Abstract: Sensor saturation is a common physical constraint in control systems. Two learning control algorithms are proposed in this research for a class of linear systems with saturated output. Specifically, an open-loop P-type iterative learning controller is first designed for repetitive operating systems to ensure entire tracking in limited interval, and the convergence condition is derived by employing λ norm analysis. Furthermore, for controlled systems with periodic desired trajectory, the asymptotic tracking condition of closed-loop P-type repetitive learning control technique is deduced as well. Finally, the simulation results show the effectiveness of the proposed algorithms.