A repetitive learning control scheme is designed for high-order nonlinear systems with parametric and non-
parametric uncertainties. It is assumed that the common periodicity of unknown time-varying parameter and reference
signal are known. By regrouping the system parameters, all unknown time-varying terms are combined into a periodically
time-varying vector. Combining the modifying backstepping approach with the pointwise integral mechanism, a differential-
difference mixed-type adaptive law and an adaptive repetitive learning control one are constructed to ensure the asymptotic
convergence of the tracking error in the sense of square error norm. Also, a sufficient condition of the convergence of the
method is given. A simulation example shows the effectiveness of the proposed method.