“Discrete Learning Control with Application to Hydraulic Actuators”

Authors: Torben Ole Andersen, Henrik C. Pedersen and Michael R. Hansen,
Affiliation: Aalborg University and University of Agder
Reference: 2015, Vol 36, No 4, pp. 215-224.

Keywords: Discrete learning control, Hydraulic actuators

Abstract: In this paper the robustness of a class of learning control algorithms to state disturbances, output noise, and errors in initial conditions is studied. We present a simple learning algorithm and exhibit, via a concise proof, bounds on the asymptotic trajectory errors for the learned input and the corresponding state and output trajectories. Furthermore, these bounds are continuous functions of the bounds on the initial condition errors, state disturbance, and output noise, and the bounds are zero in the absence of these disturbances.

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DOI forward links to this article:
[1] Xuerong Li, Shaoping Bai and Ole Madsen (2019), doi:10.1016/j.rcim.2019.04.009
References:
[1] Ahn, H.-S., Chen, Y.Q., and Moore, K. (2007). Iterative learning control: Brief survey and categorization, Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on. 37(6):1099--1121. doi:10.1109/TSMCC.2007.905759
[2] Arimoto, S. (1990). Learning control theory for robotic motion, International Journal of Adaptive Control and Signal Processing. 4(6):543--564. doi:10.1002/acs.4480040610
[3] Arimoto, S., Kawamura, S., and Miyazaki, F. (1984). Bettering operation of dynamic systems by learning: A new control theory for servomechanism or mechatronics systems, In Decision and Control. The 23rd IEEE Conference on. pages 1064--1069. doi:10.1109/CDC.1984.272176
[4] Arimoto, S., Naniwa, T., and Suzuki, H. (1990). Robustness of p-type learning control with a forgetting factor for robotic motions, In Decision and Control., Proceedings of the 29th IEEE Conference on. pages 2640--2645 vol.5. doi:10.1109/CDC.1990.203457
[5] Arimoto, S., Naniwa, T., and Suzuki, H. (1991). Selective learning with a forgetting factor for robotic motion control, In Robotics and Automation. Proceedings., 1991 IEEE International Conference on. pages 728--733 vol.1. doi:10.1109/ROBOT.1991.131671
[6] Atkeson, C. and McIntyre, J. (1986). Robot trajectory learning through practice, In Robotics and Automation. Proceedings. 1986 IEEE International Conference on, volume3. pages 1737--1742. doi:10.1109/ROBOT.1986.1087423
[7] Bondi, P., Casalino, G., and Gambardella, L. (1988). On the iterative learning control theory for robotic manipulators, Robotics and Automation, IEEE Journal of. 4(1):14--22. doi:10.1109/56.767
[8] Bristow, D., Tharayil, M., and Alleyne, A. (2006). A survey of iterative learning control, Control Systems, IEEE. 26(3):96--114. doi:10.1109/MCS.2006.1636313
[9] Craig, J.J. (1984). Adaptive control of manipulators through repeated trials, In Proc. of the American Control Conference, San Diego, volume3. pages 1566--1573.
[10] Hauser, J. (1987). Learning control for a class of nonlinear systems, In Decision and Control. 26th IEEE Conference on, volume26. pages 859--860. doi:10.1109/CDC.1987.272514
[11] Heinzinger, G., Fenwick, D., Paden, B., and Miyazaki, F. (1989). Robust learning control, In Proc. of 28th Conf. on Decision and Control. Tampa, Florida, pages 2632--2634. http://www.eecs.berkeley.edu/Pubs/TechRpts/1989/1338.html.
[12] Heinzinger, G., Fenwick, D., Paden, B., and Miyazaki, F. (1992). Stability of learning control with disturbances and uncertain initial conditions, Automatic Control, IEEE Transactions on. 37(1):110--114. doi:10.1109/9.109644
[13] Kavli, T. (1992). Frequency domain synthesis of trajectory learning controllers for robot manipulators, Journal of Robotic Systems. 9(5):663--680. doi:10.1002/rob.4620090506
[14] Mita, T. and Kato, E. (1985). Iterative control and its application to motion control of robot arm - a direct approach to servo-problems, In Decision and Control, 1985 24th IEEE Conference on. pages 1393--1398. doi:10.1109/CDC.1985.268740
[15] Saab, S., Vogt, W.G., and Mickle, M. (1993). Theory of p-type learning control with implication for the robot manipulator, In Robotics and Automation. Proceedings., 1993 IEEE International Conference on. pages 665--671 vol.1. doi:10.1109/ROBOT.1993.292055
[16] Togai, M. and Yamano, O. (1985). Analysis and design of an optimal learning control scheme for industrial robots: A discrete system approach, In Decision and Control, 1985 24th IEEE Conference on. pages 1399--1404. doi:10.1109/CDC.1985.268741
[17] Tso, S.K. and Ma, L. Y.X. (1993). Discrete learning control for robots: strategy, convergence and robustness, International Journal of Control. 57(2):273--291. doi:10.1080/00207179308934388
[18] Wang, Y., Gao, F., and III, F. J.D. (2009). Survey on iterative learning control, repetitive control, and run-to-run control, Journal of Process Control. 19(10):1589 -- 1600. doi:10.1016/j.jprocont.2009.09.006
[19] Xu, J.-X. (2011). A survey on iterative learning control for nonlinear systems, International Journal of Control. 84(7):1275--1294. doi:10.1080/00207179.2011.574236


BibTeX:
@article{MIC-2015-4-2,
  title={{Discrete Learning Control with Application to Hydraulic Actuators}},
  author={Andersen, Torben Ole and Pedersen, Henrik C. and Hansen, Michael R.},
  journal={Modeling, Identification and Control},
  volume={36},
  number={4},
  pages={215--224},
  year={2015},
  doi={10.4173/mic.2015.4.2},
  publisher={Norwegian Society of Automatic Control}
};