Multidisciplinary robust design and optimization of multistage boost phase interceptor

This paper presents Robust Design Method (RDM) for the conceptual design of a multistage boost phase interceptor to obtain an optimum system configuration insensitive to uncertainties in the form of design variable variations. 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. RDM is implemented using First Order Orthogonal Design Matrix (FOODM) to calculate the worst-case variation which is then utilized to evaluate the mean and variance of a system output. Latin Hypercube Sampling (LHS) is used for its good space filling properties to extract maximum useful information about 'mean' of quality function. The performance of Robust Design is compared with the Optimal Design. Genetic Algorithm (GA) is used as optimizer to search the design space for optimal and robust solution. Real/exact simulation analyses are used instead of surrogate models. To compare the robustness of the solutions obtained, a sensitivity analysis is performed using Monte Carlo simulation runs. The results indicate that the proposed method can find a robust configuration without compromising the performance objectives and design constraints.