{"title":"Research on modelling and scheduling strategy for mine transportation control system based on CPS","authors":"Jingzhao Li, Dayu Yang, Xiaoming Zhang","doi":"10.1504/IJES.2019.10022383","DOIUrl":null,"url":null,"abstract":"Cyber-physical systems (CPS) have made great strides in industrial control, intelligent transportation, remote medical and other fields. Coal mine transportation control system is a representative multi-subsystem of CPS. In this study, for the sake of optimising the scheduling mechanism for event response and precise control of tramcar behaviour in the system, we propose an event-orient scheduling algorithm (EOSA) to achieve a rapid response based on building a no-memory continuous time model. Therefore, the control system can match tasks in the queue according to the real-time load situation, and each physical entity can accurately execute the instruction under discrete event environment. Simulation results have shown that the proposed algorithm has a higher execution speed compared with the hybrid genetic algorithm and fuzzy clustering scheduling algorithm. Our approach realises the load balancing of global task scheduling and is more suitable for mine transportation scenario.","PeriodicalId":412308,"journal":{"name":"Int. J. Embed. Syst.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Embed. Syst.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJES.2019.10022383","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Cyber-physical systems (CPS) have made great strides in industrial control, intelligent transportation, remote medical and other fields. Coal mine transportation control system is a representative multi-subsystem of CPS. In this study, for the sake of optimising the scheduling mechanism for event response and precise control of tramcar behaviour in the system, we propose an event-orient scheduling algorithm (EOSA) to achieve a rapid response based on building a no-memory continuous time model. Therefore, the control system can match tasks in the queue according to the real-time load situation, and each physical entity can accurately execute the instruction under discrete event environment. Simulation results have shown that the proposed algorithm has a higher execution speed compared with the hybrid genetic algorithm and fuzzy clustering scheduling algorithm. Our approach realises the load balancing of global task scheduling and is more suitable for mine transportation scenario.