Adaptive parameter identification of linear SISO systems with unknown time-delay

Jing Na*, Xuemei Ren, Yuanqing Xia

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

76 Citations (Scopus)


An adaptive online parameter identification is proposed for linear single-input-single-output (SISO) time-delay systems to simultaneously estimate the unknown time-delay and other parameters. After representing the system as a parameterized form, a novel adaptive law is developed, which is driven by appropriate parameter estimation error information. Consequently, the identification error convergence can be proved under the conventional persistent excitation (PE) condition, which can be online tested in this paper. A finite-time (FT) identification scheme is further studied by incorporating the sliding mode scheme into the adaptation to achieve FT error convergence. The previously imposed constraint on the system relative degree is removed and the derivatives of the input and output are not required. Comparative simulation examples are provided to demonstrate the validity and efficacy of the proposed algorithms.

Original languageEnglish
Pages (from-to)43-50
Number of pages8
JournalSystems and Control Letters
Issue number1
Publication statusPublished - 1 Apr 2014


  • Parameter estimation
  • System identification
  • Time-delay systems


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