On the convergence of iterative learning control

M. Mahdi Ghazaei Ardakani, Sei Zhen Khong, Bo Bernhardsson

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

We derive frequency-domain criteria for the convergence of linear iterative learning control (ILC) on finite-time intervals that are less restrictive than existing ones in the literature. In particular, the former can be used to establish the convergence of ILC in certain cases where the latter are violated. The results cover ILC with non-causal filters and provide insights into the transient behaviors of the algorithm before convergence. We also stipulate some practical rules under which ILC can be applied to a wider range of applications.

Original languageEnglish (US)
Pages (from-to)266-273
Number of pages8
JournalAutomatica
Volume78
DOIs
StatePublished - Apr 1 2017

Bibliographical note

Funding Information:
This work was supported by the Swedish Research Council through LCCC Linnaeus Center and the eLLIIT Excellence Center at Lund University and Institute for Mathematics and its Applications with funds provided by the National Science Foundation. The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Changyun Wen under the direction of Editor Miroslav Krstic.

Publisher Copyright:
© 2017 Elsevier Ltd

Keywords

  • Convergence analysis
  • Iterative improvement
  • Learning control
  • Stability criteria
  • Transient stability analysis

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