{"title":"基于群智能优化和高度能量剖面的再入制导分析框架","authors":"Hui XU , Guangbin CAI , Chaoxu MU , Xin LI","doi":"10.1016/j.cja.2023.07.029","DOIUrl":null,"url":null,"abstract":"<div><p>Aimed at improving the real-time performance of guidance instruction generation, an analytical hypersonic reentry guidance framework is presented. The key steps of the novel guidance framework are the parameterization of reentry guidance problems and the optimization of parameters. First, a quintic polynomial function of energy was designed to describe the altitude profile. Then, according to the altitude-energy profile, the altitude, velocity, flight path angle, and bank angle were obtained analytically, which naturally met the terminal constraints. In addition, the angle of the attack profile was determined using the velocity parameter. The swarm intelligent optimization algorithms were used to optimize the parameters. The path constraints were enforced by the penalty function method. Finally, extensive simulations were carried out in both nominal and dispersed cases, and the simulation results showed that the proposed guidance framework was effective, high-precision, and robust in different scenarios.</p></div>","PeriodicalId":55631,"journal":{"name":"Chinese Journal of Aeronautics","volume":"36 12","pages":"Pages 336-348"},"PeriodicalIF":5.3000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1000936123002650/pdfft?md5=f04f8d07e70cea44278e0c5ac6b14ead&pid=1-s2.0-S1000936123002650-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Analytical reentry guidance framework based on swarm intelligence optimization and altitude-energy profile\",\"authors\":\"Hui XU , Guangbin CAI , Chaoxu MU , Xin LI\",\"doi\":\"10.1016/j.cja.2023.07.029\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Aimed at improving the real-time performance of guidance instruction generation, an analytical hypersonic reentry guidance framework is presented. The key steps of the novel guidance framework are the parameterization of reentry guidance problems and the optimization of parameters. First, a quintic polynomial function of energy was designed to describe the altitude profile. Then, according to the altitude-energy profile, the altitude, velocity, flight path angle, and bank angle were obtained analytically, which naturally met the terminal constraints. In addition, the angle of the attack profile was determined using the velocity parameter. The swarm intelligent optimization algorithms were used to optimize the parameters. The path constraints were enforced by the penalty function method. Finally, extensive simulations were carried out in both nominal and dispersed cases, and the simulation results showed that the proposed guidance framework was effective, high-precision, and robust in different scenarios.</p></div>\",\"PeriodicalId\":55631,\"journal\":{\"name\":\"Chinese Journal of Aeronautics\",\"volume\":\"36 12\",\"pages\":\"Pages 336-348\"},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1000936123002650/pdfft?md5=f04f8d07e70cea44278e0c5ac6b14ead&pid=1-s2.0-S1000936123002650-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chinese Journal of Aeronautics\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1000936123002650\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, AEROSPACE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chinese Journal of Aeronautics","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1000936123002650","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
Analytical reentry guidance framework based on swarm intelligence optimization and altitude-energy profile
Aimed at improving the real-time performance of guidance instruction generation, an analytical hypersonic reentry guidance framework is presented. The key steps of the novel guidance framework are the parameterization of reentry guidance problems and the optimization of parameters. First, a quintic polynomial function of energy was designed to describe the altitude profile. Then, according to the altitude-energy profile, the altitude, velocity, flight path angle, and bank angle were obtained analytically, which naturally met the terminal constraints. In addition, the angle of the attack profile was determined using the velocity parameter. The swarm intelligent optimization algorithms were used to optimize the parameters. The path constraints were enforced by the penalty function method. Finally, extensive simulations were carried out in both nominal and dispersed cases, and the simulation results showed that the proposed guidance framework was effective, high-precision, and robust in different scenarios.
期刊介绍:
Chinese Journal of Aeronautics (CJA) is an open access, peer-reviewed international journal covering all aspects of aerospace engineering. The Journal reports the scientific and technological achievements and frontiers in aeronautic engineering and astronautic engineering, in both theory and practice, such as theoretical research articles, experiment ones, research notes, comprehensive reviews, technological briefs and other reports on the latest developments and everything related to the fields of aeronautics and astronautics, as well as those ground equipment concerned.