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网络信息模式下分布式系统协调预测控制

郑毅 李少远

郑毅, 李少远. 网络信息模式下分布式系统协调预测控制. 自动化学报, 2013, 39(11): 1778-1786. doi: 10.3724/SP.J.1004.2013.01778
引用本文: 郑毅, 李少远. 网络信息模式下分布式系统协调预测控制. 自动化学报, 2013, 39(11): 1778-1786. doi: 10.3724/SP.J.1004.2013.01778
ZHENG Yi, LI Shao-Yuan. Networked Cooperative Distributed Model Predictive Control for Dynamic Coupling Systems. ACTA AUTOMATICA SINICA, 2013, 39(11): 1778-1786. doi: 10.3724/SP.J.1004.2013.01778
Citation: ZHENG Yi, LI Shao-Yuan. Networked Cooperative Distributed Model Predictive Control for Dynamic Coupling Systems. ACTA AUTOMATICA SINICA, 2013, 39(11): 1778-1786. doi: 10.3724/SP.J.1004.2013.01778

网络信息模式下分布式系统协调预测控制

doi: 10.3724/SP.J.1004.2013.01778
基金项目: 

国家重点基础研究发展计划(973计划)(2013CB035500),国家自然科学基金(61233004,61221003)和高等学校博士学科点专项科研基金(20120073130006)资助

详细信息
    作者简介:

    郑毅 上海交通大学电子信息与电气工程学院助理研究员. 2010 年于上海交通大学获得控制理论与控制工程博士学位. 主要研究方向为工业过程的建模, 控制与优化. E-mail: yizheng@sjtu.edu.cn

Networked Cooperative Distributed Model Predictive Control for Dynamic Coupling Systems

Funds: 

Supported by National Basic Research Program of China (973 Program) (2013CB035500), National Natural Science Foundation of China (61233004, 61221003), and Specialized Research Fund for the Doctoral Program of Higher Education (20120073130006)

  • 摘要: 工业系统中广泛存在一类由多个相互关联的子系统组成的大系统. 尽管分布式控制结构的性能没有集中式控制好,但由于其具有较高的灵活性和容错性,相对于集中控制更加适合控制上述系统.在保持容错性的情况下如何提高系统的整体性能是分布式控制的一个难点问题.本文提出了一种分布式预测控制(Distributed model predictive control, DMPC)方法,该方法通过在各子系统预测控制器的性能指标中加入输入变量对其下游子系统的影响的二次函数,来扩大分布式预测控制的协调度,进而在不增加网络连通度,不改变系统容错性的前提下,提高系统的性能.另外,本文给出了基于该协调策略的带输入约束的分布式预测控制器的设计方法,在初始可行的前提下,该方法相继可行并可保证系统渐近稳定.
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出版历程
  • 收稿日期:  2013-08-13
  • 修回日期:  2013-08-31
  • 刊出日期:  2013-11-20

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