivariable controllers using closed loop data, Part I: Identification of system models. Journal of Process Control, 2012, 22(1): 125 -131[10] Huang B, Shah S L. Performance Assessment of Control Loops: Theory and Applications. UK: Springer-Verlag, 1999.[11] Kadali R, Huang B. Controller performance analysis with LQG benchmark obtained under closed loop conditions. ISA Transactions, 2002, 41(4): 521-537[12] Xu Q L, Zhao C, Zhang D F, An A M, Zhang C. Data-driven LQG benchmaking for economic performance assessment of advanced process control systems. In: Proceedings of the 2011 American Control Conference. San Francisco, USA, IEEE: 2011. 5085-5090[13] Grimble M J. Controller performance benchmarking and tuning using generalised minimum variance control. Automatica, 2002, 38(12): 2111-2119[14] Tian X M, Chen G Q, Chen S. A data-based approach for multivariate model predictive control performance monitoring. Neurocomputing, 2011, 74(4): 588-597[15] Luyben W L. Realistic models for distillation columns with partial condensers producing both liquid and vapor products. Industrial and Engineering Chemistry Research, 2012, 51(24): 8334-8339
  • 加载中
计量
  • 文章访问数:  1122
  • HTML全文浏览量:  61
  • PDF下载量:  1132
  • 被引次数: 0
出版历程
  • 收稿日期:  2012-05-15
  • 修回日期:  2012-07-22
  • 刊出日期:  2013-05-20

目录

    /

    返回文章
    返回