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An Incremental Learning-based Fuzzy Control Scheme for a Class of Uncertain Euler-Lagrange Systems | ||
| Iranian Journal of Fuzzy Systems | ||
| دوره 22، شماره 2، خرداد و تیر 2025، صفحه 147-170 اصل مقاله (1.93 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22111/ijfs.2025.48879.8616 | ||
| نویسندگان | ||
| Amir Arsalan Haghrah1؛ Sehraneh Ghaemi* 2؛ Mohammad Ali Badamchizadeh1 | ||
| 1Faculty of Electrical and Computer Engineering, University of Tabriz | ||
| 2Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran | ||
| چکیده | ||
| Euler-Lagrange systems describe a wide range of mechanical and robotic systems. Uncertainties and dynamic parameter changes pose significant challenges to control the Euler-Lagrange systems using traditional methods. In such cases, intelligent methods can cover the limits of the classical techniques. In this research, we intend to present a fuzzy 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 have performed several simulations to test the capabilities of the proposed method and compared the results with wellknown machine learning-based methods using various criteria. Considering the integral of absolute error, the results show that the proposed method has improved by 40.89%, 38.32%, 34.12%, and 34.79% compared to the best other method in nominal system scenario and three other scenarios considering three different levels of uncertainty. The overshoot of the system response achieved by the proposed control scheme is approximately 44 − 48% less than the best other method in four scenarios. Also, we have studied the system response to disturbance and noise. | ||
| کلیدواژهها | ||
| Fuzzy Systems؛ Artificial Intelligence؛ Incremental Learning؛ Euler-Lagrange Systems | ||
| مراجع | ||
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