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基于多模型混合最小方差控制的时变扰动控制系统性能评估

张巍 王昕 王振雷

张巍, 王昕, 王振雷. 基于多模型混合最小方差控制的时变扰动控制系统性能评估. 自动化学报, 2014, 40(9): 2037-2044. doi: 10.3724/SP.J.1004.2014.02037
引用本文: 张巍, 王昕, 王振雷. 基于多模型混合最小方差控制的时变扰动控制系统性能评估. 自动化学报, 2014, 40(9): 2037-2044. doi: 10.3724/SP.J.1004.2014.02037
ZHANG Wei, WANG Xin, WANG Zhen-Lei. Performance Assessment of Control Loop with Time-variant Disturbance Dynamics Based on Multi-model Mixing Minimum Variance Control. ACTA AUTOMATICA SINICA, 2014, 40(9): 2037-2044. doi: 10.3724/SP.J.1004.2014.02037
Citation: ZHANG Wei, WANG Xin, WANG Zhen-Lei. Performance Assessment of Control Loop with Time-variant Disturbance Dynamics Based on Multi-model Mixing Minimum Variance Control. ACTA AUTOMATICA SINICA, 2014, 40(9): 2037-2044. doi: 10.3724/SP.J.1004.2014.02037

基于多模型混合最小方差控制的时变扰动控制系统性能评估

doi: 10.3724/SP.J.1004.2014.02037
基金项目: 

国家重点基础研究发展计划(973计划)(2012CB720500),国家自然科学基金重点项目(61134007),国家自然科学基金(61203157,61222303),中央高校基本科研业务费专项资金,上海市科技攻关项目(12dz1125100),十二五国家科技支撑计划项目(2012BAF05B00),上海市重点学科建设项目(B504),流程工业综合自动化国家重点实验室开放课题基金资助

详细信息
    作者简介:

    张巍 华东理工大学信息科学与工程学院硕士研究生.主要研究方向为控制系统性能评估.E-mail:zhangwei19880407@tom.com

    通讯作者:

    王振雷 华东理工大学教授.主要研究方向为智能控制,复杂系统的建模及特征分析,故障诊断,智能优化算法.本文通信作者.E-mail:wangzhenl@ecust.edu.cn

Performance Assessment of Control Loop with Time-variant Disturbance Dynamics Based on Multi-model Mixing Minimum Variance Control

Funds: 

Supported by National Basic Research Program of China (973 Program) (2012CB720500), Key Project of National Natural Science Foundation of China (61134007), National Natural Science Foundation of China (61203157, 61222303), Fundamental Research Funds for the Central Universities, Shanghai Science and Technology Research Projects (12dz1125100), National Science and Technology Pillar Program during the 12th Five-year Plan Period (2012BAF05B00), Shanghai Leading Academic Discipline Project (B504), and Open Research Fund of State Key Laboratory of Synthetical Automation for Process Industries

  • 摘要: 在实际工业过程中,控制系统经常会受到时变扰动的影响,致使针对单一扰动模型设计的最小方差控制准则不再适用于评估时变扰动控制系统的性能. 当多个扰动信号同时出现时,采用常规多模型切换方法会发生间歇切换进而产生较大的暂态误差,不能准确评估系统当前性能. 针对上述问题,本文提出了一种基于多模型混合最小方差控制准则的性能评估方法. 首先根据每个扰动模型分别制定最小方差控制器,组成多模型最小方差控制器,然后在每个时间点混合多模型最小方差控制器,并将在其作用下的输出方差作为最终的性能评估基准,该方法既 充分考虑到每个扰动的特性,又避免了常规多模型切换方法因间歇切换而产生的暂态误差对评估结果准确性带来的影响,实现了准确、可靠地评估时变扰动控制系统的性能. 通过仿真,验证了基于多模型混合最小方差控制准则的性能评估方法的有效性.
  • [1] Astrom K J. Introduction to Stochastic Control Theory. New York: Academic, 1970.
    [2] Harris T. Assessment of control loop performance. Canadian Journal of Chemical Engineering, 1989, 67(5): 856-861
    [3] Stanfelj N, Marlin T E, MacGregor J F. Monitoring and diagnosing process control performance: the single-loop case. Industrial and Engineering Chemistry Research, 1993, 32(2): 301-314
    [4] Tyler M, Morari M. Performance assessment for unstable and nonminimum-phase systems. In: Proceedings of the 1996 IFAC Workshop on On-Line Fault Detection and Supervision in the Chemical Process Industries. Tyne, UK: IFAC, 1996. 187-192
    [5] Olaleye F, Huang B, Tamayo E. Performance assessment of control loops with time-variant disturbance dynamics. Journal of Process Control, 2004, 14(8): 867-877
    [6] Zhou M F, Xie L, Pan H T,Wang S Q. Performance assessment of PID controller with time-variant disturbance dynamics. In: Proceedings of the 2011 International Symposium on Advanced Control of Industrial Processes. Hangzhou, China: IEEE, 2011. 650-655
    [7] Huang B. Minimum variance control and performance assessment of time variant processes. Journal of Process Control, 2002, 12(6): 707-719
    [8] Xu F W, Huang B. Performance monitoring of SISO control loops subject to LTV disturbance dynamics: an improved LTI benchmark. Journal of Process Control, 2006, 16(6): 567-579
    [9] Huang B, Shah S L. Performance Assessment of Control Loops: Theory and application. New York: Springer, 1999
    [10] Roderick M S, Johansen T A. Multiple Model Approaches to Modeling and Control. London: Taylor and Francis, 1997.
    [11] Dong Zhi-Kun, Wang Xin, Wang Xiao-Bo, Li Shao-Yuan, Zheng Yi-Hui. Application of weighted multiple models adaptive controller in the plate cooling process. Acta Automatica Sinica, 2010, 36(8): 1144-1150(董志坤, 王昕, 王笑波, 李少远, 郑益慧. 多模型加权自适应控制在中厚板层流冷却系统中的应用. 自动化学报, 2010, 36(8): 1144-1150)
    [12] Zheng Yi-Hui, Wang Xin, Li Shao-Yuan. Multiple models direct adaptive decoupling controller for stochastic systems. Acta Automatica Sinica, 2010, 36(9): 1295-1304(郑益慧, 王昕, 李少远. 随机系统的多模型自适应解耦控制器. 自动化学报, 2010, 36(9): 1295-1304)
    [13] Wang Xin, Li Shao-Yuan, Yue Heng. Multivariable adaptive decoupling controller using hierarchical multiple models. Acta Automatica Sinica, 2005, 31(2): 223-230(王昕, 李少远, 岳恒. 分层递阶多模型自适应解耦控制器. 自动化学报, 2005, 31(2): 223-230)
    [14] Matthew K, Petros I. Multiple model adaptive control with mixing. IEEE Transactions on Automatic Control, 2010, 55(8): 1822-1836
    [15] Simone B, Petros I, Edoardo M. Multiple model adaptive mixing control: the discrete-time case. IEEE Transactions on Automatic Control, 2012, 57(4): 1040-1045
    [16] Chen Ming-Jie, Lan Hai, Sun Shi-Feng. GA in fuzzy PID control of the boiler steam pressure. Techniques of Automation and Applications, 2008, 27(1): 12-16(陈明杰, 兰海, 孙世峰. 遗传算法在锅炉蒸汽压力模糊PID控制中的应用研究. 自动化技术与应用, 2008, 27(1): 12-16)
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出版历程
  • 收稿日期:  2013-07-08
  • 修回日期:  2014-02-26
  • 刊出日期:  2014-09-20

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