Flexible ILC : towards a convex approach for non-causal rational basis functions

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Iterative learning control (ILC) is subject to a trade-off between effective compensation of repeating disturbances, and amplification of non-repeating disturbances. Although important progress has been made in enhancing the flexibility of ILC to non-repeating tasks by means of basis functions, at present high performance comes at the cost of non-convex optimization. The aim of this paper is to develop a convex approach to ILC with rational basis functions. A key aspect of the proposed approach is the use of orthonormal basis functions in L2, such that non-causal control actions can be utilized. The benefits of using non-causal rational basis functions in ILC are demonstrated by means of a relevant example.
Original languageEnglish
Pages (from-to)12107-12112
Number of pages6
Issue number1
Publication statusPublished - Aug 2017
Event20th World Congress of the International Federation of Automatic Control (IFAC 2017 World Congress) - Toulouse, France
Duration: 9 Jul 201714 Jul 2017
Conference number: 20


  • Iterative learning control
  • motion control
  • preview control
  • rational basis functions


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