13_粒子群

  航迹规划是无人机执行侦察和作战任务中的关键技术，规划算法的性能直接影响着航迹规划的质量。针对航迹规划最优性和实时性问题，提出一种惯性权值" 阶梯式" 调整策略与跳出局部最优解策略相结合的改进粒子群无人机航迹规划算法。(Route planning is the key technology for UAV to perform reconnaissance and combat tasks, and the performance of planning algorithm directly affects the quality of route planning. Aiming at the optimization and real-time performance of trajectory planning, an improved particle swarm optimization (UAV) trajectory planning algorithm is proposed, which combines the inertia weight "ladder" adjustment strategy with the strategy of jumping out of the local optimal solution.)

13_粒子群
13_粒子群\sample1
13_粒子群\sample1\MexicoHatnew.m
13_粒子群\sample1\PSO0.m
13_粒子群\sample1\PSO1.m
13_粒子群\sample1\PSO2.m
13_粒子群\sample1\PSO3.m
13_粒子群\sample1\PSO4.m
13_粒子群\sample1\fun.m
13_粒子群\sample1\main.m
13_粒子群\sample1\wchange.m
13_粒子群\sample2-Rastrgrin
13_粒子群\sample2-Rastrgrin\PSO.m
13_粒子群\sample2-Rastrgrin\fun.m
13_粒子群\sample2-Rastrgrin\pso.fig
13_粒子群\sample2-Rastrgrin\pso.mat
13_粒子群\sample2-Rastrgrin\rastrigrin.fig
13_粒子群\sample2-Rastrgrin\rastrigrin.m
13_粒子群\sample3-Griewankan
13_粒子群\sample3-Griewankan\Griewank.fig
13_粒子群\sample3-Griewankan\Griewank.m
13_粒子群\sample3-Griewankan\PSO.m
13_粒子群\sample3-Griewankan\fun.m
13_粒子群\sample3-Griewankan\pso.fig
13_粒子群\sample3-Griewankan\pso.mat