An Adaptive Iterative Learning Control for Robot Manipulator in Task Space

Authors

  • ThanhQuyen Ngo HCM City University of Industry College of Electrical Engineering HCM City, Vietnam
  • M. Hung Nguyen HCM City University of Industry College of Electrical Engineering HCM City, Vietnam
  • YaoNan Wang Hunan University College of Electrical and Information Engineering Changsha, Hunan Province 410082, P.R.China
  • Ji Ge Hunan University College of Electrical and Information Engineering Changsha, Hunan Province 410082, P.R.China
  • ShuNing Wei Hunan University College of Electrical and Information Engineering Changsha, Hunan Province 410082, P.R.China
  • T. Long Mai HCM City University of Industry College of Electronic Engineering HCM City, Vietnam

Keywords:

PD Control, Learning control, robot manipulator

Abstract

In this paper, adaptive iterative learning control (AILC) of uncertain robot manipulators in task space is considered for trajectory tracking in an iterative operation mode. The control scheme incluces a PD controller with a gain switching technique plus a learning feedforward term, is exploited to predict the desired actuator torque. By using Lyapunov method, an adaptive iterative learning control scheme is presented for robotic system with both structured and unstructured uncertainty, and the overall stability of the closed-loop system in the iterative domain is established. The validity of the scheme is confirmed through a numerical simulation.

References

P. Bondi, G. Cacaline and L. Gambardella, On the iterative learning Control theory for robot manipulators, IEEE J. On Robotics and Automation, 4:14-22, 1984. http://dx.doi.org/10.1109/56.767

S. Arimoto, S. Kawamura and F. Miyazaki, Bettering operation of dynamic system by learning: A new control theory for servomechanism or mechatronics systems, Proceedings of 23rd. CDC, 1064- 1069, 1984.

J.J. Craig, Adaptive control of mechanical manipulators, Addison-Wesley, New York, 1988.

Hyo-Sung Ahn, YangQuan Chen, Kevin L. Moore, Iterative learning control: Brief Survey and Categorization, IEEE Trans. Ind. Sys, 6:1099-1121, 2007.

Dong-II Kim, Sungkwun Kim An iterative learning control method with application for CNC machine tools, IEEE Trans. Ind. App, 32(1):66-72, 1996. http://dx.doi.org/10.1109/28.485814

K.L. Moore, Iterative learning control for deterministic systems,Advances Industrial Control, New York, Springer-Verlag, 1993. http://dx.doi.org/10.1007/978-1-4471-1912-8

Tayebi A, Adaptive iterative learning control for robot manipulators, Automatica, 40:1195-1203, 2004. http://dx.doi.org/10.1016/j.automatica.2004.01.026

Ouyang P R, Zhang W J, Gupta M M, An adaptive switching learning control method for trajectory tracking of robot manipulators, it Mechatronics, 16:51-61, 2006. http://dx.doi.org/10.1016/j.mechatronics.2005.08.002

Choi JY, Lee JS, Adaptive iterative learning control of uncertain robotic systems,IEE Proc Contr Theory, 147(4):217-223, 2000.

B.S. Chen, H.J. Uang, and C.S. Tseng, Robust tracking enhancement of robot systems including motor dynamics: A fuzzy-based dynamic game approach,IEEE Trans. Fuzzy syst, 11(4):538- 552,1998. http://dx.doi.org/10.1109/91.728449

Craig JJ. Introduction to robotics: mechanics and control. Reading, MA: Addison-Wesley, 1986.

T.Y Kuc, K. Nam, J.S. Lee, An iterative learning control of robot Manipulators, IEEE Trans Robot Automat., 7(6): 835-842, 1991. http://dx.doi.org/10.1109/70.105392

S.S. Ge, C.C. Hang, Adaptive neural network control of robot manipulators in task space,IEEE Trans. Ind. Elec., 44(6):746-752, 1997. http://dx.doi.org/10.1109/41.649934

Published

2014-09-18

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.