Model-free adaptive robust control method for high-speed trains

作     者：Zhongqi Li Liang Zhou Hui Yang Yue Yan 

作者机构：School of Electrical and Automation EngineeringEast China Jiaotong UniversityNanchang 330013JiangxiChina State Key Laboratory of Performance Monitoring and Protecting of Rail Transit InfrastructureEast China Jiaotong UniversityNanchang 330013JiangxiChina 

出 版 物：《Transportation Safety and Environment》 (交通安全与环境（英文）)

年 卷 期：2024年第6卷第1期

页      面：93-102页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0823[工学-交通运输工程] 

基　　金：The authors thank the anonymous reviewers for their valuable suggestions.This work is supported by funds National Natural Science Foundation of China(Grants No.52162048,61991404 and 62003138) National Key Research and Development Program of China(Grant No.2020YFB1713703) Jiangxi Graduate Innovation Fund Project(Grant No.YC2021-S446). 

主　　题：automatic train operation(ATO) model-free adaptive control(MFAC) disturbance suppression minimum variance estimation Kalman filtering(KF) partial format data model 

摘      要：Aiming at the robustness issue in high-speed trains(HSTs)operation control,this article proposes a model-free adaptive control(MFAC)scheme to suppress disturbance.Firstly,the dynamic linearization data model of train system under the action of measurement disturbance is given,and the Kalman filter(KF)based on this model is derived under the minimum variance estimation criterion.Then,according to the KF,an anti-interference MFAC scheme is designed.This scheme only needs the input and output data of the controlled system to realize the MFAC of the train under strong disturbance.Finally,the simulation experiment of CRH380A HSTs is carried out and compared with the traditional MFAC and the MFAC with attenuation factor.The proposed control algorithm can effectively suppress the measurement disturbance,and obtain smaller tracking error and larger signal to noise ratio with better applicability.