Abstract: In this paper, an iterative learning controller is presented for a class of strict-feedback nonlinear systems with time-varying uncertainties. The learning controller is designed based on the Lyapunov-like synthesis, which can handle system dynamics with non-global Lipschitz nonlinearities. For the controller design, the time-varying parameters are expanded into Taylor series with bounded remained term, and backstepping design technique is applied. Hyperbolic tangent function is used with a typical series introduced in order to guarantee the differentiability of the virtue control variables. Theoretical analysis shows that all signals in the closed-loop system remain bounded and that complete tracking over a pre-specified time interval is achieved.