Aiming at the speed control problem of the train under external disturbance and uncertain dynamics， a composite control scheme combining integral back-stepping （IBS） method and linear active disturbance rejection control （LADRC） is designed. Firstly， considering the strong coupling of the train， a multi-particle model with time-varying coefficients is established to better conform to the real longitudinal dynamic characteristics and force conditions of the train. Secondly， to reduce the difficulty of parameter adjustment， the tracking differentiator （TD） and the extended state observer （ESO） are in linear form. TD is used to obtain the differential signal and has a filtering effect. The problem of differential explosion in back-stepping method can be solved by using the TD to derive the virtual control quantity. ESO is used to estimate the total disturbance in real-time. In addition， the IBS method is used to improve the error feedback control law， and an integral back-stepping linear active disturbance rejection control （IBS-LADRC） algorithm is designed. Finally， the convergence of the observation error and the stability of the closed-loop system are proved. Combined with the parameters of AH electric multiple units of Hangzhou Metro Line 6 and the actual line data， the simulation comparison is carried out， and the IBS-LADRC is compared with the back-stepping method， LADRC algorithm and PID control.The results show that under the IBS-LADRC method， the velocity error of each power unit is within ±0.04 km/h， the acceleration is within ±1 m/s2， and the acceleration and velocity error change smoothly. The coupler force is the smallest and the change is the most gentle compared with the other three methods， and the maximum coupler force is only 2 320 N. The proposed control strategy has high tracking accuracy for the expected speed of the train， which is conducive to ensuring the safety of the coupler， preventing the coupler from breaking， and improving the safety， stability and passenger comfort of the train operation.