Knee extension tracking and fatigue regulation results using a robust MPC approach in a hybrid exoskeleton

Abstract

A nonlinear model predictive controller (NMPC) is a promising approach for cooperative control of functional electrical stimulation (FES) and an exoskeleton to assist limb function in people with spinal cord injury (SCI). Potentially, the cooperative control can mitigate the effects of FES-induced muscle fatigue, a significant technical challenge impeding the clinical translation of FES. However, previous NMPC-based cooperative designs have been limited to limb regulation and may not include fatigue regulation in the control objective. In this paper, we design a new NMPC law for limb tracking and fatigue regulation and present experimental results from participants with no disability and a participant with SCI. For robust tracking, this paper augments the NMPC with a Lyapunov-based feedback controller. A terminal controller and terminal constraint regions are specifically derived to show the robust NMPC scheme’s recursive feasibility and to satisfy the input constraints. The experimental results of continuous knee tracking show dynamic allocation of exoskeleton assistance despite decreasing control effectiveness of FES due to muscle fatigue. The robust tube-based MPC reduced the knee angle’s root mean square tracking error by 34% compared to a nominal MPC. It elicited cooperative behavior when it automatically modulated (increased or decreased) FES and motor inputs for different desired fatigue levels while maintaining desired knee angle tracking performance. The statistical t-test showed that the FES input was significantly reduced in the post-fatigue trial (with the desired fatigue level of 1), and the muscle was significantly less fatigued compared to the pre-fatigue experiment (with the desired fatigue level of 0.5).