Extremum Seeking Control for Stiffness Auto-Tuning of a Quasi-Passive Ankle Exoskeleton

Recently, it has been shown that light-weight, passive, ankle exoskeletons with spring-based energy store-and-release mechanisms can reduce the muscular effort of human walking. The stiffness of the spring in such a device must be properly tuned in order to minimize the muscular effort. However, thi...

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Vydáno v:IEEE robotics and automation letters Ročník 5; číslo 3; s. 4604 - 4611
Hlavní autoři: Kumar, Saurav, Zwall, Matthew Richard, Bolivar-Nieto, Edgar A., Gregg, Robert D., Gans, Nicholas
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.07.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Ankle
Electromyography
Exoskeletons
Legged locomotion
Locomotion
Muscles
Optimization
prosthetics and exoskeletons
Real-time systems
Robust/adaptive control of robotic systems
Self tuning
Sensors
Springs
Stiffness
Walking
wearable robots
Weight reduction
ISSN:2377-3766, 2377-3766
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Shrnutí:Recently, it has been shown that light-weight, passive, ankle exoskeletons with spring-based energy store-and-release mechanisms can reduce the muscular effort of human walking. The stiffness of the spring in such a device must be properly tuned in order to minimize the muscular effort. However, this muscular effort changes for different locomotion conditions (e.g., walking speed), causing the optimal spring stiffness to vary as well. Existing passive exoskeletons have a fixed stiffness during operation, preventing it from responding to changes in walking conditions. Thus, there is a need of a device and auto-tuning algorithm that minimizes the muscular effort across different walking conditions, while preserving the advantages of passive exoskeletons. In this letter, we developed a quasi-passive ankle exoskeleton with a variable stiffness mechanism capable of self-tuning. As the relationship between the muscular effort and the optimal spring stiffness across different walking speeds is not known a priori, a model-free, discrete-time extremum seeking control (ESC) algorithm was implemented for real-time optimization of spring stiffness. Experiments with an able-bodied subject demonstrate that as the walking speed of the user changes, ESC automatically tunes the torsional stiffness about the ankle joint. The average RMS EMG readings of tibialis anterior and soleus muscles at slow walking speed decreased by 26.48% and 7.42%, respectively.
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ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2020.3001541