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系统H范数计算:Lyapunov函数的直接优化方法

刘秀翀 王占山

刘秀翀, 王占山. 系统H∞范数计算:Lyapunov函数的直接优化方法. 自动化学报, 2019, 45(8): 1606-1610. doi: 10.16383/j.aas.c180619
引用本文: 刘秀翀, 王占山. 系统H范数计算:Lyapunov函数的直接优化方法. 自动化学报, 2019, 45(8): 1606-1610. doi: 10.16383/j.aas.c180619
LIU Xiu-Chong, WANG Zhan-Shan. Calculation of the System H∞ Norm: a Lyapunov Function Optimization Method. ACTA AUTOMATICA SINICA, 2019, 45(8): 1606-1610. doi: 10.16383/j.aas.c180619
Citation: LIU Xiu-Chong, WANG Zhan-Shan. Calculation of the System H Norm: a Lyapunov Function Optimization Method. ACTA AUTOMATICA SINICA, 2019, 45(8): 1606-1610. doi: 10.16383/j.aas.c180619

系统H范数计算:Lyapunov函数的直接优化方法

doi: 10.16383/j.aas.c180619
基金项目: 

国家重点研究发展计划 2017YFF0108800

详细信息
    作者简介:

    王占山   东北大学信息科学与工程学院教授.主要研究方向为递归神经网络的稳定性分析, 故障诊断, 容错控制, 非线性控制理论.E-mail:wangzhanshan@ise.neu.edu.cn

    通讯作者:

    刘秀翀   东北大学信息科学与工程学院讲师.主要研究方向为控制理论与应用, 电力电子与电力传动.本文通信作者.E-mail:liuxiuchong@mail.neu.edu.cn

Calculation of the System H Norm: a Lyapunov Function Optimization Method

Funds: 

National Key Research and Development Program of China 2017YFF0108800

More Information
    Author Bio:

      Professor at the College of Information Science and Engineering, Northeastern University. His research interest covers stability analysis of recurrent neural networks, fault diagnosis, fault tolerant control, and nonlinear control theory

    Corresponding author: LIU Xiu-Chong  #160; Lecturer at the College of Information Science and Engineering, Northeastern University. His research interest covers control theory and applications, power electronics, and power drives. Corresponding author of this paper
  • 摘要: 研究了李雅普诺夫函数的选择对求解系统H范数的影响,提出了一种李雅普诺夫函数的直接优化方法,该方法通过优化黎卡提不等式中的李雅普诺夫函数,给出了H范数的通用解析表达式,实现了二阶系统H范数的精确求解.不同于需要繁琐优化过程的线性矩阵不等式(Linear matrix inequality,LMI)方法,本文提供了一种有效的途径以直接求解系统H范数.
    1)  本文责任编委 高会军
  • 图  1  函数分析

    Fig.  1  Function analysis

    表  1  $H_{\infty}$范数分析($\alpha = 2$)

    Table  1  $H_{\infty}$ norm analysis ($\alpha = 2$)

    $\lambda$ $\nu$ MATLAB 定理4 稳态误差$\|A^{-1}\|$ 状态上界
    2 6 0.626 0.626 0.307 0.626
    2 4 0.626 0.626 0.419 0.626
    2 2 0.626 0.626 0.588 0.626
    2 1.2 0.626 0.626 0.626 0.626
    2 1 0.622 0.622 0.622 0.622
    2 0 0.501 0.501 0.501 0.501
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-09-18
  • 录用日期:  2019-02-03
  • 刊出日期:  2019-08-20

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