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任意初态下的迭代学习控制策略
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  • 英文篇名:Iterative Learning Control with the Arbitrary Initial State Errors
  • 作者:李国军 ; 韩一士 ; 陈东杰 ; 许中石
  • 英文作者:LI Guojun;HAN Yishi;CHEN Dongjie;XU Zhongshi;Basic Courses Department,Zhejiang Police College;
  • 关键词:迭代学习控制 ; 初始修正 ; 收敛 ; 线性矩阵不等式
  • 英文关键词:Iterative learning control;;Initial rectifying;;Convergence;;Linear matrix inequality
  • 中文刊名:YISU
  • 英文刊名:Mathematica Applicata
  • 机构:浙江警察学院公共基础部;
  • 出版日期:2019-03-25 15:28
  • 出版单位:应用数学
  • 年:2019
  • 期:v.32;No.133
  • 基金:浙江省自然科学基金(LQ18G010001);; 北京东方计量测试研究所刘尚合院士专家工作站静电研究基金(BOIMTLSHJD20182001)资助项目;; 浙江警察学院校级课题(2017QTY042)
  • 语种:中文;
  • 页:YISU201902017
  • 页数:8
  • CN:02
  • ISSN:42-1184/O1
  • 分类号:155-162
摘要
针对一类在有限区间上执行重复任务的动态系统,本文提出一种迭代学习初始修正算法,用于解决各次迭代过程中的任意初态问题.通过构造一个虚拟误差函数来分析算法的收敛性,分析结果表明该算法可在指定区间上实现对期望轨迹的一致性跟踪,并通过求解线性矩阵不等式的方法获得具体的矩阵型控制增益.最后,通过数值结果,验证了算法的有效性.
        In this paper, we present an iterative learning initial rectifying algorithm for a class of dynamic systems, where the initial state of every iteration can be arbitrary. The convergence analysis results are addressed through a virtual error function. Furthermore, the matrix type control gains can be obtained via solving the linear matrix inequality. Finally, the effectiveness of the stated algorithm are demonstrated by some simulation results.
引文
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