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Rev. Sci. Instrum. 79, 103704 (2008); http://dx.doi.org/10.1063/1.2980377 (14 pages)

High bandwidth control of precision motion instrumentation

Douglas A. Bristow1, Jingyan Dong2, Andrew G. Alleyne2, Placid Ferreira2, and Srinivas Salapaka2

1Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology, Rolla, Missouri 65401, USA
2Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA

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(Received 4 June 2008; accepted 20 August 2008; published online 15 October 2008)

This article presents a high-bandwidth control design suitable for precision motion instrumentation. Iterative learning control (ILC), a feedforward technique that uses previous iterations of the desired trajectory, is used to leverage the repetition that occurs in many tasks, such as raster scanning in microscopy. Two ILC designs are presented. The first design uses the motion system dynamic model to maximize bandwidth. The second design uses a time-varying bandwidth that is particularly useful for nonsmooth trajectories such as raster scanning. Both designs are applied to a multiaxis piezoelectric-actuated flexure system and evaluated on a nonsmooth trajectory. The ILC designs demonstrate significant bandwidth and precision improvements over the feedback controller, and the ability to achieve precision motion control at frequencies higher than multiple system resonances.

© 2008 American Institute of Physics

Article Outline

  1. INTRODUCTION
  2. SYSTEM DESCRIPTION
    1. Frequency regions
    2. Feedback control
    3. Feedforward control
  3. ITERATIVE LEARNING CONTROL
    1. First-order ILC algorithm
    2. ILC analysis
      1. Convergence
      2. ILC asymptotic performance
  4. HIGH-BANDWIDTH LEARNING ALGORITHM DESIGN
    1. Learning filter L
      1. Construction of mathinv(z)
        1. d -step delayed inversion
        2. Stabilization of the inversion
        3. Noncausal delay correction
      2. Learning rate selection
    2. LTI Q design
      1. Zero-phase filter construction
      2. Bandwidth selection
  5. AN ADVANCED Q DESIGN FOR NONSMOOTH TRAJECTORIES
    1. Time-varying Q -filter
    2. Time-frequency analysis
    3. Filter shaping
    4. Parameter tuning
  6. APPLICATION: PARALLEL KINEMATIC MECHANISM
    1. Feedback control results
    2. ILC1: LTI Q -filter
    3. ILC2: LTV Q -filter
  7. CONCLUSIONS

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KEYWORDS and PACS

PACS

  • 07.05.Dz

    Control systems

  • 07.05.Mh

    Neural networks, fuzzy logic, artificial intelligence

  • 07.07.Tw

    Servo and control equipment; robots

ARTICLE DATA

PUBLICATION DATA

ISSN

0034-6748 (print)  
1089-7623 (online)

For access to fully linked references, you need to log in.
    F. J. Giessibl, Rev. Mod. Phys. 75, 949 (2003).

    S. Salapaka, A. Sebastian, J. P. Cleveland, and M. V. Salapaka, Rev. Sci. Instrum. 73, 3232 (2002)RSINAK000073000009003232000001.

    Y. Li and J. Bechhoefer, Rev. Sci. Instrum. 78, 013702 (2007)RSINAK000078000001013702000001.

    Q. Zou, C. V. Giessen, J. Garbini, and S. Devasia, Rev. Sci. Instrum. 76, 023701 (2005)RSINAK000076000002023701000001.


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