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A Q, L Factorization of Norm-Optimal Iterative Learning Control

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper we consider the Norm-Optimal Iterative Learning Control (ILC) problem for discrete-time linear multi-input, multi-output systems. The solution to this problem is well known and naturally factors into a form with a filter on the previous control, Lu and a filter on the previous error, Le. We show that this solution can always be factored into a Q,L form where Q filters the previous control and QL filters the previous error. This latter form is popularized with frequency domain ILC designs, and this common factorization suggests some general relationships between Norm-Optimal and frequency domain design, which are explored. Although the Q,L factorization is well known for some special cases, the results here are general and include differently dimensioned control and observation windows.

Original languageAmerican English
Pages (from-to)2380-2384
Number of pages5
JournalProceedings of the 47th IEEE Conference on Decision and Control (2008, Coral Beach, FL)
DOIs
StatePublished - Dec 11 2008
Event47th IEEE Conference on Decision and Control, CDC 2008 - Cancun, Mexico
Duration: Dec 9 2008Dec 11 2008

ASJC Scopus Subject Areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Keywords

  • Iterative Learning Control
  • Optimal Control

Disciplines

  • Aerospace Engineering
  • Mechanical Engineering

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