Fuzzy Adaptive Controller of a Wearable Assistive Upper Limb Exoskeleton Using a Disturbance Observer

Abstract

The motivation behind the development of a wearable assistive upper limb exoskeleton robot was to provide comprehensive multijoint therapy by assisting physiotherapists in enhancing the recovery of hemiplegic patients. However, the controlling of an upper limb exoskeleton for rehabilitation is a challenging task because of its nonlinear characteristics. This article presents a novel fuzzy adaptive controller that utilizes a high-dimensional integral-type Lyapunov function for a wearable assistive upper limb exoskeleton. A disturbance observer had been used to tackle uncertainties in the exoskeleton's dynamic model, thereby enhancing the tracking performance of the joints. The aim of this control scheme was to overcome unknown parameters in the dynamic model. The performance of the adaptive controller was validated through human interactive experiments and periodically repeated reference trajectory tests. The results demonstrated that the proposed fuzzy adaptive controller, with the inclusion of a disturbance observer, could effectively compensate for uncertain disturbances and could achieve efficient tracking of the reference trajectory. The statistical analysis revealed that the fuzzy adaptive controller performed 45%, 44%, and 31% less in average error compared to adaptive conventional controllers. The findings ascertained the potential of the proposed controller in improving the recovery of motor functions of hemiplegic patients.