{"title":"Synthesis of train traffic control system with evolutionary computing","authors":"A. O. Kilyen, M. Hulea, T. Letia","doi":"10.1109/AQTR.2014.6857825","DOIUrl":null,"url":null,"abstract":"The purpose of this paper is to present a method of control synthesis f o r a given train station system and train set based on optimal resource scheduling. A Genetic Algorithm was designed to resolve the resource allocation problem in an example train traffic system with three stations. A method of controller synthesis based on Genetic Programming is also presented. This method synthetizes controllers that behaves according to the obtained resource allocation tables. These controllers are built based on Timed Petri Nets. The possibility of minimal environmental change was also added in order to obtain flexible and robust controllers. Solution methods were proposed f o r this extended problem.","PeriodicalId":297141,"journal":{"name":"2014 IEEE International Conference on Automation, Quality and Testing, Robotics","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Automation, Quality and Testing, Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AQTR.2014.6857825","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The purpose of this paper is to present a method of control synthesis f o r a given train station system and train set based on optimal resource scheduling. A Genetic Algorithm was designed to resolve the resource allocation problem in an example train traffic system with three stations. A method of controller synthesis based on Genetic Programming is also presented. This method synthetizes controllers that behaves according to the obtained resource allocation tables. These controllers are built based on Timed Petri Nets. The possibility of minimal environmental change was also added in order to obtain flexible and robust controllers. Solution methods were proposed f o r this extended problem.