The problem to improving the rate of convergence and the accuracy of tracking of ilc for deterministic linear systems is considered , in the meanwhile , the effects of the plant characteristics , various types of disturbances , errors in initial conditions and the " slowly " varying desired trajectories on the convergence and performance of ilc for uncertain linear and nonlinear systems are also investigated 针对确定的线性系统,主要研究能够提高算法的收敛速度和跟踪精度的迭代学习控制技术;针对不确定的线性和非线性系统,主要考虑系统的特性、各种干扰、初始状态偏移和不确定的未建模动态以及缓慢变化的期望轨迹对迭代学习控制过程收敛性和跟踪性能的影响。