# Research on Tracking Control of Urban Rail Trains Based on Improved Disturbance Observer
###### Abstract  
Urban rail transit trains operate in a complex and changing environment susceptible to uncertainties such as unknown disturbances or actuator faults. In order to ensure that the automatic train control (ATC) system can operate safely and control accurately even when the train is affected by uncertainties, the train is first subjected to force analysis, and a multiple point-mass model for the urban rail trains (URTs) is established. Secondly, an improved disturbance observer is proposed to estimate and attenuate the unknown disturbance online. The stability of the URTs system under the improved disturbance observer-based control (IDOBC) is demonstrated based on the linear matrix inequality and Lyapunov theorem. Finally, the Simulink platform is used to verify the target curves obtained after data optimization of the certain Nanchang Metro line for case verification. Compared to the traditional disturbance observer-based control (TDOBC) method, the train tracking error converges to near the zero region faster after being subjected to an external disturbance, and the mean absolute error (MAE) metric is smaller throughout the whole operation. The control strategy proposed in this paper has a more desirable control effect and can ensure the safer and more stable operation of the URTs. urban rail trains; improved disturbance observer; unknown disturbance; tracking control +
Footnote †: journal: Applied sciences  
of multiple trains. Literature [8] solves the nonlinear optimization problem of the train presence by using punctuality as a penalty factor and minimum traction energy as an objective using a heuristic evolutionary algorithm. In [9], a PID controller is implemented to enhance the resilience and precision in tracking of the subway train and use neural networks to adjust the PID parameter gains adaptively. In the above mention literature, the researchers analyzed the motion state of URTs by considering the URTs as a single point-mass model to establish the kinematic equations. The single point-mass model has the advantage of real-time and accuracy in simulating the operation effect of the UTRs and has a high level of computational efficiency. However, the single point-mass model neglects the interconnected forces among the carriages, which reduces the control accuracy during the force analysis, and the control effect under the operating platform is also not satisfactory [10]. Therefore, in order to improve the control accuracy of the UTRs, this paper considers the coupling forces to establish a multiple point-mass model, which better corresponds to the practical operation of URTs. The URTs operate most of the time in tunnels, where the operating environment is relatively stable and less affected by uncertain disturbances. Nevertheless, during the actual operation, it remains susceptible to unpredictable external disturbances caused by variations in environmental factors. Especially in the moment of operation from the tunnel to the ground environment, the resistance suffered by the URTs will change significantly. In addition, when the URTs operate on the elevated road, the impact of some uncertainties, such as wind gusts of different levels or disturbance from trains running on adjacent tracks, will be significantly increased. These uncertain external unknown disturbances will seriously affect the tracking performance of the URTs and may also pose a threat to the safe and stable operation of the URTs. In order to improve the robustness of the high-speed train system, a speed prediction control method based on an improved echo state network was proposed in [11]. In [12], a \(H_{\infty}\) robust output feedback controller with uncertain drag coefficients was designed to suppress external disturbances. This method may be too conservative in practical application engineering to eliminate disturbances at a fast rate.