Robust Adaptive Control for Robot Manipulators Trajectory Tracking Based on Iterative Learning Observer with Time-delay

Authors

  • Fu Xingjian School of Automation, Beijing Information Science and Technology University
  • He Jiahui School of Automation, Beijing Information Science and Technology University

DOI:

https://doi.org/10.7546/CRABS.2022.06.10

Keywords:

iterative learning, observer, robust adaptive control, robot manipulators

Abstract

For the trajectory tracking of the robot manipulators, the robust adaptive control based on iterative learning observer is designed. The robot manipulators model is given, and an iterable dynamic equation is obtained by linearizing the model. An iterative learning observer is designed, so that the output state of the observer can converge to the actual state of the system and the convergence analysis of the observer is also given. Based on Lyapunov stability theory, the robust adaptive controller is given to ensure that the trajectory tracking error of the robot manipulators gradually approaches zero. Finally, the double joint robot manipulators systems are simulated, and the results verify the effectiveness of the method. 

Author Biographies

Fu Xingjian, School of Automation, Beijing Information Science and Technology University

Mailing Address:
School of Automation,
Beijing Information Science and Technology University
No. 12 Xiaoying East Road
Qinghe, Haidian District
Beijing, 100192, China

E-mail: fxj@bistu.edu.cn

He Jiahui, School of Automation, Beijing Information Science and Technology University

Mailing Address:
School of Automation,
Beijing Information Science and Technology University
No. 12 Xiaoying East Road
Qinghe, Haidian District
Beijing, 100192, China

E-mail: 647811515@qq.com

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Published

30-06-2022

How to Cite

[1]
X. Fu and J. He, “Robust Adaptive Control for Robot Manipulators Trajectory Tracking Based on Iterative Learning Observer with Time-delay”, C. R. Acad. Bulg. Sci. , vol. 75, no. 6, pp. 861–872, Jun. 2022.

Issue

Section

Engineering Sciences