Extended state observer based adaptive iterative trajectory tracking control of a two-jointed robotic arm

Xin  Zhang; Wentao  Lu

doi:10.6180/jase.202506_28(6).0004

Extended state observer based adaptive iterative trajectory tracking control of a two-jointed robotic arm

Electrical Engineering

Xin ZhangThis email address is being protected from spambots. You need JavaScript enabled to view it. and Wentao Lu

School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China

Received: April 2, 2024
Accepted: June 30, 2024
Publication Date: August 3, 2024

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202506_28(6).0004

In order to minimize the effects of inner ambiguity and outer disturbance of the robotic arm model on the controlled system and to enhance the iterative performance, the paper designs an adaptive iterative control (AILC) method with forgetting factor based on the compensation of extended state observer (ESO). This iterative algorithm for controlling the torque is designed by establishing a dynamic model of a two-jointed robotic arm, and proof of the stability and convergence of the system is given theoretically by using the composite energy function based on Lyapunov function, and the efficacy of the algorithm in this paper is demonstrated by simulations and comparison.

Keywords: Forgetting factor; Lyapunov function; Linear Extended State Observer; Stability analysis

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