Development of Robust Learning Control and Application to Motion Control

Meng-Shiun Tsai, Chung-Liang Yen, Hong-Tzong Yau

2012

Abstract

In this paper, the error dynamic equation of the ILC algorithm is derived with consideration of parameter uncertainties and noise. The H∞ frame work is utilized using the derived error dynamics to design the robust learning controller. The proper learning gain is designed based on an optimization process to ensure that both tracking performance and convergence condition can be achieved. Simulation and experiments are conducted to validate the robust learning algorithm and the system is stable ever under high payload uncertainty.

References

  1. Ahn, H. S., Chen, Y. Q., and Moore, K. L., 2007, Iterative learning control: brief survey and categorization, IEEE Trans. on Systems, Man, and Cybernetics, 37, 1099- 1121.
  2. French, M., and Rogers, E., 2000, Nonlinear iterative learning by an adaptive Lyapunov technique. International Journal of Control, 73, 840-850.
  3. Geng, Z., Carroll, R., and Xie, J., 1990, Two-dimensional model and algorithm analysis for a class of iterative learning control systems. Int. J. Control, 52, 833-862.
  4. Kuc, T. Y., Nam, K., and Lee, J. S., 1991, An iterative learning control of robot manipulators. IEEE Trans. Robot. Autom., 7, 835-841.
  5. Lee, J. H., and Lee, K. S., 2007, Iterative learning control applied to batch processes: An overview. Control Engineering Practice, 15, 1306-1318.
  6. Ljung, L., 1999, System Identification: Theory for the User. Prentice Hall.
  7. Padieu, F., and Su, R., 1990, H 8 approach to learning control systems, Int. J. Adaptive Contr. Signal Processing, 4, 465-474.
  8. Tayabi, A, and Islam, S., 2006, Adaptive iterative learning control for robot manipulators: Experimental results. Control Engineering Practice, 14, 843-851.
  9. Tsai, M. S., Lin, M. T., and Yau, H. T., 2006, Development of command-based iterative learning control algorithm with consideration of friction, disturbance, and noise effects. IEEE Trans. Control Syst. Technol., 14, 511-518.
  10. VenturCom Inc., 2006, VenturCom RTX 6.5 SDK Documentation. Cambridge.
  11. Wang, H., and Afshar, P., 2009, ILC-Based FixedStructure Controller Design for Output PDF Shaping in Stochastic Systems Using LMI Techniques. IEEE Trans. on Automatic control, 54, 760-773.
  12. Ye, Y. Q., and Wang, D. W., 2005, Clean system inversion learning control law. Automatica, 41, 1549- 1556.
  13. Zhou, K., Doyle, J. C., and Glover, K., 1996, Robust and Optimal Control. New Jersey, Prentice Hall.
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Paper Citation


in Harvard Style

Tsai M., Yen C. and Yau H. (2012). Development of Robust Learning Control and Application to Motion Control . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-8565-21-1, pages 148-152. DOI: 10.5220/0004008601480152


in Bibtex Style

@conference{icinco12,
author={Meng-Shiun Tsai and Chung-Liang Yen and Hong-Tzong Yau},
title={Development of Robust Learning Control and Application to Motion Control},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2012},
pages={148-152},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004008601480152},
isbn={978-989-8565-21-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Development of Robust Learning Control and Application to Motion Control
SN - 978-989-8565-21-1
AU - Tsai M.
AU - Yen C.
AU - Yau H.
PY - 2012
SP - 148
EP - 152
DO - 10.5220/0004008601480152