CEAS EuroGNC 2026
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A Genetic Algorithm-Based Neuro-Fuzzy Adaptive Computed-Torque Controller for Lower-Limb Rehabilitation Exoskeletons
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| Muhammad Adel Yusuf |
Ph.D. Student, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia. | | Ali Nasir |
Assistant Professor, King Fahd University of Petroleum and Minerals (KFUPM); Interdisciplinary Research Center for Intelligent Manufacturing and Robotics, Dhahran, Saudi Arabia. | | Sami El-Ferik |
Professor, King Fahd University of Petroleum and Minerals (KFUPM); Interdisciplinary Research Center for Smart Mobility and Logistics, Dhahran, Saudi Arabia. |
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| Abstract:
Due to the growing aging society and the increasing number of people who suffer from lower limb disorders worldwide, the need for robot-assisted gait training devices has become increasingly urgent. These systems are essential for supporting clinicians in rehabilitation and enhancing functional recovery in both upper and lower extremities. However, the significant variability in users' physical characteristics—such as body mass, limb length, and inertia—introduces dynamic uncertainties that challenge conventional control strategies. To address this, we propose a User-Adaptive Genetic Algorithm-Tuned Neuro-Fuzzy (GA-Tuned Neuro-Fuzzy) controller integrated within a Computed Torque Control (CTC) framework. The proposed approach leverages the learning capability of an Adaptive Neuro-Fuzzy Inference System (ANFIS) and the optimization ability of a Genetic Algorithm (GA) to adaptively tune control parameters based on varying anthropometric profiles. Simulation results demonstrate that the controller achieves accurate trajectory tracking, low steady-state error, and robust performance across a wide range of user conditions and reference inputs. These findings validate the effectiveness of the proposed controller for personalized and adaptive rehabilitation in lower limb exoskeleton applications.
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| Keywords: Rehabilitation; Exoskeleton; Computed Torque Control; ANFIS; Adaptive control; Genetic ALgorithm |
 View PDF CEAS-GNC-2026-005 doi: 10.82124/CEAS-GNC-2026-005 |
| Muhammad Adel Yusuf, Ali Nasir, Sami El-Ferik: A Genetic Algorithm-Based Neuro-Fuzzy Adaptive Computed-Torque Controller for Lower-Limb Rehabilitation Exoskeletons. Proceedings of the 2026 CEAS EuroGNC conference. Madrid, Spain. May 2026. doi: 10.82124/CEAS-GNC-2026-005.
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| BibTeX entry (UTF-8):
@Incollection{CEAS-GNC-2026-005,
author = {Adel Yusuf, Muhammad and Nasir, Ali and El-Ferik, Sami},
title = {A Genetic Algorithm-Based Neuro-Fuzzy Adaptive Computed-Torque Controller for Lower-Limb Rehabilitation Exoskeletons},
booktitle = {Proceedings of the 2026 {CEAS EuroGNC} conference},
address = {Madrid, Spain},
month = may,
year = {2026},
doi = {10.82124/CEAS-GNC-2026-005}
}
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