Robust Sliding-Mode Control of a Two-DOF Lower-Limb Exoskeleton Using a Cascade-Adaptive Super-Twisting Observer

This paper presents an output-feedback sliding-mode control strategy for a two-DOF lower-limb exoskeleton system aimed at rehabilitation assistance for disabled individuals. The core of the approach is a cascade super-twisting observer, beginning with a super-twisting differentiator (STD) that estimates unmeasured angular velocities from measured joint angles. These velocity estimates feed into a second-stage adaptive super-twisting sliding-mode observer (ASTSMO), which accurately reconstructs external load torque disturbances affecting the system. Using these estimates, a sliding-mode controller robustly tracks the exoskeleton’s desired trajectories despite external disturbances. The stability of the proposed control scheme is rigorously established through Lyapunov-based analysis within a sliding-mode framework. Numerical simulations conducted in Matlab R2022/Simulink demonstrate the method’s effectiveness in accurately estimating unmeasured states and unknown disturbances, as well as achieving robust tracking performance in the presence of system uncertainties.