Rastegar Mojdeh, Kobravi Hamid Reza
Department of Biomedical Engineering, Research Center of Biomedical Engineering, Islamic Azad University of Mashhad, Mashhad, Iran.
Basic Clin Neurosci. 2021 Jul-Aug;12(4):441-452. doi: 10.32598/bcn.2021.173.3. Epub 2021 Jul 1.
Utilizing Functional Electrical Stimulation (FES) and rehabilitation robots for motion control is an open research problem. In this paper, a new control algorithm has been proposed which was de-signed based on a combination of FES and an active mechanical actuator to control the knee joint movement.
An adaptive controller and a Proportional-Derivative (PD) controller have adjusted the motor torque and stimulation intensity, respectively. The FES controller was activated whenever a disturbance observer detected the presence of the external disturbance. In this manner, the occurrence of the muscle fatigue arises from the FES can be postponed.
The simulation studies were carried out on a model of muscle-joint system along with a model of a servo-motor. The computed RMS of the tracking errors compared to the range of knee motion show that the tracking performance is acceptable. In this research, the trajectories envisioned as the knee joint reference trajectory were designed using the recorded human data.
The achieved results prove the ability of the proposed control strategy to not only reject the external disturbance but also compensate the muscle fatigue.
利用功能性电刺激(FES)和康复机器人进行运动控制是一个开放的研究问题。本文提出了一种新的控制算法,该算法基于FES和主动机械致动器的组合设计,用于控制膝关节运动。
自适应控制器和比例 - 微分(PD)控制器分别调整电机扭矩和刺激强度。每当干扰观测器检测到外部干扰时,FES控制器就会被激活。通过这种方式,可以推迟由FES引起的肌肉疲劳的发生。
在肌肉 - 关节系统模型以及伺服电机模型上进行了仿真研究。与膝关节运动范围相比,计算出的跟踪误差均方根表明跟踪性能是可接受的。在本研究中,使用记录的人体数据设计了设想为膝关节参考轨迹的轨迹。
所取得的结果证明了所提出的控制策略不仅能够抵抗外部干扰,还能够补偿肌肉疲劳的能力。