Performance analysis for uncertain multivariable systems obtained by system identification

Arash Sadeghzadeh

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)


This article provides a framework for robust performance analysis of linear time-invariant uncertain multivariable systems obtained by classical system identification methods. The performance measures are in terms of H 2 or H ∞ norm of a closed-loop transfer matrix. An upper bound for the performance analysis criterion is computed via an LMI-based optimisation problem. The LFT description is used as a tool for uncertainty modelling. The proposed performance conditions are derived based on using the parameter-dependent Lyapunov functions and are deduced via a parametrisation for the set of multipliers corresponding to the ellipsoidal uncertainty set delivered by system identification procedure. The effectiveness of the proposed analysis approach is demonstrated by a numerical example.

Original languageEnglish
Pages (from-to)547-555
Number of pages9
JournalInternational Journal of Systems Science
Issue number3
Publication statusPublished - 1 Mar 2014
Externally publishedYes


  • ellipsoidal parametric uncertainty
  • performance analysis
  • system identification


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