{"title":"燃气轮机航空发动机系统模糊增益调度:多目标方法","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":"{\"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}","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}
Towards fuzzy gain scheduling for gas turbine aero-engine systems: a multiobjective approach
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.