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Abstract: In this article, we present a robust fixed-time attitude control scheme with severe funnel driving constraints for high-speed aircraft developed concerning uncertain signals. Firstly, an adaptive fixed-time radial basis function neural network (AFTR) observer is described, designed as a compensation control based on a converted attitude error system, aiming at eliminating the influence of strong disturbances and uncertainties. Then, we propose a performance-prescribed transformation strategy that can effectively enhance the accuracy of error tracking and state convergence by constructing second-order performance error functions. Based on the above preparation and transformation, we present a double-integral fixed-time sliding mode controller combined with an auxiliary oscillation-suppression function designed to achieve fixed-time convergence of attitude angles and angular rates, which ensures the rapidity of error tracking and state convergence. Finally, the fixed-time stability of the entire closed-loop system is proved via Lyapunov synthesis theory, and the upbound of convergence time is derived. Nominal and comparative simulation cases were used to investigate the effectiveness and reliability of the proposed integrated framework.