Development and Hybrid Control of an Electrically Actuated Lower Limb Exoskeleton for Motion Assistance

• Main Authors: Chao-Feng Chen, Zhi-Jiang Du, Long He, Yong-Jun Shi, Jia-Qi Wang, Guo-Qiang Xu, Yu Zhang, Dong-Mei Wu, Wei Dong
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Lower limb exoskeleton; system design; human motion intention; hybrid dual-mode control; tracking performance; power-assisted effect
• Online Access: https://ieeexplore.ieee.org/document/8897544/

This paper describes a system design and hybrid control algorithm of an electrically actuated lower limb exoskeleton (LLE). The system design mainly includes three parts: mechanical structure design, actuation system design and sensor system design. According to the initial state of the joint angle, LLE can be divided into Non-anthropomorphic state (NAS) and anthropomorphic state (AS). The human motion intention (HMI) estimation can be divided into gait phase classification and reference trajectory estimation. The fuzzy logic is used to detect different phases in the gait phase classification. In the reference trajectory estimation, the kinematic model of the LLE is utilized to obtain a continuous joint trajectory, which is used as input of the control law. To make the LLE accurately follow the movement of people and remain stable, a hybrid dual-mode control strategy is proposed in this paper, i.e., the adaptive impedance control (AIC) method is used to improve the stability and resistance to shock in stance phase, and the active disturbance rejection control with the fast terminal sliding mode control (ADRC-FTSMC) method is employed to improve the response speed and the tracking precision in swing phase. Furthermore, in order to solve the torque discontinuity in the switching process, a smoothing method is proposed during the transition. Finally, the prototype experiments were set up to verify the tracking performance and power-assisted effect of the proposed exoskeleton. The experiments results show the LLE can achieve excellent tracking performance and power-assisted effect based on the proposed HMI methodology and hybrid dual-mode control strategy.