Journal of Advanced Computational Intelligence and Intelligent Informatics
Online ISSN : 1883-8014
Print ISSN : 1343-0130
ISSN-L : 1883-8014
Regular Papers
Cooperative Active Disturbance Rejection Control for Heavy-Haul Trains
Zongying SongShuo Li Xiaoquan YuYingze YangXingzhong Wang
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JOURNAL OPEN ACCESS

2025 Volume 29 Issue 1 Pages 165-174

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Abstract

Cooperative control of multiple heavy-haul trains can improve the safety and efficiency of heavy-haul railway transportation. However, the influence of internal and external unknown disturbances for multiple heavy-haul trains is a serious obstacle, which will lead to imprecise train operation control. To address this issue, a cooperative active disturbance rejection control for heavy-haul trains is proposed. First, a multi-mass point longitudinal dynamic model of heavy-haul trains is established to meet the actual operation. Second, a cooperative active disturbance rejection controller is designed to estimate and compensate for the disturbance caused by the interaction between the trains and environment. Moreover, the extended state observer is leverage to estimate the nonlinear disturbance online, which enhances the resistance of multiple heavy-haul trains to nonlinear time-varying disturbance and suppresses the overshoots of train velocities and inter-train distance. Finally, the performance of the proposed method is verified in two different simulation scenarios: acceleration and deceleration conditions. The simulation results show that the proposed method reduces the maximum relative displacement by 38.9% and the velocity error by 54.5%.

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