Data-driven model-free adaptive sliding mode control for the multi degree-of-freedom robotic exoskeleton

In this paper, a data-driven model-free adaptive sliding mode control (MFASMC) approach is proposed based on a novel transformation and linearization of the robotic exoskeleton dynamics and a discrete time sliding mode with exponential reaching law. The main feature of the approach is that the dynamics of the multi degree-of-freedom (DOF) robotic exoskeleton are transformed and linearized properly for MFASMC, the controller designing depends only on the measured input torque and output velocity of each joint of the exoskeleton and the sliding mode reaching law guarantees the convergence of MFASMC schemes. The proposed control strategy can maneuver the robotic exoskeleton tracking on its desired velocity tightly even when the dynamic parameter of the exoskeleton is time-varying irregularly and uncertainly. Extensive simulation experiments are conducted by a SimMechanics model of the robotic exoskeleton to illustrate the effectiveness of the proposed approaches.