• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2022, Vol. 58 ›› Issue (7): 32-43.doi: 10.3901/JME.2022.07.032

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Human-machine Coupling Dynamics Modeling and Active Compliance Control of Lower Limb Rehabilitation Robot

LU Hao1,2,3,4, WANG Hongbo1,2,4, FENG Yongfei5   

  1. 1. Academy for Engineering & Technology, Fudan University, Shanghai 200433;2. Shanghai Clinical Research Center for Aging and Medicine, Shanghai 200040;3. Institute of AI and Robotics, Fudan University, Shanghai 200433;4. Shanghai Engineering Research Center of AI & Robotics, Shanghai 200433;5. Faculty of Mechanical Engineering & Mechanics, Ningbo University, Ningbo 315211
  • Received:2021-08-04 Revised:2021-11-05 Online:2022-04-05 Published:2022-05-20

Abstract: Aiming at the problem that the nonlinear human-computer interaction force of lower limb rehabilitation robot affects the comfort and safety of training process, a human-computer coupling dynamic modeling method and a dynamic feedforward control strategy are proposed. Combined with the characteristics of early rehabilitation training of stroke and the requirements of reducing hip output power, the degree of freedom configuration, self-balancing structure principle and specific model design scheme are determined. Based on the simplified human muscle bone model and considering the man-machine coupling mode, the man-machine interaction force model is determined, and the man-machine coupling dynamic model considering the influence of self-balancing structure is further given. The environmental stiffness is introduced to simulate the contact force effect of different soft and hard roads, the dynamic feedforward is used to carry out the feedforward compensation control of joint expected torque, and the stability of the control system is determined by Lyapunov method. The accuracy of trajectory tracking and force tracking were verified by experiments. Further, through clinical trials, 92.2% of stroke patients are relieved, which verifies the feasibility and safety of this research.

Key words: lower limb rehabilitation robot, human-machine coupling dynamics, compliance control, clinical trial

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