Aiming at the problem of low tension control accuracy existing in the warp yarn tension control of carbon fiber corner link loom, a warp yarn tension control method considering the effect of beating-up is proposed. Firstly, the elongation of the warp yarn during beating-up is analyzed, and then a new tension control model of the warp feeding system is established by combining Hooke"s law with the existing tension model. Secondly, a command filter backstepping sliding mode controller is proposed, which estimates the first-order differentiation of the virtual control law through the filter to avoid theproblem of "differential expansion", and adopts the RBF neural network to adaptively estimate the unmodeled part of the system, and at the same time, introduces the sliding mode control to enhance the robustness of the system. Finally, using MATLAB/SIMULINK software to carry out simulation experiments on the tension system, the results show that: the filtered backstepping sliding mode control considering the effect of beating-up in tension control compared with the traditional backstepping sliding mode control in the case of similar response time, the stabilization time is shortened by nearly 16.3%, the amount of overshooting is reduced by 24.6%; compared with the fuzzy PID control, the stabilization time is shortened by 51.7%, the amount of overshooting is reduced by 49.2%.