AUTHOR=Mo Lufan , Feng Pengbo , Shao Yixin , Shi Di , Ju Linhang , Zhang Wuxiang , Ding Xilun 

TITLE=Anti-Disturbance Sliding Mode Control of a Novel Variable Stiffness Actuator for the Rehabilitation of Neurologically Disabled Patients

JOURNAL=Frontiers in Robotics and AI

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2022.864684

DOI=10.3389/frobt.2022.864684

ISSN=2296-9144

ABSTRACT=Lower limb exoskeletons are widely used for rehabilitation training of patients suffering from neurological disorders. To improve the human-robot interaction performance, series elastic actuators (SEAs) with low output impedance have been developed. However, the adaptability and control performance are limited by the constant spring stiffness used in current SEAs. In this paper, a novel load-adaptive variable stiffness actuator (LaVSA) is used to design an ankle exoskeleton. In order to overcome the problems of LaVSA with larger mechanical gap and more complex dynamic model. The model error caused by this gap and the dynamic model of the load-side is regarded as the disturbance set, and its value is observed in real-time with the disturbance observer (DOB). The first-order derivative of the disturbance set is treated as a bounded value. Subsequently, the parameter adaptive law is used to find the upper bound of the observation error and make corresponding compensation in the control law. Thus, a sliding mode controller based on disturbance observer is designed and Lyapunov stability analysis is given. Finally, simulation and experimental verification are carried out. The experimental results are very close to the simulation results, and the tracking error of zero impedance is less than 0.15mm.