An Incremental Learning-based Fuzzy Control Scheme for a Class of Uncertain Euler-Lagrange Systems
نویسندگان
1 Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
2 Faculty of Electrical and Computer Engineering, University of Tabriz
3 Faculty of Electrical and Computer Engineering, University of Tabriz
doi
10.22111/ijfs.2025.48879.8616چکیده
Euler-Lagrange systems describe a wide range of mechanical and robotic systems. Uncertainties and dynamic parameterchanges pose significant challenges to control the Euler-Lagrange systems using traditional methods. In suchcases, intelligent methods can cover the limits of the classical techniques. In this research, we intend to present afuzzy logic-based controller trained by the proposed incremental learning algorithm to face the challenges of Euler-Lagrange systems. Incremental learning aims to accumulate experiences over time to train the models. We haveperformed several simulations to test the capabilities of the proposed method and compared the results with wellknownmachine learning-based methods using various criteria. Considering the integral of absolute error, the resultsshow that the proposed method has improved by 40.89%, 38.32%, 34.12%, and 34.79% compared to the best othermethod in nominal system scenario and three other scenarios considering three different levels of uncertainty. Theovershoot of the system response achieved by the proposed control scheme is approximately 44 − 48% less than thebest other method in four scenarios. Also, we have studied the system response to disturbance and noise.
