Hu Kexin, Ma Zhongjing, Zou Suli, Li Jian, Ding Haoran
School of Automation, Beijing Institute of Technology, Beijing, China.
University College London, London, UK.
Cyborg Bionic Syst. 2024 Jun 1;5:0099. doi: 10.34133/cbsystems.0099. eCollection 2024.
Rehabilitation robots can reproduce the rehabilitation movements of therapists by designed rehabilitation robot control methods to achieve the goal of training the patients' motion abilities. This paper proposes an impedance sliding-mode control method based on stiffness-scheduled law for the rehabilitation robot, which can be applied to rehabilitation training with both active and passive modes. A free-model-based sliding-mode control strategy is developed to avoid model dependence and reduce the system uncertainty caused by limb shaking. Additionally, the stiffness scheduling rule automatically regulates the impedance parameter of the rehabilitation robot based on the force exerted by the patient on the robot such that the rehabilitation training caters to the patient's health condition. The proposed method is compared with the fixed stiffness and variable stiffness impedance methods, and the superiority of the proposed method is proved. Rehabilitation training experiments on an actual rehabilitation robot are provided to demonstrate the feasibility and stability of the proposed method.
康复机器人可以通过设计的康复机器人控制方法来重现治疗师的康复动作,以实现训练患者运动能力的目标。本文提出了一种基于刚度调度律的康复机器人阻抗滑模控制方法,该方法可应用于主动和被动两种模式的康复训练。开发了一种基于自由模型的滑模控制策略,以避免模型依赖并减少肢体抖动引起的系统不确定性。此外,刚度调度规则根据患者施加在机器人上的力自动调节康复机器人的阻抗参数,使康复训练能够适应患者的健康状况。将所提出的方法与固定刚度和可变刚度阻抗方法进行了比较,证明了所提方法的优越性。提供了在实际康复机器人上进行的康复训练实验,以验证所提方法的可行性和稳定性。