Model predictive control for upper limb rehabilitation robotic system under disturbed condition

S. F. Ahmed, Athar Ali, Syed Yarooq Raza, K. Kadir, M. K. Joyo, K. Naidu
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引用次数: 4

Abstract

Demands for rehabilitation robots are now increasing day by day due to increase in the number of patients with neural disorder. These robots help the patients in therapeutic exercise performing specific movements which leads to mitigating neural disorders through a gradual improvement of the patients’ limb performances. As robots are the best suitable options to perform repetitive tasks without the risks of monotony and fatigue failure, rehabilitation via robots have proven to be more of a comfortable exercise than an exhausting treatment procedure. Rehabilitation robots require precise and efficient control in terms of position and force, ensuring thus accuracy in exercise movements. Nonlinear controllers make good option to this end as they adapt to handle the system uncertainties. This paper presents a Model Predictive Control (MPC) to control the rehabilitation robot for upper limb extremity under various disturbed conditions. From the results MPC proves to be robust controller under the action of applied external disturbances.Demands for rehabilitation robots are now increasing day by day due to increase in the number of patients with neural disorder. These robots help the patients in therapeutic exercise performing specific movements which leads to mitigating neural disorders through a gradual improvement of the patients’ limb performances. As robots are the best suitable options to perform repetitive tasks without the risks of monotony and fatigue failure, rehabilitation via robots have proven to be more of a comfortable exercise than an exhausting treatment procedure. Rehabilitation robots require precise and efficient control in terms of position and force, ensuring thus accuracy in exercise movements. Nonlinear controllers make good option to this end as they adapt to handle the system uncertainties. This paper presents a Model Predictive Control (MPC) to control the rehabilitation robot for upper limb extremity under various disturbed conditions. From the results MPC proves to be robust controller under the action of app...
扰动条件下上肢康复机器人系统的模型预测控制
由于神经系统疾病患者数量的增加,对康复机器人的需求日益增加。这些机器人帮助患者在治疗运动中进行特定的运动,通过逐渐改善患者的肢体表现来减轻神经障碍。由于机器人是执行重复性任务的最佳选择,没有单调和疲劳失败的风险,通过机器人进行康复已被证明是一种更舒适的锻炼,而不是令人筋疲力尽的治疗过程。康复机器人需要在位置和力度方面进行精确有效的控制,从而确保运动动作的准确性。非线性控制器可以很好地适应系统的不确定性。提出了一种基于模型预测控制的上肢康复机器人在各种干扰条件下的控制方法。结果表明,MPC控制器在外界扰动作用下具有鲁棒性。由于神经系统疾病患者数量的增加,对康复机器人的需求日益增加。这些机器人帮助患者在治疗运动中进行特定的运动,通过逐渐改善患者的肢体表现来减轻神经障碍。由于机器人是执行重复性任务的最佳选择,没有单调和疲劳失败的风险,通过机器人进行康复已被证明是一种更舒适的锻炼,而不是令人筋疲力尽的治疗过程。康复机器人需要在位置和力度方面进行精确有效的控制,从而确保运动动作的准确性。非线性控制器可以很好地适应系统的不确定性。提出了一种基于模型预测控制的上肢康复机器人在各种干扰条件下的控制方法。结果表明,MPC在应用程序的作用下是鲁棒控制器。
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