Luo Shengguo, Li Xiangyun, Lu Qi, Chen Peng, Li Kang
College of Electrical Engineering, Sichuan University, Chengdu 610065, P. R. China.
West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, P. R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2025 Apr 25;42(2):318-325. doi: 10.7507/1001-5515.202501049.
To solve the safety problems caused by the restriction of interaction space and the singular configuration of rehabilitation robot in terminal traction upper limb rehabilitation training, a trajectory planning and tracking control scheme for rehabilitation training is proposed. The human-robot safe interaction space was obtained based on kinematics modeling and rehabilitation theory, and the training trajectory was planned based on the occupational therapy in rehabilitation medicine. The singular configuration of the rehabilitation robot in the interaction space was avoided by exponential adaptive damped least square method. Then, a nonlinear controller for the upper limb rehabilitation robot was designed based on the backstepping control method. Radial basis function neural network was used to approximate the robot model information online to achieve model-free control. The stability of the controller was proved by Lyapunov stability theory. Experimental results demonstrate the effectiveness and superiority of the proposed singular avoidance control scheme.
为解决上肢康复训练中因康复机器人在终端牵引时交互空间受限和奇异构型所引起的安全问题，提出了一种康复训练轨迹规划与跟踪控制方案。基于运动学建模和康复理论获得人机安全交互空间，并依据康复医学中的作业疗法规划训练轨迹。采用指数自适应阻尼最小二乘法避免康复机器人在交互空间中的奇异构型。然后，基于反步控制方法设计了上肢康复机器人的非线性控制器。利用径向基函数神经网络在线逼近机器人模型信息以实现无模型控制。通过李雅普诺夫稳定性理论证明了控制器的稳定性。实验结果验证了所提奇异避免控制方案的有效性和优越性。
