Adaptive fuzzy control of time-varying impedance in rehabilitation exercises

Time-varying impedance control is pivotal in shaping the dynamics of both patients and robots concurrently, facilitating tailored training for rehabilitation within human-robot interaction (HRI) scenarios, particularly for exoskeleton robots. Given the diverse physical characteristics of patients, sudden movement variations can pose challenges, potentially disrupting the robot's functionality. Moreover, the inherent dynamics of robots coupled with uncertainties present additional hurdles for ensuring optimal and safe rehabilitation exercises. In this study, we introduce a novel approach: fuzzy adaptive time-varying impedance control, adept at mitigating external disturbances and addressing all uncertainties associated with both robot and patient dynamics, thereby ensuring safe and effective rehabilitation protocols. A primary concern with time-varying impedance control lies in system stability. Leveraging Lyapunov stability analysis, we delineate the safe operational boundaries of time-varying impedance control, thus averting potential instability. Our proposed impedance modulation facilitates desired dynamics while facilitating passive and isometric exercises for patients. Through simulations conducted in MATLAB2023, we demonstrate the efficacy of our approach, comparing its performance against conventional constant impedance control methods and also we used the controller for three different patients with various physical features that shows good results for all of them.