The quadcopter as a typical complex system, encompasses strong coupling, demands for multivariable control, and significant nonlinear characteristics, posing substantial challenges for precise attitude regulation. To address this issue, this paper delves into the essence of quadcopter construction and flight mechanisms, thereby constructing an accurate mathematical model. Through model simplification, we design a flight control system aimed at providing a reliable benchmark model for subsequent control algorithm development. Building upon this foundation, the paper innovatively proposes a quadcopter attitude control scheme based on model-free adaptive iterative learning control strategy. To validate the effectiveness of this control strategy, comprehensive simulation experiments are conducted using the Matlab platform. The experimental results demonstrate that compared to traditional PID controllers, the proposed model-free adaptive iterative learning controller not only significantly enhances system robustness but also achieves substantial reduction in settling time. Moreover, it reduces both maximum error and mean squared error, showcasing superior control performance and stability. This opens up new avenues for attitude control of quadcopter flight systems.