MULTI-OBJECTIVE OPTIMIZATION OF A STEALTH UNMANNED COMBAT AERIAL VEHICLE

Abstract

For Unmanned Combat Aerial Vehicles (UCAVs) operating during wartime, the mission objective is dependent on the survivability of the UCAV, which depends on two things: 1. Its ability to evade detection by enemy radars and scanners (Stealth) 2. Its ability to evade enemy fire when detected and fired upon. (Maneuverability). This project entails the optimization of an Unmanned Combat Aerial Vehicle with maximized survivability to be used in conceptual phase of Aircraft Design. This shall be accomplished by means of a Multi-Objective Optimization, employing the Genetic Algorithm, with the objective functions being the Radar Cross Section (RCS) – which is to be minimized, and the Lift-to-Drag Ratio which signifies the Aerodynamic performance – which is to be maximized. Genetic Algorithm for Multi-Objective Optimization from MATLAB Optimization Toolbox is used. To minimize computational expense in the conceptual design phase, low fidelity methods for Lift to Drag Ratio and RCS calculations are used; Vortex Lattice Method (VLM) and Physical Optics (PO), respectively.