{"title":"Min-Max Optimal Control for High-Speed Train Movements with Exogenous Disturbances and Uncertain Parameters","authors":"Junfeng Ma, Sha Ma, Tao Peng, W. Gui","doi":"10.1109/ICoPESA54515.2022.9754439","DOIUrl":null,"url":null,"abstract":"This study investigates the min-max optimal control of high-speed train movements considering worst-case exogenous disturbances and uncertain parameters simultaneously. For a high-speed train, each car is modeled as a point mass connected by flexible coupling to track the reference speed profile of the train. Based on the robust model predictive control (RMPC) approach, a min-max optimal control problem is formulated to reduce the energy consumption and tracking errors while satisfying some individual constraints. The desired control inputs can be obtained by solving the min-max optimization problem.","PeriodicalId":142509,"journal":{"name":"2022 International Conference on Power Energy Systems and Applications (ICoPESA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Power Energy Systems and Applications (ICoPESA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICoPESA54515.2022.9754439","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study investigates the min-max optimal control of high-speed train movements considering worst-case exogenous disturbances and uncertain parameters simultaneously. For a high-speed train, each car is modeled as a point mass connected by flexible coupling to track the reference speed profile of the train. Based on the robust model predictive control (RMPC) approach, a min-max optimal control problem is formulated to reduce the energy consumption and tracking errors while satisfying some individual constraints. The desired control inputs can be obtained by solving the min-max optimization problem.