一、无人机模型简介：
单个无人机三维路径规划问题及其建模_IT猿手的博客-CSDN博客
参考文献：
[1]胡观凯,钟建华,李永正,黎万洪.基于IPSO-GA算法的无人机三维路径规划[J].现代电子技术,2023,46(07):115-120
二、Tiki-taka算法（TTA）简介
极致攻守算法（Tiki-Taka Algorithm，TTA）由Mohd Fadzil Faisae Ab. Rashid于2020年提出，该算法受tiki-taka 足球风格的短传、球员定位和保持控球的特点所启发。其旨在控制控球权并利用其战术优势击败对手，TTA算法新颖高效。单目标应用：Tiki-taka算法（TTA）求解太阳能光伏模型MATLAB_IT猿手的博客-CSDN博客
参考文献：
[1]Ab. Rashid, M.F.F. (2021), "Tiki-taka algorithm: a novel metaheuristic inspired by football playing style", Engineering Computations, Vol. 38 No. 1, pp. 313-343. Tiki-taka algorithm: a novel metaheuristic inspired by football playing style | Emerald Insight
[2]Zamli, Kamal Z , Kader, et al. Selective chaotic maps Tiki-Taka algorithm for the S-box generation and optimization.
三、TTA求解无人机路径规划
（1）部分代码
close all
clear
clc
addpath('./Algorithm/')%添加算法路径
warning off;
%% 三维路径规划模型定义
global startPos goalPos N
N=2;%待优化点的个数(可以修改)
startPos = [10, 10, 80]; %起点(可以修改)
goalPos = [80, 90, 150]; %终点(可以修改)
SearchAgents_no=30; % 种群大小(可以修改)
Function_name='F2'; %F1:随机产生地图 F2：导入固定地图
Max_iteration=50; %最大迭代次数(可以修改)
% Load details of the selected benchmark function
[lb,ub,dim,fobj]=Get_Functions_details(Function_name);
[Best_score,Best_pos,curve]=TTA(SearchAgents_no,Max_iteration,lb,ub,dim,fobj);%算法优化求解
AlgorithmName='TTA';%算法名字
figure
semilogy(curve,'Color','g','linewidth',3)
xlabel('迭代次数');
ylabel('飞行路径长度');
legend(AlgorithmName)
display(['算法得到的最优适应度: ', num2str(Best_score)]);
Position=[Best_pos(1:dim/3); Best_pos(1+dim/3:2*(dim/3)); Best_pos(1+(2*dim/3):end)]'; %优化点的XYZ坐标（每一行是一个点）
plotFigure(Best_pos,AlgorithmName)%画最优路径
（2）部分结果
无人机飞行路径坐标：
1.0000000e+01 1.0000000e+01 8.0000000e+01 1.0299938e+01 1.0779412e+01 8.0346200e+01 1.0579515e+01 1.1471367e+01 8.0675710e+01 1.0840111e+01 1.2079507e+01 8.0989721e+01 1.1083104e+01 1.2607472e+01 8.1289422e+01 1.1309872e+01 1.3058901e+01 8.1576002e+01 1.1521796e+01 1.3437437e+01 8.1850652e+01 1.1720253e+01 1.3746718e+01 8.2114560e+01 1.1906623e+01 1.3990386e+01 8.2368916e+01 1.2082284e+01 1.4172080e+01 8.2614911e+01 1.2248615e+01 1.4295441e+01 8.2853732e+01 1.2406994e+01 1.4364110e+01 8.3086571e+01 1.2558802e+01 1.4381727e+01 8.3314616e+01 1.2705416e+01 1.4351932e+01 8.3539058e+01 1.2848215e+01 1.4278366e+01 8.3761084e+01 1.2988579e+01 1.4164668e+01 8.3981887e+01 1.3127885e+01 1.4014481e+01 8.4202653e+01 1.3267514e+01 1.3831443e+01 8.4424574e+01 1.3408842e+01 1.3619195e+01 8.4648840e+01 1.3553251e+01 1.3381378e+01 8.4876638e+01 1.3702117e+01 1.3121632e+01 8.5109159e+01 1.3856821e+01 