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Iterative Learning Control for Spiral Scanning Patterns in Atomic Force Microscopy

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Intelligent Robotics and Applications (ICIRA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10985))

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Abstract

This paper applies the Iterative Learning Control (ILC) strategy in order to increase the performance of spiral patterns tracking using simple proportional-integral controllers. Such patterns arise in different areas where fast and smooth reference signals are required, as for example the Atomic Force Microscopy. The ILC is implemented as a feedforward control strategy that makes use of the information obtained in previous batches in order to improve the tracking performance, normally applied along side an already implemented feedback controller. A new suitable scanning reference pattern is also proposed, which allows the application of the iterative learning concept in repetitive tasks. The proposed control strategy is evaluated through a set of simulations using a numerical model of an Atomic Force Microscope nanopositioner. The numerical results obtained through the simulations show that the proposed ILC structure is able to improve the performance of a traditional proportional-integral controller available in the area.

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References

  1. Jin, X.: Non-repetitive trajectory tracking for joint position constrained robot manipulators using iterative learning control. In: 2016 IEEE 55th Conference on Decision and Control (CDC), pp. 5490–5495, December 2016

    Google Scholar 

  2. Bazaei, A., Maroufi, M., Fowler, A.G., Moheimani, S.O.R.: Internal model control for spiral trajectory tracking with MEMS AFM scanners. IEEE Trans. Control Syst. Technol. 24(5), 1717–1728 (2016)

    Article  Google Scholar 

  3. Ramos, G.A., Soto-Perez, R.A., Cifuentes, J.A.: A varying frequency LPV-based control strategy for three-phase inverters. IEEE Trans. Ind. Electron. 64(9), 7599–7608 (2017)

    Article  Google Scholar 

  4. Mahmood, I.A., Moheimani, S.O.R., Bhikkaji, B.: A new scanning method for fast atomic force microscopy. IEEE Trans. Nanotechnol. 10(2), 203–216 (2011)

    Article  Google Scholar 

  5. Meyer, E., Hug, H.J., Bennewitz, R.: Scanning Probe Microscopy: The Lab on a Tip. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-662-09801-1

    Book  Google Scholar 

  6. Rana, M.S., Pota, H.R., Petersen, I.R.: Spiral scanning with improved control for faster imaging of AFM. IEEE Trans. Nanotechnol. 13(3), 541–550 (2014)

    Article  Google Scholar 

  7. Ziegler, D., Meyer, T.R., Amrein, A., Bertozzi, A.L., Ashby, P.D.: Ideal scan path for high-speed atomic force microscopy. IEEE/ASME Trans. Mechatron. 22(1), 381–391 (2017)

    Article  Google Scholar 

  8. Owens, D.H.: Iterative learning control: an optimization paradigm (2015)

    Google Scholar 

  9. Bristow, D., Tharayil, M., Alleyne, A.: A survey of iterative learning control. IEEE Control Syst. Mag. 26(3), 96–114 (2006)

    Article  Google Scholar 

  10. Leyva-Ramos, J., Ortiz-Lopez, M.G., Diaz-Saldierna, L.H.: Disturbance rejection control scheme for optical disk drive systems. IEEE Trans. Magn. 46(10), 3772–3777 (2010)

    Article  Google Scholar 

  11. Chen, C.T.: Linear System Theory and Design, p. 334 (1999)

    Google Scholar 

  12. Bazaei, A., Maroufi, M., Moheimani, S.R.: Tracking of constant-linear-velocity spiral trajectories by approximate internal model control. In: 2017 IEEE Conference on Control Technology and Applications (CCTA), pp. 129–134. IEEE, August 2017

    Google Scholar 

  13. Habibullah, H., Pota, H., Petersen, I.: Phase-locked loop-based proportional integral control for spiral scanning in an atomic force microscope. In: IFAC Proceedings Volumes, 19th IFAC World Congress, vol. 47, no. 3, pp. 6563–6568 (2014)

    Google Scholar 

  14. Żak, S.H.: Systems and Control. Oxford University Press, New York (2003)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Instituto Tecnológico de Aeronáutica, São José dos Campos, Brazil

    Matheus S. de Oliveira

  2. School of Technology, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil

    Aurélio T. Salton

Authors
  1. Matheus S. de Oliveira
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  2. Aurélio T. Salton
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Corresponding author

Correspondence to Aurélio T. Salton .

Editor information

Editors and Affiliations

  1. University of Newcastle, Callaghan, New South Wales, Australia

    Zhiyong Chen

  2. University of Newcastle, Callaghan, New South Wales, Australia

    Alexandre Mendes

  3. University of Newcastle, Callaghan, New South Wales, Australia

    Yamin Yan

  4. Shenzhen Institutes of Advanced Technology, Shenzhen, China

    Shifeng Chen

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de Oliveira, M.S., Salton, A.T. (2018). Iterative Learning Control for Spiral Scanning Patterns in Atomic Force Microscopy. In: Chen, Z., Mendes, A., Yan, Y., Chen, S. (eds) Intelligent Robotics and Applications. ICIRA 2018. Lecture Notes in Computer Science(), vol 10985. Springer, Cham. https://doi.org/10.1007/978-3-319-97589-4_33

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  • DOI: https://doi.org/10.1007/978-3-319-97589-4_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97588-7

  • Online ISBN: 978-3-319-97589-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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