引用本文:黄金峰,张合新,胡友涛,张植.基于有限记忆变遗忘因子的子空间辨识算法[J].控制理论与应用,2012,29(7):893~898.[点击复制]
HUANG Jin-feng,ZHANG He-xin,HU You-tao,ZHANG zhi.Subspace identification algorithm based on finite-memory variable forgetting factor[J].Control Theory and Technology,2012,29(7):893~898.[点击复制]
基于有限记忆变遗忘因子的子空间辨识算法
Subspace identification algorithm based on finite-memory variable forgetting factor
摘要点击 2366  全文点击 1614  投稿时间:2011-02-28  修订日期:2012-01-04
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DOI编号  10.7641/j.issn.1000-8152.2012.7.CCTA110190
  2012,29(7):893-898
中文关键词  子空间辨识  变遗忘因子  有限记忆  欧氏距离
英文关键词  subspace identification  variable forgetting factor  finite-memory  Euclidean-distance
基金项目  国家自然科学基金面上资助项目(61074072).
作者单位E-mail
黄金峰* 第二炮兵工程大学 自动控制系 star3618@126.com 
张合新 第二炮兵工程大学 自动控制系  
胡友涛 第二炮兵工程大学 自动控制系  
张植 第二炮兵驻国营二OO厂军代室  
中文摘要
      针对传统递推子空间辨识算法对时变参数跟踪速度慢的问题, 基于自适应变遗忘因子机制提出一种新的子空间辨识算法. 为此首先设计了变遗忘因子作用下输入输出Hankel矩阵的更新机制; 然后运用系统矩阵特征值空间欧氏距离信息实现变遗忘因子的自适应更新; 最后为隔断历史数据的作用, 采用有限记忆法进一步改进算法. 理论及仿真结果表明, 新算法跟踪速度快、跟踪效果好.
英文摘要
      A novel subspace identification algorithm is proposed based on self-adaptive variable forgetting factor to deal with the problem of low convergence rate in traditional algorithms. The update form of input-output data Hankel matrices is redesigned. The self-adaptive forgetting factor is realized with the help of Euclidean-distance of eigenvalues of the identified system matrix. In order to eliminate the effect of old data, a modified algorithm is designed based on the finite-memory method. Theoretical proof and simulation results show that the tracking response of the modified algorithm is faster and the performance is better than the traditional algorithms.