1.2843597e+01 8.5347594e+01 1.4018740e+01 1.2550914e+01 8.5593130e+01 1.4189255e+01 1.2247224e+01 8.5846958e+01 1.4369742e+01 1.1936166e+01 8.6110267e+01 1.4561582e+01 1.1621380e+01 8.6384247e+01 1.4766154e+01 1.1306509e+01 8.6670087e+01 1.4984835e+01 1.0995191e+01 8.6968977e+01 1.5219005e+01 1.0691067e+01 8.7282107e+01 1.5470042e+01 1.0397778e+01 8.7610666e+01 1.5739326e+01 1.0118963e+01 8.7955843e+01 1.6028235e+01 9.8582641e+00 8.8318829e+01 1.6338149e+01 9.6193207e+00 8.8700812e+01 1.6670445e+01 9.4057735e+00 8.9102983e+01 1.7026503e+01 9.2212627e+00 8.9526531e+01 1.7407701e+01 9.0694289e+00 8.9972645e+01 1.7815419e+01 8.9539123e+00 9.0442515e+01 1.8251035e+01 8.8783534e+00 9.0937331e+01 1.8715927e+01 8.8463925e+00 9.1458281e+01 1.9211476e+01 8.8616701e+00 9.2006557e+01 1.9739059e+01 8.9278266e+00 9.2583347e+01 2.0300056e+01 9.0485023e+00 9.3189840e+01 2.0895845e+01 9.2273376e+00 9.3827227e+01 2.1527805e+01 9.4679729e+00 9.4496697e+01 2.2197315e+01 9.7740487e+00 9.5199439e+01 2.2905753e+01 1.0149205e+01 9.5936644e+01 2.3654499e+01 1.0597083e+01 9.6709500e+01 2.4444932e+01 1.1121322e+01 9.7519197e+01 2.5278429e+01 1.1725564e+01 9.8366925e+01 2.6156371e+01 1.2413447e+01 9.9253873e+01 2.7080135e+01 1.3188614e+01 1.0018123e+02 2.8051101e+01 1.4054703e+01 1.0115019e+02 2.9070647e+01 1.5015356e+01 1.0216194e+02 3.0140153e+01 1.6074213e+01 1.0321766e+02 3.1260996e+01 1.7234915e+01 1.0431855e+02 3.2434557e+01 1.8501101e+01 1.0546581e+02 3.3662213e+01 1.9876412e+01 1.0666060e+02 3.4945344e+01 2.1364489e+01 1.0790414e+02 3.6285328e+01 2.2968971e+01 1.0919760e+02 3.7683544e+01 2.4693500e+01 1.1054218e+02 3.9141371e+01 2.6541716e+01 1.1193906e+02 4.0660188e+01 2.8517258e+01 1.1338944e+02 4.2241374e+01 3.0623769e+01 1.1489450e+02 4.3886307e+01 3.2864886e+01 1.1645544e+02 4.5596366e+01 3.5244253e+01 1.1807344e+02 4.7372930e+01 3.7765507e+01 1.1974969e+02 4.9217378e+01 4.0432291e+01 1.2148539e+02 5.1131089e+01 4.3248244e+01 1.2328172e+02 5.3115442e+01 4.6217007e+01 1.2513987e+02 5.5171814e+01 4.9342221e+01 1.2706103e+02 5.7301586e+01 5.2627525e+01 1.2904640e+02 5.9506136e+01 5.6076559e+01 1.3109715e+02 6.1786843e+01 5.9692966e+01 1.3321449e+02 6.4145085e+01 6.3480383e+01 1.3539959e+02 6.6582242e+01 6.7442454e+01 1.3765365e+02 6.9099692e+01 7.1582816e+01 1.3997787e+02 7.1698814e+01 7.5905112e+01 1.4237342e+02 7.4380986e+01 8.0412981e+01 1.4484150e+02 7.7147589e+01 8.5110063e+01 1.4738330e+02 8.0000000e+01 9.0000000e+01 1.5000000e+02
四、完整MATLAB代码
