Development and Learning Control of a Human Limb With a Rehabilitation Exoskeleton

Abstract

This paper describes a novel development of a lower limber exoskeleton for physical assistance and rehabilitation. The developed exoskeleton is a motorized leg device having a total of 4 DOF with hip, knee, and ankle actuated in the sagittal plane. The exoskeleton applies forces and learns the impedance parameters of both robot and human. An adaptive control scheme by incorporating learning control approaches into the exoskeleton system is developed to help the leg movement on a desired periodic trajectory and handle periodic uncertainties with known periods. The proposed control approach does not require a muscle model and can be proven to yield asymptotic stability for a nonlinear muscle model and an exoskeleton model in the presence of bounded nonlinear disturbances (e.g., spasticity and fatigue). The performance of the controller is demonstrated through closed-loop experiments on human subjects. The experiments illustrate the ability of the exoskeleton to enable the leg shank to track single and multiple period trajectories with different periods and ranges of motion.