Optimization Design of Multi-Objective Aerodynamic Shape of a Intercepting UAV

Using drones to intercepting drones is an effective and affordable means of countering UAVs. In this paper, for a canard interceptor UAV, the Reynolds-averaged N-S equation (RANS) is used to calculate the flow field, and the Kriging surrogate model and the decomposition-based multi-objective evolutionary algorithm (MOEA/D) are used to carry out the aerodynamic shape optimization design. In the optimization work, the range and the maximum available overload are taken as the design goals, the longitudinal position of the canard, the twist angle of the main wing, the aspect ratio and the sweep angle are taken as the design variables, and the static stability and the maximum deflection angle of the canard are constrained, and the cost is relatively high. Less computing resources get a uniformly distributed Pareto front, and the optimized range and maximum available overload of the unmanned aerial vehicle have increased by 24.6% and 6.4% respectively compared to the benchmark shape, proving the effectiveness of this optimization method