首页    期刊浏览 2024年09月16日 星期一
登录注册

文章基本信息

  • 标题:Consistent Estimate of Innovations Model * * This work is supported by JSPS KAKENHI Grant Number 15K06146.
  • 本地全文:下载
  • 作者:Kenji Ikeda
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2016
  • 卷号:49
  • 期号:13
  • 页码:129-134
  • DOI:10.1016/j.ifacol.2016.07.939
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper proposes a numerical solution of the consistent estimates of Kalman gain and the covariance of the innovations process in the innovations model. The estimates are given as solutions of some BMI problem, so an iterative algorithm for solving the problem will be required. An algorithm for a class of BMI problems in which the objective function is non-increasing is applied for solving this problem. Explicit formulations of the estimation error in PO-MOESP method are also derived and shown to be consistent so that the consistent estimate of all the parameters in the innovations model are obtained.
  • 关键词:KeywordsSystem identificationSubspace methodsConsistencyKalman filtersNonlinear programmingNumerical solutions
国家哲学社会科学文献中心版权所有