Meta-heuristic approach for the conceptual design and optimization of multistage interceptor

The design of a missile system capable of intercepting fast moving target(s) is a complex problem that must balance competing objectives and constraints. It involves teams of specialists working separately in their specialized design domains (such as propulsion, aerodynamics, guidance etc), but are also coordinated through a system level set of design requirements such as physical size or weight. This type of segmented design process requires rigorous iterations to ensure that the missile sub-systems are compatible with each other while still meeting the mission specifications. Therefore the need arises for a Multidisciplinary Design Optimization (MDO) approach that can control the design domains concurrently and configure an optimum design within the set design limits and constraints. Recently the authors have considered the design of ground-launched and air-launched configurations for short range endo-atmospheric interceptors using evolutionary optimization techniques but still the potential of using meta-heuristic search algorithms like Simulated Annealing (SA) for the MDO of a multistage long range exo-atmospheric interceptor have not yet been gauged. In this paper we propose a conceptual design and optimization strategy using Genetic Algorithm (GA) cascaded with Simulated Annealing (SA), for the design of a multistage ground based Interceptor comprised of a three stage solid propulsion system for an exo-atmospheric boost phase intercept. The elite solution from GA is passed on to SA as initial guess. Search Space Reduction (SSR) is used to enhance the convergence of the Hybrid Meta-Heuristic Search Algorithm (HMSA). The SSR is applied on the optimal solution from GA, the upper and lower bounds for SA are then reset based upon the optimal solution from GA. The mission of the Ground Based Interceptor is to deliver the Kinetic Kill Vehicle (KKV) to an optimal position in space to allow it to complete the intercept. The modules for propulsion characteristics, aerodynamics, mass properties and flight dynamics have been integrated to produce a high fidelity model of the entire vehicle. The Propulsion module is comprised of sub-modules of Solid Rocket Motor (SRM) design, nozzle geometry and performance prediction analysis. Internal ballistics and performance prediction parameters have been calculated using a lumped parameter method. For the present effort, the design objective is to minimize the Gross Lift Off Mass (GLOM) (kg) of the interceptor under the mission constraints of miss distance (m), intercept time (sec), lateral divert (m/sec), velocity at intercept (km/sec), g-loads and stage configuration requirements. SRM envelope constraints comprised length to diameter ratios, nozzle expansion ratios, propellant burn rates and grain geometry constraints such as web fraction, volumetric loading efficiency, etc. Interceptor conceptual design problem was posed to optimizer and it successfully solved these under the given conditions and constraints and satisfied the Interceptor trajectory/ performance objectives. The proposed meta-heuristic design and optimization methodology coupled with the SSR provides the designer with a computationally efficient and powerful approach for the design of interceptor systems.