{"title":"基于粒子群优化的自动着陆控制","authors":"J. Juang, B. Lin, Kuo-Chih Chin","doi":"10.1109/ICMECH.2005.1529350","DOIUrl":null,"url":null,"abstract":"This paper proposes an intelligent aircraft automatic landing controller that uses fuzzy-neural controller with particle swarm optimization to improve the performance of conventional automatic landing system. Control gains are selected by a parameter searching method called particle swarm theory. Comparisons on different control schemes are given. Simulation results show that the proposed automatic landing controller can successfully expand the safety envelope of an aircraft to include severe wind disturbance environments without using the conventional gain scheduling technique.","PeriodicalId":175701,"journal":{"name":"IEEE International Conference on Mechatronics, 2005. ICM '05.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Automatic landing control using particle swarm optimization\",\"authors\":\"J. Juang, B. Lin, Kuo-Chih Chin\",\"doi\":\"10.1109/ICMECH.2005.1529350\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an intelligent aircraft automatic landing controller that uses fuzzy-neural controller with particle swarm optimization to improve the performance of conventional automatic landing system. Control gains are selected by a parameter searching method called particle swarm theory. Comparisons on different control schemes are given. Simulation results show that the proposed automatic landing controller can successfully expand the safety envelope of an aircraft to include severe wind disturbance environments without using the conventional gain scheduling technique.\",\"PeriodicalId\":175701,\"journal\":{\"name\":\"IEEE International Conference on Mechatronics, 2005. ICM '05.\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Mechatronics, 2005. ICM '05.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMECH.2005.1529350\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Mechatronics, 2005. ICM '05.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMECH.2005.1529350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic landing control using particle swarm optimization
This paper proposes an intelligent aircraft automatic landing controller that uses fuzzy-neural controller with particle swarm optimization to improve the performance of conventional automatic landing system. Control gains are selected by a parameter searching method called particle swarm theory. Comparisons on different control schemes are given. Simulation results show that the proposed automatic landing controller can successfully expand the safety envelope of an aircraft to include severe wind disturbance environments without using the conventional gain scheduling technique.