Adaptive Admittance Control of Hybrid Exoskeletons

Abstract

Hybrid exoskeletons combine two increasingly common rehabilitative therapies, functional electrical stimulation (FES) and robotic therapy, for use on individuals with neuromuscular disorders. As hybrid exoskeletons increase in popularity and complexity, it remains an ever-important issue to not only assist people in performing rehabilitation, but also to guarantee their safety while coupled to the exoskeleton. In this paper, a novel adaptive controller for hybrid exoskeletons is developed to regulate an admittance error system using the exoskeleton's motors while simultaneously regulating a position error system using the operator's muscles, stimulated through FES. The stability of the controller is rigorously analyzed using a combined Lyapunov-passivity approach and while the hybrid exoskeleton is proven to be energetically passive, the admittance error system is proven to demonstrate global exponential convergence to a uniform ultimate bound. Simulations were performed on a two degree-of-freedom lower-limb hybrid exoskeleton to demonstrate the efficacy of the controller. Results show the controller achieves an average admittance tracking error of 0.00±0.08 rad and 0.00±0.08 rad/s for joint one (the knee joint), and 0.01±0.11 rad and 0.01±0.12 rad/s for joint two (the ankle joint), while simultaneously applying FES to the operator's muscles for rehabilitation.