A Terminal Sliding Mode with a Neural Network for an Exoskeleton Electric-Drive System

Abstract: This paper describes a control algorithm for the sliding mode of a lower-extremity exoskeleton model with a neural network for elimination of external perturbances and uncertainties. The sliding control of rapid action is used for achievement of rapid convergence in finite time, absence of singularity, and suppression of oscillations. The neural network allows the efficiency of the regulator inside the boundary layer to be improved. The analysis of the asymptotic stability of the closed system is confirmed by the Lyapunov stability criterion guaranteeing the condition of sliding. The efficiency of the proposed control method has been proven using simulation in the MATLAB software, including the construction of a five-joint mathematical model of a lower-extremity exoskeleton. © 2023, Allerton Press, Inc.