Adaptive Synergetic Motion Control for Wearable Knee‐Assistive System: A Rehabilitation of Disabled Patients

Abstract

In this study, synergetic‐based adaptive control design is developed for trajectory tracking control of joint position in knee‐rehabilitation system. This system is often utilized for rehabilitation of patients with lower‐limb disabilities. However, this knee‐assistive system is subject to uncertainties when applied to different persons undertaking exercises. This is due to the different masses and inertias of different persons. In order to cope with these uncertainties, an adaptive scheme has been proposed. In this study, an adaptive synergetic control scheme is established, and control laws are developed to ensure stable knee exoskeleton system subjected to uncertainties in parameters. Based on Lyapunov stability analysis, the developed adaptive synergetic laws are used to estimate the potential uncertainties in the coefficients of the knee‐assistive system. These developed control laws guarantee the stability of the knee rehabilitation system controlled by the adaptive synergetic controller. In this study, particle swarm optimization (PSO) algorithm is introduced to tune the design parameters of adaptive and non‐adaptive synergetic controllers, in order to optimize their tracking performances by minimizing an error‐cost function. Numerical simulations are conducted to show the effectiveness of the proposed synergetic controllers for tracking control of the exoskeleton knee system. The results show that compared to classical synergetic controllers, the adaptive synergetic controller can guarantee the boundedness of the estimated parameters and hence avoid drifting, which in turn ensures the stability of the controlled system in the presence of parameter uncertainties.