Abstract: The trajectory tracking control accuracy of coal mine anchor bolt drilling booms has an important impact on the efficiency and safety of support operations. To address the insufficient trajectory tracking accuracy caused by the nonlinearity, time delay, and time-varying parameters of the hydraulic system of underground coal mine anchor bolt drilling booms, an Iterative-Learning-Compensation-Based Sliding-Mode Active Disturbance Rejection Control (ILC-SMADRC) algorithm was proposed. A six-degree-of-freedom kinematic model of the anchor bolt drilling boom was established based on the D-H parameter method, and smooth trajectories were planned using quintic polynomial interpolation. A high-order Extended State Observer (ESO) was designed to achieve accurate estimation of system states and disturbances. A novel sliding mode reaching law constructed based on the Rayleigh distribution function and the tanh function was proposed to effectively suppress high-frequency chattering. Iterative learning compensation was incorporated to improve trajectory tracking accuracy and robustness, and system stability was proven using the Lyapunov criterion. Simulation results showed that, compared with conventional PID and Sliding Mode Control (SMC) methods, the cumulative absolute error of the ILC-SMADRC algorithm was reduced by 83.5% and 59.2%, respectively, with the error of joint 6 reduced by 96.8% compared with SMC, significantly enhancing the motion control accuracy and stability of the anchor bolt drilling boom under complex underground operating conditions.