Fuzzy logic compliance adaptation for an assist-as-needed controller on the Gait Rehabilitation Exoskeleton (GAREX)

Abstract

Assist-as-needed control strategy is an emerging approach to improve the effectiveness of gait rehabilitation training. We have proposed a pneumatic muscle (PM) driven Gait Rehabilitation Exoskeleton (GAREX) implemented with a multi-input–multi-output (MIMO) sliding mode control system to actively adjust the assistance level provided during gait rehabilitation. To realize the assist-as-needed control strategy, a specific algorithm is imperative to assess the active participation or effort of wearers and adapt the amount of assistance accordingly. We sought to establish a fuzzy logic compliance adaptation (FLCA) controller to form a novel cascade control system. We evaluated the feasibility of implemented FLCA controller on the performance of adjusting the compliance of GAREX’s knee joint according to the online assessment of the wear’s active participation level once in every gait cycle. Using controlled, treadmill-based walking tests involved three healthy subjects, we demonstrate that FLCA controller could effectively distinguish the capability/effort levels of wearers and enable the exoskeleton to adapt the knee joint compliance accordingly. Obtained results reveal that FLCA controller can collaborate well with MIMO sliding mode controller in a system and indicate the novel method of realizing assist-as-needed concept with the pneumatic muscle powered mechanisms.