To address the challenge that high-precision motion control systems of permanent magnet synchronous motors (PMSMs) are vulnerable to dynamic parameter uncertainties during the iterative learning control (ILC) process—hindering the achievement of optimal performance—a control method combining L1 adaptive control with ILC is proposed. The L1 adaptive controller compensates for dynamic parameter uncertainties, noise, load disturbances, and other factors in the time domain, ensuring that the impact of system uncertainties after compensation is sufficiently minimized. This enables the ILC to be designed based on the nominal system, allowing it to compensate for repetitive uncertainties such as friction torque and cogging torque in the iteration domain. Based on the closed-loop stability conditions of L1 adaptive control, a frequency-domain approach is adopted to design the ILC update law, ensuring overall system stability. Experimental results demonstrate that the proposed approach offers significant advantages over traditional ILC methods, greatly enhancing the system's tracking response speed while ensuring high position tracking accuracy.