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

Transportation Safety and Environment 2024年第1期6卷 93-102页

作者： Zhongqi Li Liang Zhou Hui Yang Yue Yan School of Electrical and Automation Engineering East China Jiaotong UniversityNanchang 330013JiangxiChina State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong UniversityNanchang 330013JiangxiChina

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.

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

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Performance analysis of SBAS ephemeris corrections and integrity algorithms in China region

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Satellite Navigation 2021年第1期2卷 213-226页

作者： Biao Jin Shanshan Chen Dongjun Li Yuechen Wang Elhadi Takka Space Star Technology Co. Ltd.Beijing 100194China Yunnan Observatory Chinese Academy of SciencesKunming 650011China UniStrong Science Technology Co. Ltd.Beijing 100176China Ecole Militaire Polytechnique 16024 AlgerAlgeria.

Satellite Based Augmentation Systems(SBASs)improve the positioning accuracy and integrity by broadcasting to the civil aviation community the corrections and integrity parameters.A snapshot algorithm based on the minimum variance estimation is investigated in this study to calculate the satellite clock and orbit corrections.A chi-square test is performed on the remaining errors in the corrected ephemeris to guarantee the integrity.User Differential Range Error(UDRE)and scaling matrix contained in Message Type 28 are derived using the covariance information based on the assumption that one of the reference stations failed.A software package is developed and applied in the real data collected at 26 stations.International GNSS(Global Navigation Satellite System)Service(IGS)precise clock and orbit products are taken as the references to assess the accuracy of corrections.For both Global Positioning System(GPS)and BeiDou Navigation Satellite System(BDS),the range accuracy of 0.10 m can be achieved with the employment of the derived corrections.No obvious performance difference between GPS and BDS is found.UDREs for all visible satellites are generated with the maximum index of 12 and minimum index of 3.The geometric range differences calculated with IGS precise products and broadcast ephemeris are employed to assess the integrity of UDRE.It is found that the UDRE is able to bound the residuals with 99.9%confidence which meet the requirement of aviation users.With ionospheric delay corrected by Global Ionosphere Map(GIM),the positioning accuracy of 0.98 m with GPS corrections and 0.80 m with multi-constellation augmentation can be achieved which indicates a significant improvement of GPS standalone results.

关键词： SBAS minimum variance estimation Ephemeris correction UDRE

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Evaluation of GPS/DR navigation system based on optimal smooth theory

Evaluation of GPS/DR navigation system based on optimal smoo...

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第四届国际自动化测试与仪器仪表学术会议

作者： Bao Ruixin School of Mechanical Engineering Liaoning Shihua University

In vehicle navigation system,Kalman filtering method is used to estimate vehicle driving state,but the effect of this method strongly depends on the accuracy of initial state,and the precision of this method is low.This paper presented an application of optimal smoother method,this method calculated minimum variance estimation using all data the system obtained,the accuracy is improved,at the same time,the accumulative error is controlled using this method.The simulation shows that this method is effective.

关键词： Kalman filtering optimal smoother minimum variance estimation

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