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多变量非线性系统的变阶采样迭代学习控制

孙明轩 李芝乐 朱胜

孙明轩, 李芝乐, 朱胜. 多变量非线性系统的变阶采样迭代学习控制. 自动化学报, 2013, 39(7): 1027-1036. doi: 10.3724/SP.J.1004.2013.01027
引用本文: 孙明轩, 李芝乐, 朱胜. 多变量非线性系统的变阶采样迭代学习控制. 自动化学报, 2013, 39(7): 1027-1036. doi: 10.3724/SP.J.1004.2013.01027
SUN Ming-Xuan, LI Zhi-Le, ZHU Sheng. Varying-Order Sampled-Data Iterative Learning Control for MIMO Nonlinear Systems. ACTA AUTOMATICA SINICA, 2013, 39(7): 1027-1036. doi: 10.3724/SP.J.1004.2013.01027
Citation: SUN Ming-Xuan, LI Zhi-Le, ZHU Sheng. Varying-Order Sampled-Data Iterative Learning Control for MIMO Nonlinear Systems. ACTA AUTOMATICA SINICA, 2013, 39(7): 1027-1036. doi: 10.3724/SP.J.1004.2013.01027

多变量非线性系统的变阶采样迭代学习控制

doi: 10.3724/SP.J.1004.2013.01027
基金项目: 

国家自然科学基金(61174034, 60874041),浙江省自然科学基金(LQ12F03005)资助

详细信息
    通讯作者:

    孙明轩

Varying-Order Sampled-Data Iterative Learning Control for MIMO Nonlinear Systems

Funds: 

Supported by National Natural Science Foundation of China (61174034, 60874041) and Zhejiang Provincial Natural Science Foundation of China (LQ12F03005)

  • 摘要: 针对存在初态误差的情形, 提出多变量非线性系统的变阶采样迭代学习控制方法. 相对固定阶迭代学习算法, 变阶算法可有效降低跟踪误差. 对变阶采样迭代学习算法进行了收敛性分析, 推导出收敛充分条件. 给出了变阶学习的两种实现策略-DD (Direct division)和DIP (Division in phases)策略. 数值仿真表明, 基于DIP策略的变阶采样迭代学习算法在获得较高的控制精度的同时, 具有较快的收敛速度.
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出版历程
  • 收稿日期:  2011-11-14
  • 修回日期:  2012-10-25
  • 刊出日期:  2013-07-20

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