IBLF-based fuzzy adaptive super-twisting control for fixed-wing UAVs with time-varying full-state constraints and disturbances

Abstract

This paper investigates the attitude trajectory tracking problem of fixed-wing unmanned aerial vehicles (UAVs) subject to time-varying full-state constraints and unknown disturbances. To address the strong nonlinear coupling and aerodynamic uncertainties inherent in fixed-wing UAV dynamics, a robust control framework termed NFDO–ASTSMC is developed. A nonlinear fuzzy disturbance observer (NFDO) is constructed to estimate and compensate for lumped uncertainties by exploiting the universal approximation capability of fuzzy logic systems. To rigorously enforce safety-related state constraints, an adaptive super-twisting sliding mode controller (ASTSMC) is synthesized within an integral barrier Lyapunov function (IBLF) framework, which guarantees that all system states remain strictly within prescribed time-varying bounds while effectively suppressing chattering. Lyapunov-based analysis establishes the uniform ultimate boundedness of all closed-loop signals. Comparative simulation studies demonstrate that the proposed approach achieves improved tracking accuracy, enhanced robustness against disturbances, and strict constraint satisfaction when compared with existing control strategies.