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Firstly, radial basis function neural network (RBFNN) and adaptive virtual parameter learning method are combined to compensate dynamic uncertainty and external interference. Then barrier Lyapunov function (BLF) is used to prevent the violation of the full-state constraint. The Lyapunov stability theory is used to prove that the proposed control scheme can achieve semi-global uniform boundedness of the closed-loop system. Finally, simulation results further demonstrate its excellent performance. 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