Adaptive Robust Backstepping Force Control of 1-DOF Joint Exoskeleton for Human Performance Augmentation

Abstract

The exoskeleton for human performance augmentation is a human-machine interaction system whose control goal is to minimize the human machine interaction force while carrying external loads and following human motion. This paper addresses the dynamics and the interaction force control of a 1-DOF joint exoskeleton. A backstepping control method based on the whole dynamics is proposed to overcome the bandwidth restriction of the commonly used cascade control. Lager bandwidth can be achieved by considering the coupling effect between different layers of dynamics. Moreover, a backstepping adaptive robust control(ARC) algorithm is developed to deal with the effect of parametric uncertainties and uncertain nonlinearities of the system. It is theoretically shown that the proposed adaptive robust backstepping force controller not only achieves good robust performance to model uncertainty, but also faster closed-loop responses and smaller interaction forces. All these theoretical results have been validated by simulation.