Brahmi Brahim, Dahani Hicham, Bououden Soraya, Fareh Raouf, Rahman Mohamed Habibur
Electrical Engineering Department, College Ahuntsic, Montreal, QC H2M 1Y8, Canada.
Electrical Engineering Department, Ferhat Abas Setif 1 University, Setif 19137, Algeria.
Sensors (Basel). 2024 Jan 12;24(2):489. doi: 10.3390/s24020489.
Rehabilitation robotics has seen growing popularity in recent years due to its immense potential for improving the lives of people with disabilities. However, the complex, uncertain dynamics of these systems present significant control challenges, requiring advanced techniques. This paper introduces a novel adaptive control framework integrating modified function approximation (MFAT) and double-integral non-singular terminal sliding mode control (DINTSMC). The goal is to achieve precise tracking performance, high robustness, a fast response, a finite convergence time, reduced chattering, and effective handling of unknown system dynamics. A key feature is the incorporation of a higher-order sliding mode observer, eliminating the need for velocity feedback. This provides a new solution for overcoming the inherent variations and uncertainties in robot manipulators, enabling improved accuracy within fixed convergence times. The efficacy of the proposed approach was validated through simulations and experiments on an exoskeleton robot. The results successfully demonstrated the controller's effectiveness. Stability analysis using Lyapunov theory proved the closed-loop system's uniform ultimate boundedness. This contribution is expected to enable enhanced control for rehabilitation robots and improved patient outcomes.
近年来，康复机器人技术因其在改善残疾人生活方面的巨大潜力而越来越受欢迎。然而，这些系统复杂、不确定的动态特性带来了重大的控制挑战，需要先进的技术。本文介绍了一种新颖的自适应控制框架，该框架集成了改进函数逼近（MFAT）和双积分非奇异终端滑模控制（DINTSMC）。目标是实现精确的跟踪性能、高鲁棒性、快速响应、有限收敛时间、减少抖振以及有效处理未知系统动态特性。一个关键特性是引入了高阶滑模观测器，无需速度反馈。这为克服机器人操纵器固有的变化和不确定性提供了一种新的解决方案，能够在固定收敛时间内提高精度。通过在外骨骼机器人上进行的仿真和实验验证了所提方法的有效性。结果成功证明了控制器的有效性。使用李雅普诺夫理论进行的稳定性分析证明了闭环系统的一致最终有界性。这一贡献有望实现对康复机器人的增强控制并改善患者治疗效果。
