Fuzzy Enhanced Adaptive Admittance Control of a Wearable Walking Exoskeleton With Step Trajectory Shaping

The generation of motor adaptation in response to mechanical perturbation during human walking is seldom considered in an exoskeleton system. Reshaping step trajectory over consecutive gait cycles for a walking exoskeleton is investigated in this article. Step adjustment of a walking exoskeleton can adapt to human walking intention by shaping step trajectory. This work develops an admittance adaptive fuzzy control strategy for a walking exoskeleton robot to provide assistance for human lower limb movement. Considering human walking intention and utilizing an admittance model, it shapes a reference trajectory to ensure that the walking exoskeleton follows it according to the human-robot force produced by its wearer. Considering a nonlinear and dynamic model with uncertainties, this work designs an integral-type Lyapunov function controller to track a reference trajectory. A disturbance observer is integrated into the controller design to compensate for uncertain disturbance in order to achieve an effective tracking performance. Finally, this work conducts experiments on two healthy subjects with the proposed method on a walking exoskeleton to validate its effectiveness. The results show that it can be applied to walking exoskeletons to enhance human mobility.

Automated summary

This article investigates step adjustment in a walking exoskeleton system to enhance human mobility. By considering human walking intention and utilizing an admittance model, the proposed method shapes a reference trajectory for the walking exoskeleton robot to follow. Experiments on healthy subjects demonstrate its effectiveness in improving human mobility when applied to walking exoskeletons.