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噪声下相互依存网络的自适应H异质同步

郭天姣 涂俐兰

郭天姣, 涂俐兰. 噪声下相互依存网络的自适应H∞异质同步. 自动化学报, 2020, 46(6): 1229-1239. doi: 10.16383/j.aas.c180075
引用本文: 郭天姣, 涂俐兰. 噪声下相互依存网络的自适应H异质同步. 自动化学报, 2020, 46(6): 1229-1239. doi: 10.16383/j.aas.c180075
GUO Tian-Jiao, TU Li-Lan. Adaptive H∞ Heterogeneous Synchronization for 0.3 nterdependent Networks With Noise. ACTA AUTOMATICA SINICA, 2020, 46(6): 1229-1239. doi: 10.16383/j.aas.c180075
Citation: GUO Tian-Jiao, TU Li-Lan. Adaptive H Heterogeneous Synchronization for 0.3 nterdependent Networks With Noise. ACTA AUTOMATICA SINICA, 2020, 46(6): 1229-1239. doi: 10.16383/j.aas.c180075

噪声下相互依存网络的自适应H异质同步

doi: 10.16383/j.aas.c180075
基金项目: 

国家自然科学基金 61473338

详细信息
    作者简介:

    郭天姣  武汉科技大学理学院硕士研究生.主要研究方向为复杂网络的同步与控制. E-mail: guotianjiao@wust.edu.cn

    通讯作者:

    涂俐兰  武汉科技大学冶金工业过程系统科学湖北省重点实验室教授, 武汉科技大学理学院教授.主要研究方向为复杂网络的同步, 控制与拓扑结构识别.本文通信作者. E-mail: tulilan@wust.edu.cn

Adaptive H Heterogeneous Synchronization for 0.3 nterdependent Networks With Noise

Funds: 

National Natural Science Foundation of China 61473338

More Information
    Author Bio:

    GUO Tian-Jiao   Master student at the College of Science, Wuhan University of Science and Technology. Her research interest covers synchronization and control of complex networks

    Corresponding author: TU Li-Lan  Professor at Hubei Province Key Laboratory of Systems Science in Metallurgical Process, Wuhan University of Science and Technology, and at College of Science, Wuhan University of Science and Technology. Her research interest covers synchronization, control and topology identiflcation of complex networks. Corresponding author of this paper
  • 摘要: 针对具有噪声的相互依存复杂动力网络, 本文研究了它的局部自适应H异质同步问题.该网络由两个具有"一对一"相互依赖关系的子网构成, 子网内部耦合和子网间的耦合均含有未知但有界的非线性函数.基于李雅普诺夫稳定性理论、线性矩阵不等式(Linear matrix inequality, LMI)技术和自适应以及H控制方法, 本文提出了使得相互依存网络在外部噪声的干扰下, 两个子网各自达到一致的充分条件.这些条件不仅可以保证受扰动的网络获得鲁棒渐近同步而且可以让网络达到一个给定的鲁棒H水平.最后的数值模拟验证了提出的方法的有效性以及可行性.
    Recommended by Associate Editor LU Ren-Quan
    1)  本文责任编委 鲁仁全
  • 图  1  噪声下子网1误差系统迹图

    Fig.  1  The trajectory of the error system of sub-network 1 with noise

    图  2  噪声下子网2误差系统轨迹图

    Fig.  2  The trajectory of the error system of sub-network 2 with noise

    图  3  无噪声子网1误差系统轨迹图

    Fig.  3  The trajectory of the error system of sub-network 1 without noise

    图  4  无噪声子网2误差系统轨迹图

    Fig.  4  The trajectory of the error system of sub-network 2 without noise

    图  5  噪声下子网1自适应律轨迹图

    Fig.  5  The adaptive laws of sub-network 1 with noise

    图  6  噪声下子网2自适应律轨迹图

    Fig.  6  The adaptive laws of sub-network 2 with noise

    图  7  无噪声子网1自适应律轨迹图

    Fig.  7  The adaptive laws of sub-network 1 without noise

    图  8  无噪声子网2自适应律轨迹图

    Fig.  8  The adaptive laws of sub-network 2 without noise

    图  9  子网误差H范数和外部噪声H范数比值开方与时间关系图((a)子网1; (b)子网2)

    Fig.  9  The square root of the ratio between the H norm of the error and noise concerning time ((a) Sub-network 1; (b) Sub-network 2)

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出版历程
  • 收稿日期:  2018-01-30
  • 录用日期:  2018-08-21
  • 刊出日期:  2020-07-10

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