基于粒子群算法的不同推力条件下运载火箭上升段轨迹优化

M. Dileep, Surekha Kamath, Vishnu G. Nair
{"title":"基于粒子群算法的不同推力条件下运载火箭上升段轨迹优化","authors":"M. Dileep, Surekha Kamath, Vishnu G. Nair","doi":"10.15866/IREASE.V9I6.10521","DOIUrl":null,"url":null,"abstract":"Launch vehicle trajectory optimization has gained enormous significance in the recent past. Constraints handling and accuracy of launch vehicle system, are challenging factors, \non account of their high degree of non-linearity. This paper brings in the application of thetaparticle \nswarm optimization (TH-PSO), which is a recently emerged variant of particle swarm optimization (PSO), for launch vehicle trajectory optimization, which can efficiently handle the constraints and drive the system towards optimality. TH–PSO approach is implemented on a \nmultistage liquid propellant rocket, taking angle of attack as the control parameter. Single and dual thrust cases were solved using TH-PSO technique, and a comparative study was made with classical PSO in terms of terminal error, IE consistency of solutions. Based on the statistics, it can \nbe confirmed that in both single and dual thrust cases TH-PSO outperformed, classical PSO. Copyright © 2016 Praise Worthy Prize S.r.l. - All rights reserved","PeriodicalId":14462,"journal":{"name":"International Review of Aerospace Engineering","volume":"1 1","pages":"200-207"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Ascent Phase Trajectory Optimization of Launch Vehicle Using Theta-Particle Swarm Optimization with Different Thrust Scenarios\",\"authors\":\"M. Dileep, Surekha Kamath, Vishnu G. Nair\",\"doi\":\"10.15866/IREASE.V9I6.10521\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Launch vehicle trajectory optimization has gained enormous significance in the recent past. Constraints handling and accuracy of launch vehicle system, are challenging factors, \\non account of their high degree of non-linearity. This paper brings in the application of thetaparticle \\nswarm optimization (TH-PSO), which is a recently emerged variant of particle swarm optimization (PSO), for launch vehicle trajectory optimization, which can efficiently handle the constraints and drive the system towards optimality. TH–PSO approach is implemented on a \\nmultistage liquid propellant rocket, taking angle of attack as the control parameter. Single and dual thrust cases were solved using TH-PSO technique, and a comparative study was made with classical PSO in terms of terminal error, IE consistency of solutions. Based on the statistics, it can \\nbe confirmed that in both single and dual thrust cases TH-PSO outperformed, classical PSO. Copyright © 2016 Praise Worthy Prize S.r.l. - All rights reserved\",\"PeriodicalId\":14462,\"journal\":{\"name\":\"International Review of Aerospace Engineering\",\"volume\":\"1 1\",\"pages\":\"200-207\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Review of Aerospace Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15866/IREASE.V9I6.10521\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Aerospace Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15866/IREASE.V9I6.10521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

运载火箭轨道优化在近年来具有重要的意义。由于运载火箭系统的高度非线性,约束处理和精度是具有挑战性的因素。本文将粒子群算法(TH-PSO)应用于运载火箭轨道优化,该算法是粒子群算法(PSO)的一种新变体,能够有效地处理约束条件,推动系统向最优方向发展。以攻角为控制参数,在某多级液体火箭上实现了TH-PSO方法。采用TH-PSO方法求解单推力和双推力情况,并与经典PSO方法在解的终端误差、IE一致性等方面进行了比较研究。通过统计可以证实,在单推力和双推力情况下,TH-PSO的性能都优于经典PSO。版权所有©2016 Praise Worthy Prize S.r.l -版权所有
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ascent Phase Trajectory Optimization of Launch Vehicle Using Theta-Particle Swarm Optimization with Different Thrust Scenarios
Launch vehicle trajectory optimization has gained enormous significance in the recent past. Constraints handling and accuracy of launch vehicle system, are challenging factors, on account of their high degree of non-linearity. This paper brings in the application of thetaparticle swarm optimization (TH-PSO), which is a recently emerged variant of particle swarm optimization (PSO), for launch vehicle trajectory optimization, which can efficiently handle the constraints and drive the system towards optimality. TH–PSO approach is implemented on a multistage liquid propellant rocket, taking angle of attack as the control parameter. Single and dual thrust cases were solved using TH-PSO technique, and a comparative study was made with classical PSO in terms of terminal error, IE consistency of solutions. Based on the statistics, it can be confirmed that in both single and dual thrust cases TH-PSO outperformed, classical PSO. Copyright © 2016 Praise Worthy Prize S.r.l. - All rights reserved
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信