{"title":"Towards fuzzy gain scheduling for gas turbine aero-engine systems: a multiobjective approach","authors":"B. Bica, A. Chipperfield, P. Fleming","doi":"10.1109/ICIT.2000.854104","DOIUrl":null,"url":null,"abstract":"This paper investigates the use of a nonconventional approach to the control of a gas turbine aeroengine. The rationale behind this study is the need to develop advanced tools and techniques that can assist in improving the performances of the system and which simultaneously enhance the flexibility of the control strategy. Here, two such methods, fuzzy logic and evolutionary algorithms, are considered. Emerging from new requirements for gas turbine engine control, a flexible gain scheduler is developed and analysed. A hierarchical multiobjective genetic algorithm is developed to perform search and optimisation of the candidate fuzzy scheduling solutions.","PeriodicalId":405648,"journal":{"name":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2000.854104","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
This paper investigates the use of a nonconventional approach to the control of a gas turbine aeroengine. The rationale behind this study is the need to develop advanced tools and techniques that can assist in improving the performances of the system and which simultaneously enhance the flexibility of the control strategy. Here, two such methods, fuzzy logic and evolutionary algorithms, are considered. Emerging from new requirements for gas turbine engine control, a flexible gain scheduler is developed and analysed. A hierarchical multiobjective genetic algorithm is developed to perform search and optimisation of the candidate fuzzy scheduling solutions.
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