{"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}
引用次数: 1
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
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
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