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 針對確定的線性系統(tǒng),主要研究能夠提高算法的收斂速度和跟蹤精度的迭代學習控制技術;針對不確定的線性和非線性系統(tǒng),主要考慮系統(tǒng)的特性、各種干擾、初始狀態(tài)偏移和不確定的未建模動態(tài)以及緩慢變化的期望軌跡對迭代學習控制過程收斂性和跟蹤性能的影響。