Model-Free Variable Impedance Control for Upper Limb Rehabilitation Robot

Abstract

This paper presents an innovative approach to control upper-limb rehabilitation robots for both passive and active-assistive rehabilitation therapy. In contrast to conventional model-based impedance control strategies, which may compromise controller stability and robustness due to model uncertainties, unmodeled dynamics, and external disturbances, our proposed model-free impedance control (MFIC) strategy eliminates the requirement for prior knowledge about the controlled system dynamics. MFIC is achieved by incorporating model-free control into conventional impedance control, employing time delay estimation (TDE) to estimate unknown dynamics. Numerical simulations confirm that MFIC outperforms traditional impedance control in terms of tracking performance and robustness. Furthermore, model-free variable impedance control (MFVIC) is introduced by enhancing MFIC with online impedance parameters adaptation using fuzzy logic control. The desired impedance model adapts according to motion and contact torque measurements. MFVIC employs two fuzzy systems to adjust the desired impedance model for two stages of rehabilitation: passive and active-assistive rehabilitation training. Our controller is designed for n degrees-of-freedom (DOF) robots and has been tested on a two-DOF robot model for simplicity.