Improving Robustness Filter Bandwidth in Repetitive Control by Considering Model Mismatch

Improving Robustness Filter Bandwidth in Repetitive Control by Considering Model Mismatch Repetitive control (RC) is used to track and reject periodic signals by including a model of a periodic signal in the feedback path. The performance of RC can be improved by including an inverse plant response filter, but due to modeling uncertainty at high frequencies, a low‐pass robustness filter is also required to limit the bandwidth of the signal model and ensure stability. The design of robustness filters is presently ad‐hoc, which may result in excessively conservative performance. This article proposes a new automatic method for designing the robustness filter based on convex optimization and an uncertainty model. Experimental results on a nanopositioning system demonstrate that the proposed method outperforms the traditional brick‐wall filter approach. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Asian Journal of Control Wiley

Improving Robustness Filter Bandwidth in Repetitive Control by Considering Model Mismatch

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Publisher
Wiley
Copyright
© 2018 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd
ISSN
1561-8625
eISSN
1934-6093
DOI
10.1002/asjc.1437
Publisher site
See Article on Publisher Site

Abstract

Repetitive control (RC) is used to track and reject periodic signals by including a model of a periodic signal in the feedback path. The performance of RC can be improved by including an inverse plant response filter, but due to modeling uncertainty at high frequencies, a low‐pass robustness filter is also required to limit the bandwidth of the signal model and ensure stability. The design of robustness filters is presently ad‐hoc, which may result in excessively conservative performance. This article proposes a new automatic method for designing the robustness filter based on convex optimization and an uncertainty model. Experimental results on a nanopositioning system demonstrate that the proposed method outperforms the traditional brick‐wall filter approach.

Journal

Asian Journal of Control – Wiley

Published: Jan 1, 2018

Keywords: ; ; ;

References

  • Repetitive control system: A new type servo system for periodic exogenous signals
    Hara, S.; Yamamoto, Y.; Omata, T.; Nakano, M.
  • Internal model principle of control‐theory
    Francis, B. A.; Wonham, W. M.
  • Design of discrete‐time repetitive control system for pole placement and application
    Yamada, M.; Riadh, Z.; Funahashi, Y.
  • Repetitive control for the track‐following servo system of an optical disk drive
    Moon, J.; Lee, M.; Chung, M. J.
  • Design of noise and period‐time robust high‐order repetitive control, with application to optical storage
    Steinbuch, M.; Weiland, S.; Singh, T.
  • Robust performance control of electrohydraulic actuators for electronic cam motion generation
    Kim, D. H.; Tsao, T.
  • A repetitive‐based controller for the compensation of 6ℓ ± 1 harmonic components
    Escobar, G.; Hernandez‐Briones, P. G.; Martinez, P. R.; Hernandez‐Gomez, M.; Torres‐Olguin, R. E.
  • Bridging the gap between conventional and video‐speed scanning probe microscopes
    Fleming, A. J.; Kenton, B. J.; Leang, K. K.
  • Design and control for high‐speed nanopositioning: Serial‐kinematic nanopositioners and repetitive control for nanofabrication
    Shan, Y.; Leang, K. K.
  • Design and analysis of discrete‐time repetitive control for scanning probe microscopes
    Aridogan, U.; Shan, Y.; Leang, K. K.
  • Analysis and synthesis of discrete‐time repetitive controllers
    Tomizuka, M.; Tsao, T.; Chew, K.
  • Designing optimized FIR repetitive controllers from noisy frequency response data
    Panomruttanarug, B.; Longman, R. W.
  • On the theory and design of linear repetitive control systems
    Longman, R. W.
  • Constrained least square design of FIR filters without specified transition bands
    Selesnick, I. W.; Lang, M.; Burrus, C. S.
  • A simplified method for discrete‐time repetitive control using model‐less finite impulse response filter inversion
    Teo, Y. R.; Eielsen, A; Gravdahl, J. T.; Fleming, A. J.
  • Techniques for designing finite‐duration impulse‐response digital filters
    Rabiner, L. R.
  • Steady‐state and stochastic performance of a modified discrete‐time prototype repetitive controller
    Chew, Kok‐Kia; Tomizuka, M.
  • Internal and external stability and robust stability condition for a class of infinite‐dimensional systems
    Yamamoto, Y.; Hara, S.
  • Essays on control: Perspectives in the theory and its applications
    Yamamoto, Y.
  • Robust high‐order repetitive control: Optimal performance trade‐offs
    Pipeleers, G.; Demeulenaere, B.; De Schutter, J.; Swevers, J.
  • System Identification: Theory for the User
    Ljung, L.
  • The use of fast fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms
    Welch, P. D.
  • Designing robust repetitive controllers
    Osburn, A. W.; Franchek, M. A.
  • How exciting can a signal really be?
    Mareels, I. M. Y.; Gevers, M.; Bitmead, R. R.; Lygeros, J.; Kosut, R. L.; Poubelle, M. A.
  • Robust optimal experiment design for system identification
    Rojas, C. R.; Welsh, J. S.; Goodwin, G. C.; Feuer, A.
  • Recent Advances in Learning and Control
    Grant, M.; Boyd, S.
  • A computer program for designing optimum FIR linear phase digital filters
    McClellan, J. H.; Parks, T. W.; Rabiner, L. R.
  • Design and control of a three‐axis serial‐kinematic high‐bandwidth nanopositioner
    Kenton, B. J.; Leang, K. K.
  • Low‐order continuous‐time robust repetitive control: Application in nanopositioning
    Eielsen, A. A.; Gravdahl, J. T.; Leang, K. K.
  • Control System Design
    Goodwin, G. C.; Graebe, S. F.; Salgado, M. E.

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