An Adaptive Iterative Learning Control for Robot Manipulator in Task Space

  • 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

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.

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Published
2014-09-18
How to Cite
NGO, ThanhQuyen et al. An Adaptive Iterative Learning Control for Robot Manipulator in Task Space. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 7, n. 3, p. 518-529, sep. 2014. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/1392>. Date accessed: 05 july 2020. doi: https://doi.org/10.15837/ijccc.2012.3.1392.

Keywords

PD Control; Learning control; robot manipulator