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• W3091661330 abstract "Lower-limb exoskeletons are increasingly used in gait assistance applications to assist patients with locomotive disorders in rehabilitation and daily life. To provide assistance based on the user's variable joint stiffness with human-like characteristics is a growing and challenging field. This paper proposed an adaptive controller for a lower-limb exoskeleton with time-varying delay using variable stiffness transferring strategy. Neural network compensation was applied to estimate the nonlinearity caused by the time-varying delay and the model uncertainties in the lower-limb exoskeleton systems. To compensate for the delay, an integral Lyapunov function was introduced and an adaptive Lyapunov-based control structure was constructed. In the controller design, a variable stiffness transferring strategy was integrated and the stiffness was transferred from an able-bodied individual estimated with muscle forces and musclotendinous stiffness. By utilizing the proposed adaptive neural network control strategy and adaptive Lyapunov-based control structure, the global stability of lower-limb exoskeleton system was guaranteed and the tracking errors converged to the zero. The proposed control strategy was validated on 2-DOFs knee and ankle lower limb exoskeleton in simulation, demonstrating effective results in trajectories tracking, and thus is crucial for determining strategies for exoskeleton control." @default.
• W3091661330 created "2020-10-08" @default.
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• W3091661330 date "2020-12-01" @default.
• W3091661330 modified "2023-10-01" @default.
• W3091661330 title "Adaptive Neural Network Control for a Lower-Limb Exoskeleton using Variable Stiffness Transferring" @default.
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• W3091661330 doi "https://doi.org/10.1109/icarm49381.2020.9195302" @default.
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