In this paper, a class of nonlinear systems with time-varying uncertainties are studied. A new iterative learning
neural network approximator design scheme and corresponding boundedness lemma are proposed to approximate timevarying
uncertainties. On the basis of Lyapunov stability theory, the iterative learning controller is designed by using
backstepping and adaptive control technique. The stability theorem is obtained according to the stability analysis, which
solves the control problem of the time-varying nonlinear system. The simulation results validate the correctness of proposed
scheme.