ArticlePeerJ. Computer science2021
Robust adaptive PD-like control of lower limb rehabilitation robot based on human movement data.
Article in PeerJ. Computer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A humanoid control strategy based on deep reinforcement learning for enhanced comfort in lower limb rehabilitation robots.Scientific reports · 2026Article
- Article
- Musculoskeletal modeling and humanoid control of robots based on human gait data.PeerJ. Computer science · 2021Article
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Authors and funding
3 authors.
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Abstract
The combination of biomedical engineering and robotics engineering brings hope of rehabilitation to patients with lower limb movement disorders caused by diseases of the central nervous system. For the comfort during passive training, anti-interference and the convergence speed of tracking the desired trajectory, this paper analyzes human body movement mechanism and proposes a robust adaptive PD-like control of the lower limb exoskeleton robot based on healthy human gait data. In the case of bounded error perturbation, MATLAB simulation verifies that the proposed method can ensure the global stability by introducing an S-curve function to make the design robust adaptive PD-like control. This control strategy allows the lower limb rehabilitation robot to track the human gait trajectory obtained through the motion capture system more quickly, and avoids excessive initial output torque. Finally, the angle similarity function is used to objectively evaluate the human body for wearing the robot comfortably.
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Registered trials
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