On inversion-based approaches for feedforward and ILC

J. van Zundert, T.A.E. Oomen

Research output: Contribution to journalArticleAcademicpeer-review

64 Citations (Scopus)
360 Downloads (Pure)


System inversion is at the basis of many feedforward and learning control algorithms. The aim of this paper is to analyze several of these approaches in view of their subsequent use, showing inappropriate use that is previously overlooked. This leads to different insights and new approaches for both feedforward and learning. The methods are compared in various aspects, including finite vs. infinite preview, exact vs. approximate, and quality of inversion in various norms which directly relates to their use. In addition, extensions to (non-square) multivariable and time-varying systems are presented. The results are validated on a nonminimum-phase benchmark system.
Original languageEnglish
Pages (from-to)282-291
Number of pages10
Publication statusPublished - Apr 2018


  • model inversion
  • nonminimum phase
  • feedforward control
  • ILC
  • Model inversion
  • Feedforward control
  • Nonminimum phase


Dive into the research topics of 'On inversion-based approaches for feedforward and ILC'. Together they form a unique fingerprint.

Cite this