Support Vector Regression-Driven Multidisciplinary Design Optimization of a Multistage Ground Based Interceptor

In this paper we propose meta-model based design and optimization strategy for multistage ground based interceptor comprising of three stage solid propulsion system for an exo-atmospheric boost phase intercept. An efficient Least Square Support Vector Regression technique is used to approximate the current problem. The mission of Ground Based Interceptor is to deliver Kinetic Kill Vehicle to an optimal position in space to allow it to complete the intercept. The modules for propulsion characteristics, mass properties and flight dynamics have been integrated to produce a high fidelity model of the entire vehicle. For the present effort, the design objective is to minimize the Gross Lift off Mass of the ground based interceptor under the mission constraints of miss distance, intercept time, lateral divert, velocity at intercept, g-loads and stage configuration requirements as Solid Rocket Motor envelope constraints which comprise of length to diameter ratios, nozzle expansion ratios, propellant burn rates and grain geometry constraints like web fraction, volumetric loading efficiency etc. Though, the optimization results and performance are to be considered as preliminary (proof-of-concept) only, but they can be compared to existing systems and used for conceptual design of ground based interceptors. The proposed design and optimization methodology provides the designer with a time efficient and powerful approach for the design of interceptor systems.