Support Vector Machine Based Trajectory Metamodel for Conceptual Design of Multi-stage Space Launch Vehicle

Abstract

AbstractThe design of new Space Launch Vehicle (SLV) involves a full set of disciplines – propulsion, structural sizing, aerodynamics, mission analysis, flight control, stages layout – with strong interaction between each other. Since multidisciplinary design optimization of multistage launch vehicles is a complex and computationally expensive. An efficient Least Square Support Vector Regression (LS-SVR) technique is used for trajectory simulation of multistage space launch vehicle. This newly formulation problem-about 17 parameters, linked to both the architecture and the command (trajectory optimization), 8 constraints – is solved through hybrid optimization algorithm using Particle Swarm Optimization (PSO) as global optimizer and Sequential Quadratic Programming (SQP) as local optimizer starting from the solution given by (PSO). The objective is to find minimum gross launch weight (GLW) and optimal trajectory during launch maneuvering phase for liquid fueled space launch vehicle (SLV).The computational cost incurred is compared for two cases of conceptual design involving exact trajectory simulation and with Least Square Support Vector Regression based trajectory simulation.KeywordsSupport Vector MachineParticle Swarm OptimizationConceptual DesignSupport Vector RegressionLittle Square Support Vector MachineThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.