Existing studies on iterative learning control focus on the robust convergence of the iterative learning control system along the trial direction，and pay little attention to the performance along the time direction，which fails to show the dynamic characteristics of the control system． Iterative learning control for linear differential repet-itive processes with regional pole constraints was studied． Firstly，combining with the two-dimensional (2D) sys-tem theory，the 2D continuous Roesser model was built under the time domain． Then，based on the Kalman-Yakubovich-Popov lemma，the tracking performance of iterative learning control systems and regional pole con-straints problems were analyzed． Moreover，the sufficient conditions of existence for the controller were derived in terms of linear matrix inequalities，which can guarantee the system performance along the trial direction and the time direction． Furthermore，the results are extended to structural uncertainty model as well． Finally，the simula-tions for a typical actuator of tracking servo system prove that the design is effective and feasible．