Abstract: To address the low tracking accuracy of traditional PID control and sliding mode control (SMC) in the motion trajectory tracking of bolter drilling booms, this study proposes a Iterative Learning Compensation-based Sliding Mode Active Disturbance Rejection Control (ILC-SMADRC) algorithm. By integrating an iterative learning mechanism with a sliding mode active disturbance rejection control strategy, the proposed method significantly improves the trajectory tracking precision and system stability of the bolter drilling boom. First, a dynamic mathematical model of the bolter drilling boom is established using the D-H parameter method. Subsequently, a sliding mode active disturbance rejection controller with iterative learning compensation is designed to effectively suppress system uncertainties and external disturbances. A simulation experimental platform for the bolter drilling boom control system, based on the ILC-SMADRC algorithm, is developed using MATLAB/Simulink. Simulation results demonstrated that the ILC-SMADRC algorithm outperforms conventional PID control and SMC in trajectory tracking accuracy, reducing cumulative errors by 83.5% and 59.2%, respectively. Moreover, the proposed algorithm exhibits superior dynamic response characteristics and robustness. The study confirms that the ILC-SMADRC algorithm effectively enhances motion control stability of bolter drilling booms under the complex underground working conditions, providing a new theoretical framework for precise control of intelligent mining equipment.