{"title":"多输入多输出过程的安全设定值监控","authors":"C. Economakos, F. Koumboulis","doi":"10.1109/ETFA.2006.355217","DOIUrl":null,"url":null,"abstract":"In a previous paper we introduced a supervisory control framework for setting the operating point of an industrial process with unknown characteristics. Here we extend this methodology for the case of MIMO processes. The proposed supervisory control framework is agent-based and it involves modeling agents and intelligent agents. The modeling agents derive local steady-state models of the process during normal process operation by using various identification techniques, each of which corresponds to a different instantiation of our system. The intelligent agents are proposed to be implemented using finite automata units. The performance of the proposed scheme is illustrated through simulation results on well-known benchmark problems of chemical industry.","PeriodicalId":431393,"journal":{"name":"2006 IEEE Conference on Emerging Technologies and Factory Automation","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Safe Set Point Supervisor for MIMO Processes\",\"authors\":\"C. Economakos, F. Koumboulis\",\"doi\":\"10.1109/ETFA.2006.355217\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a previous paper we introduced a supervisory control framework for setting the operating point of an industrial process with unknown characteristics. Here we extend this methodology for the case of MIMO processes. The proposed supervisory control framework is agent-based and it involves modeling agents and intelligent agents. The modeling agents derive local steady-state models of the process during normal process operation by using various identification techniques, each of which corresponds to a different instantiation of our system. The intelligent agents are proposed to be implemented using finite automata units. The performance of the proposed scheme is illustrated through simulation results on well-known benchmark problems of chemical industry.\",\"PeriodicalId\":431393,\"journal\":{\"name\":\"2006 IEEE Conference on Emerging Technologies and Factory Automation\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE Conference on Emerging Technologies and Factory Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETFA.2006.355217\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Conference on Emerging Technologies and Factory Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETFA.2006.355217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In a previous paper we introduced a supervisory control framework for setting the operating point of an industrial process with unknown characteristics. Here we extend this methodology for the case of MIMO processes. The proposed supervisory control framework is agent-based and it involves modeling agents and intelligent agents. The modeling agents derive local steady-state models of the process during normal process operation by using various identification techniques, each of which corresponds to a different instantiation of our system. The intelligent agents are proposed to be implemented using finite automata units. The performance of the proposed scheme is illustrated through simulation results on well-known benchmark problems of chemical industry.