System Identification in <i>H</i>^∞ for Multiple Sets of Data

• Tanaka Hideyuki

  Graduate School of Education, Hiroshima University

Bibliographic Information

Other Title

• System Identification in H[∞] for Multiple Sets of Data

Abstract

This paper studies identification in H^∞ based on multiple sets of data in the frequency domain. The traditional H^∞ worst-case identification and the stochastic identification settings are revisited, and a new problem formulation is presented by modifying the H^∞ worst-case identification setting. In the literature, given a single set of data, the limited experimental information subject to finite samples has been focused on, while this paper considers uncertainty modeling given multiple sets of data. It is shown that the problem is solved by means of linear matrix inequalities and subspace identification methods in the frequency domain.

Journal

• IEEJ Transactions on Electronics, Information and Systems

  IEEJ Transactions on Electronics, Information and Systems 132 (6), 926-931, 2012

  The Institute of Electrical Engineers of Japan

Keywords

• <i>H</i>^∞ worst-case identification
• subspace system identification
• multiple sets of data
• robust control

Details

• CRID: 1390282679583747200
• NII Article ID: 10030606509
• NII Book ID: AN10065950
• DOI: 10.1541/ieejeiss.132.926
• BIBCODE: 2012ITEIS.132..926T
• ISSN: 13488155
• ISSN: 03854221
• NDL BIB ID: 023823672
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I023823672
• Web Site: https://www.jstage.jst.go.jp/article/ieejeiss/132/6/132_926/_pdf
• Text Lang: en
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed