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Title: Optimal Energy Shaping Control for a Backdrivable Hip Exoskeleton
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.  more » « less
Award ID(s):
1949869
NSF-PAR ID:
10401872
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Proceedings of the American Control Conference
ISSN:
0743-1619
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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