Comparative and Analysis of Adaptive Robust Controller and Intelligent Adaptive Iterative Learning Controller Uncertainty Compensation for Industrial Robot

Comparative and Analysis of Adaptive Robust Controller and Intelligent Adaptive Iterative Learning Controller Uncertainty Compensation for Industrial Robot
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© 2025 by IJETT Journal
Volume-73 Issue-8
Year of Publication : 2025
Author : Vo Thu Ha, Bui Thi Hong Diem, Than Thi Thuong, Tran The Anh, Trieu Tuan Anh
DOI : 10.14445/22315381/IJETT-V73I8P125

How to Cite?
Vo Thu Ha, Bui Thi Hong Diem, Than Thi Thuong, Tran The Anh, Trieu Tuan Anh,"Comparative and Analysis of Adaptive Robust Controller and Intelligent Adaptive Iterative Learning Controller Uncertainty Compensation for Industrial Robot", International Journal of Engineering Trends and Technology, vol. 73, no. 8, pp.292-302, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I8P125

Abstract
The robot system's parameters fluctuate unpredictably or cannot be precisely determined and are further influenced by external disturbances during movement. Various adaptive, robust, and adaptive-robust control methods exist for robot motion control, all requiring an uncertain mathematical model, parameter estimation, or the assumption of constant uncertainty. However, an alternative approach—iterative learning control—does not rely on a mathematical model or assume parameter constancy. Instead, it determines learning function parameters online using an optimization method based on minimizing the sum of squared errors. This article explores and compares control performance for a 2-degree-of-freedom robot, highlighting the effectiveness of the adaptive-robust controller versus the conventional learning controller.

Keywords
Adaptive-Robust Control, Interactive Learning Control (ILC), Taylor series estimation./p>

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