Finite-time adaptive fuzzy control for a PAM-driven rehabilitation exoskeleton robot

An upper limb rehabilitation exoskeleton robot is developed to provide postoperative assistive rehabilitation training for patients with rotator cuff injuries. The use of pneumatic artificial muscle (PAM) as actuators for the exoskeleton robot provides good flexibility and safety for the patient, whereas the significant nonlinearity of PAM reduces the control performance of the system. To address this issue, this paper proposes a finite-time adaptive fuzzy control method, which uses fuzzy logic to approximate the system's external disturbances and unknown dynamics in real-time. A finite-time controller is designed to ensure that the tracking error converge to a small neighborhood of the origin within a finite time. Finally, the effectiveness of the proposed method is experimentally validated. Experimental results demonstrated that the proposed method exhibits faster response speed and better robustness, and thus providing more accurate and stable tracking performance for the exoskeleton robot.