Combined H-feedback control and iterative learning control design with application to nanopositioning systems

Brian E. Helfrich, Chibum Lee, Douglas A. Bristow, X. H. Xiao, Jingyan Dong, A. G. Alleyne, Srinivasa M. Salapaka, Placid M. Ferreira

Research output: Contribution to journalArticlepeer-review

77 Scopus citations

Abstract

This paper examines a coordinated feedback and feedforward control design strategy for precision motion control (PMC) systems. It is assumed that the primary exogenous signals are repeated; including disturbances and references. Therefore, an iterative learning control (ILC) feedforward strategy can be used. The introduction of additional non-repeating exogenous signals, including disturbances, noise, and reset errors, necessitates the proper coordination between feedback and feedforward controllers to achieve high performance. A novel ratio of repeated versus non-repeated signal power in the frequency domain is introduced and defined as the repetitive-to-non-repetitive (RNR) ratio. This frequency specific ratio allows for a new approach to delegating feedback and feedforward control efforts based on RNR value. A systematic procedure for control design is given whereby the feedback addresses the non-repeating exogenous signal content ( RNR < 0 dB}) and the feedforward ILC addresses the repeating signal content ( RNR > dB). To illustrate the design approach, two case studies using different nano-positioning devices are given.

Original languageEnglish (US)
Article number5169845
Pages (from-to)336-351
Number of pages16
JournalIEEE Transactions on Control Systems Technology
Volume18
Issue number2
DOIs
StatePublished - Mar 2010
Externally publishedYes

Bibliographical note

Funding Information:
Manuscript received July 31, 2008. Manuscript received in final form March 15, 2009. First published July 21, 2009; current version published February 24, 2010. Recommended by Associate Editor S. Devasia. This work was supported by the Nano-CEMMS Center, University of Illinois, which is funded by the NSF under Grant DMI-0328162, and by the MechSE Department fellowship.

Keywords

  • Iterative learning control (ILC)
  • Nanopositioning
  • Precision motion control (PMC)

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