{"title":"Optimal Mission Abort Planning for Partially Observable System","authors":"Fanping Wei, Shihan Zhou, Xiaobing Ma, Li Yang","doi":"10.1109/isssr58837.2023.00020","DOIUrl":null,"url":null,"abstract":"Mission abort is proved to be an effective approach to improve the survivability of systems. The existing researches on mission abort generally believe that the degradation state of the system can be completely observed. The prevailing research on mission abort typically assumes fully observability of the system’s state, but in fact, many systems cannot detect the health state completely during the execution of a mission. This paper study the control policy that timely aborts the mission system whose state information cannot be completely monitoring. A partially observable Markov decision process is used to solve the problem by minimizing the cost probably incurred by the failure of mission and system. Some properties of the model are presented and proved.","PeriodicalId":185173,"journal":{"name":"2023 9th International Symposium on System Security, Safety, and Reliability (ISSSR)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 9th International Symposium on System Security, Safety, and Reliability (ISSSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/isssr58837.2023.00020","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
Mission abort is proved to be an effective approach to improve the survivability of systems. The existing researches on mission abort generally believe that the degradation state of the system can be completely observed. The prevailing research on mission abort typically assumes fully observability of the system’s state, but in fact, many systems cannot detect the health state completely during the execution of a mission. This paper study the control policy that timely aborts the mission system whose state information cannot be completely monitoring. A partially observable Markov decision process is used to solve the problem by minimizing the cost probably incurred by the failure of mission and system. Some properties of the model are presented and proved.