Fuzzy Approximation-Based Adaptive Backstepping Control of an Exoskeleton for Human Upper Limbs

This paper presents fuzzy approximation-based adaptive backstepping control of an exoskeleton for human upper limbs to provide forearm movement assistance so that a human forearm can track any continuous desired trajectory (or constant setpoint) in the presence of parametric/functional uncertainties...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems 2015-06, Vol.23 (3), p.555-566
Main Authors: Li, Zhijun, Su, Chun-Yi, Li, Guanglin, Su, Hang
Format: Article
Language:English
Subjects:
Approximation methods
DC motors
Exoskeletons
Joints
Robots
Trajectory
Uncertainty
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Summary:This paper presents fuzzy approximation-based adaptive backstepping control of an exoskeleton for human upper limbs to provide forearm movement assistance so that a human forearm can track any continuous desired trajectory (or constant setpoint) in the presence of parametric/functional uncertainties, unmodeled dynamics, actuator dynamics, and/or disturbances from environments. Given the desired trajectories of human forearm positions, in the developed control, adaptive fuzzy approximators are used to estimate the dynamical uncertainties of the human-robot system, and an iterative learning scheme is utilized to compensate for unknown time-varying periodic disturbances. With the synthesis of the backstepping, iterative learning, and Lyapunov function approaches, the developed controller does not require exact knowledge of the exoskeleton model, and the close-loop system can be proven to be semiglobally uniformly bounded. Three comparison experiments are conducted to illustrate the effectiveness of the proposed control scheme by tracking periodic/repeated trajectories.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2014.2317511