Design and single-parameter adaptive fuzzy control of pneumatic lower limb exoskeleton with full state constraints

• Published in: Robotica Vol. 41; no. 3; pp. 995 - 1014
• Main Authors: Chen, Cheng, Huang, Jian, Tu, Xikai
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 01.03.2023
• Subjects: Adaptive control; Artificial muscles; Closed loops; Compliance; Controllers; Design; Design parameters; Emerging Topics of Advanced Robotics and Mechatronics; Exoskeletons; Experiments; Feedback control; Fuzzy control; Gait; Hip joint; Liapunov functions; Neural networks; Rehabilitation; Robots; Simulation; Tracking control; Training; adaptive fuzzy control; lower limb exoskeleton; barrier Lyapunov function; Pneumatic artificial muscle (PAM)
• ISSN: 0263-5747; 1469-8668
• DOI: 10.1017/S0263574722001229

With the excellent characteristic of intrinsic compliance, pneumatic artificial muscle can improve the interaction comfort of wearable robotic devices. This paper resolves the safety tracking control problem of a pneumatically actuated lower limb exoskeleton system. A single-parameter adaptive fuzzy control strategy is proposed with high control precision and full state constraints for the safe gait training tasks. Based on the barrier Lyapunov function, all signals in the closed-loop system can be bounded in finite time, which guarantees the deviation of the exoskeleton’s moving trajectory within a bounded range. Furthermore, with the proposed single-parameter adaptive law, the computational burden and the complexity of the control are reduced significantly. Finally, numerical simulations, no-load tracking experiments, and passive and active gait training experiments with healthy subjects validate the effectiveness of the proposed method.