RBFNN-based trajectory tracking and motion synchronization for mobile rehabilitation robot exoskeleton

In this paper, a mobile lower limb exoskeleton rehabilitation robot is designed and a prototype is built to verify the system functions. To achieve stable control of the exoskeleton motion, the lower limb exoskeleton dynamics model is established based on Lagrange's equation, and the control model is combined with the sliding mode function and radial basis neural network. To ensure the motion safety of user rehabilitation training, a six-wheel moving platform dynamics model is established based on D'Alembert's principle, and the velocity synchronization system is built with MATLAB and MSC.ADAMS for simulation experiments by combining the exoskeleton kinematics model and the function of the velocity synchronization system is verified by building a physical prototype.