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针对非线性时滞系统，讨论了输出跟踪控制的高阶迭代学习算法，并给出了算法的收敛性一证明．当由于重复定位等原因造成初态偏差时，提出一种反复学习方案，完成初态和轨迹跟踪，它对初态偏差有较强的鲁棒性．仿真结果表明了该算法的有效性．
Aiming at the nonlinear time-delay system, the high-order iterative learning algorithm of output tracking control is discussed and the convergence of the algorithm is proved. When the initial state deviation is caused by repeated positioning and other reasons, a repetitive learning plan is proposed to complete the initial state and trajectory tracking. It has strong robustness to the initial state deviation. Simulation results show the effectiveness of the algorithm.