Abstract: When a monorail inspection robot travels under complex operating conditions in mine roadways, multiple disturbances such as rail-joint impacts and time-varying wheel-rail friction can induce body vibration, which can easily result in insufficient clarity of collected inspection images and frequent shaking of video frames. A composite robust control strategy, PPC-NFTSMC-DOB, integrating Prescribed Performance Control (PPC), Nonsingular Fast Terminal Sliding Mode Control (NFTSMC), and a Disturbance Observer (DOB), was proposed. By analyzing the structural characteristics of the robot walking mechanism, dynamic and kinematic models were established for typical operating conditions such as climbing and turning. In the composite control strategy, PPC was introduced to constrain the speed-tracking error through a prescribed performance function so as to guarantee dynamic performance; NFTSMC was used to ensure finite-time convergence of the robot control system while suppressing chattering; and the DOB was employed to observe and compensate for unknown disturbances such as rail deformation and changes in the friction coefficient in real time. Simulation results showed that, under time-varying wheel-rail friction conditions, the PPC-NFTSMC-DOB strategy controlled the settling time within 0.35-0.40 s, with an overshoot of 2.0%-3.0% and a steady-state error of less than 0.005 m/s. Under rail-joint impacts as high as 20 mm, the speed overshoot remained within 7.5%-8.0% and the system returned to a stable state within 0.85-0.90 s. Compared with conventional PID, the steady-state speed-tracking error was reduced by about 80%, and the recovery time after rail-joint impact was shortened by nearly 68%. Compared with NFTSMC-DOB, the settling time was shortened by about 17% and the speed overshoot was reduced by about 50%. The proposed strategy can significantly improve the speed-tracking accuracy and operational stability of a monorail inspection robot under complex disturbances and provide technical support for high-performance control of automated inspection equipment.