{"title":"Blackboard architecture for intelligent control system","authors":"D. Linkens, M. F. Abbod, A. Browne","doi":"10.1109/ETFA.1999.813123","DOIUrl":null,"url":null,"abstract":"A blackboard for integrated intelligent control systems (BIICS) software architecture has been developed. The system is designed to simultaneously support multiple heterogeneous intelligent paradigms, such as neural networks, expert systems, fuzzy logic and genetic algorithms. It is shown how such paradigms are assimilated into the software architecture. This paper describes the BIICS system as it utilises intelligent control techniques (neuro-fuzzy and genetic optimisation) for controlling a cryogenic plant used for superconductor testing by cooling the test samples to temperatures below 100 K.","PeriodicalId":119106,"journal":{"name":"1999 7th IEEE International Conference on Emerging Technologies and Factory Automation. Proceedings ETFA '99 (Cat. No.99TH8467)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1999 7th IEEE International Conference on Emerging Technologies and Factory Automation. Proceedings ETFA '99 (Cat. No.99TH8467)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETFA.1999.813123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
A blackboard for integrated intelligent control systems (BIICS) software architecture has been developed. The system is designed to simultaneously support multiple heterogeneous intelligent paradigms, such as neural networks, expert systems, fuzzy logic and genetic algorithms. It is shown how such paradigms are assimilated into the software architecture. This paper describes the BIICS system as it utilises intelligent control techniques (neuro-fuzzy and genetic optimisation) for controlling a cryogenic plant used for superconductor testing by cooling the test samples to temperatures below 100 K.
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