SURFACE-TO-AIR MISSILE PATH PLANNING USING GENETIC AND PSO ALGORITHMS

摘要

Optimization algorithms use various mathematical and logical methods to find optimal points. Given the complexity of models and design levels, this paper proposes a heuristic optimization model for surface-to-air missile path planning in order to achieve the maximum range and optimal height based on 3DOF simulation. The proposed optimization model involves design variables based on the pitch programming and initial pitch angle (boost angle). In this optimization model, we used genetic and particle swarm optimization (PSO) algorithms. Simulation results indicated that the genetic algorithm was closer to reality but took longer computation time. PSO algorithm offered acceptable results and shorter computation time, so it was found to be more efficient in the surface-to-air missile path planning.