Authors

Jiefu Zhang, Jianping Lin, Vamsi Peddinti, Robert D. Gregg

Abstract

Task-dependent controllers widely used in exoskeletons track predefined trajectories, which overly constrain the volitional motion of individuals with remnant voluntary mobility. Energy shaping, on the other hand, provides task-invariant assistance by altering the human body’s dynamic characteristics in the closed loop. While human-exoskeleton systems are often modeled using Euler-Lagrange equations, in our previous work we modeled the system as a port-controlled-Hamiltonian system, and a task-invariant controller was designed for a knee-ankle exoskeleton using interconnection-damping assignment passivity-based control. In this paper, we extend this framework to design a controller for a backdrivable hip exoskeleton to assist multiple tasks. A set of basis functions that contains information of kinematics is selected and corresponding coefficients are optimized, which allows the controller to provide torque that fits normative human torque for different activities of daily life. Human-subject experiments with two able-bodied subjects demonstrated the controller’s capability to reduce muscle effort across different tasks.

Citation

BibTeX

@inproceedings{Zhang_2023,
  title={{Optimal Energy Shaping Control for a Backdrivable Hip Exoskeleton}},
  DOI={10.23919/acc55779.2023.10155839},
  booktitle={{2023 American Control Conference (ACC)}},
  publisher={IEEE},
  author={Zhang, Jiefu and Lin, Jianping and Peddinti, Vamsi and Gregg, Robert D.},
  year={2023},
  pages={2065--2070}
}

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References