Saturated Adaptive Control of Antagonistic Muscles on an Upper-Limb Hybrid Exoskeleton

Functional electrical stimulation (FES) is a viable rehabilitation method for individuals affected by neurological injuries. When FES is combined with a powered exoskeleton, a hybrid exoskeleton is created. To control hybrid exoskeletons, a user’s muscles must be stimulated while simultaneously activating the exoskeleton’s motors. In this paper, an adaptive position-based controller is developed to stimulate a user’s biceps and triceps muscle groups on an upper-limb hybrid exoskeleton. For user comfort and stability, the stimulation input is saturated and the remainder is redirected into the exoskeleton’s motor. The motor is actuated using a robust feedback controller along with the excess input from the user’s saturated muscle controller. A Lyapunov stability analysis is conducted to prove that the closed-loop position error system is uniformly ultimately bounded using the two controllers. This approach showcases a novel way to safely limit stimulation without sacrificing overall performance via a conditionally offloaded neural network on hybrid exoskeletons. Experiments were conducted on four participants without injuries for validation and to demonstrate the efficacy of the proposed approach.

I. Introduction

Every year, nearly 800,000 people have a stroke with over 600,000 of them being first time strokes [1]. These injuries can result in mobility impairments, with strokes being the leading cause of long-term disability with effects ranging from gait instability to falls, especially for people 65 and older [1], [2]. While there are many options for rehabilitative therapy, functional electrical stimulation (FES) is a common option, especially for people with extremely limited or non-existent muscular control. FES has been shown to impart a number of beneficial effects ranging from increased strength to endurance [3]. Precise control of FES however, is extremely difficult for specific rehabilitative motion due to dynamic nonlinearities and inherent inefficiencies such as fatigue [3], [4]. These effects can be compensated for by combining FES with motorized actuators in an exoskeleton, creating a hybrid exoskeleton [5], [6].