This paper proposes a robust barrier-function-based fuzzy adaptive super-twisting integral terminal sliding-mode control (BF-FAST-ITSMC) for robotic manipulators subject to external disturbances. Initially, an integral terminal sliding-mode manifold is designed to ensure finite-time error convergence and eliminate steady-state offsets. To reduce model dependence, the unknown nonlinear function is approximated and compensated using a fuzzy approximator. By combining the super-twisting algorithm (STA) and the barrier-function-based adaptive gains, the designed BF-FAST-ITSMC can suppress actuator chattering effectively, which allows control gains to increase automatically as the error approaches the prescribed boundary. This mechanism ensures that tracking errors are strictly confined within a predefined bound. Comparative simulations on an inverted pendulum and robotic manipulators with one to three degrees of freedom demonstrate that the proposed method provides superior tracking precision, smooth control torque, and enhanced robustness compared to conventional and fuzzy ITSMC schemes.
Wang et al. (Tue,) studied this question.