By constructing nonlinear filters and using Young's inequality, a new adaptive finite-time control method is proposed for a class of strict-feedback nonlinear systems with full state constraints, unmodeled dynamics and dynamic disturbances in this paper. The constrained system is transformed into an unconstrained system by introducing the nonlinear mapping. The radial basis function neural networks are utilized to approximate unknown nonlinear smooth functions. A dynamic signal produced by a auxiliary system is used to deal with unmodeled dynamics. Using the modified dynamic surface control technology and finite-time control method, a simple controller is developed. The singularity problem in the existing finite -time control is removed, and the converging speed of the system is accelerated. Theoretical analysis shows that all signals in the closed-loop system are bounded in finite time. Full state constraints are not triggered. Simulation results of numerical example show that the proposed approach is effective.