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
1.0462995e+01 1.0477171e+01 8.0627999e+01
1.0913211e+01 1.0913530e+01 8.1223090e+01
1.1351567e+01 1.1311203e+01 8.1786813e+01
1.1778985e+01 1.1672315e+01 8.2320707e+01
1.2196385e+01 1.1998990e+01 8.2826314e+01
1.2604688e+01 1.2293355e+01 8.3305172e+01
1.3004814e+01 1.2557533e+01 8.3758822e+01
1.3397683e+01 1.2793650e+01 8.4188804e+01
1.3784217e+01 1.3003830e+01 8.4596657e+01
1.4165336e+01 1.3190200e+01 8.4983922e+01
1.4541961e+01 1.3354883e+01 8.5352138e+01
1.4915011e+01 1.3500005e+01 8.5702846e+01
1.5285408e+01 1.3627691e+01 8.6037585e+01
1.5654072e+01 1.3740065e+01 8.6357896e+01
1.6021924e+01 1.3839254e+01 8.6665318e+01
1.6389884e+01 1.3927381e+01 8.6961391e+01
1.6758873e+01 1.4006571e+01 8.7247655e+01
1.7129811e+01 1.4078951e+01 8.7525651e+01
1.7503620e+01 1.4146645e+01 8.7796918e+01
1.7881219e+01 1.4211777e+01 8.8062996e+01
1.8263529e+01 1.4276473e+01 8.8325424e+01
1.8651471e+01 1.4342857e+01 8.8585744e+01
1.9045965e+01 1.4413056e+01 8.8845495e+01
1.9447932e+01 1.4489193e+01 8.9106216e+01
1.9858292e+01 1.4573394e+01 8.9369449e+01
2.0277966e+01 1.4667784e+01 8.9636732e+01
2.0707875e+01 1.4774488e+01 8.9909606e+01
2.1148938e+01 1.4895630e+01 9.0189611e+01
2.1602078e+01 1.5033337e+01 9.0478286e+01
2.2068214e+01 1.5189732e+01 9.0777172e+01
2.2548266e+01 1.5366940e+01 9.1087808e+01
2.3043156e+01 1.5567088e+01 9.1411735e+01
2.3553803e+01 1.5792299e+01 9.1750492e+01
2.4081129e+01 1.6044700e+01 9.2105620e+01
2.4626055e+01 1.6326414e+01 9.2478658e+01
2.5189499e+01 1.6639566e+01 9.2871146e+01
2.5772384e+01 1.6986283e+01 9.3284624e+01
2.6375630e+01 1.7368688e+01 9.3720633e+01
2.7000157e+01 1.7788907e+01 9.4180712e+01
2.7646886e+01 1.8249065e+01 9.4666400e+01
2.8316737e+01 1.8751287e+01 9.5179239e+01
2.9010632e+01 1.9297698e+01 9.5720768e+01
2.9729489e+01 1.9890422e+01 9.6292527e+01
3.0474231e+01 2.0531585e+01 9.6896056e+01
3.1245778e+01 2.1223312e+01 9.7532894e+01
3.2045050e+01 2.1967728e+01 9.8204583e+01
3.2872968e+01 2.2766958e+01 9.8912661e+01
3.3730452e+01 2.3623126e+01 9.9658668e+01
3.4618423e+01 2.4538358e+01 1.0044415e+02
3.5537802e+01 2.5514779e+01 1.0127063e+02
3.6489509e+01 2.6554514e+01 1.0213967e+02
3.7474464e+01 2.7659688e+01 1.0305279e+02
3.8493589e+01 2.8832425e+01 1.0401155e+02
3.9547803e+01 3.0074851e+01 1.0501748e+02
4.0638028e+01 3.1389092e+01 1.0607211e+02
4.1765184e+01 3.2777270e+01 1.0717699e+02
4.2930191e+01 3.4241513e+01 1.0833367e+02
4.4133970e+01 3.5783945e+01 1.0954367e+02
4.5377442e+01 3.7406690e+01 1.1080854e+02
4.6661527e+01 3.9111874e+01 1.1212982e+02
4.7987146e+01 4.0901622e+01 1.1350905e+02
4.9355219e+01 4.2778059e+01 1.1494777e+02
5.0766667e+01 4.4743310e+01 1.1644751e+02
5.2222410e+01 4.6799499e+01 1.1800983e+02
5.3723370e+01 4.8948752e+01 1.1963625e+02
5.5270466e+01 5.1193194e+01 1.2132833e+02
5.6864619e+01 5.3534950e+01 1.2308759e+02
5.8506750e+01 5.5976145e+01 1.2491558e+02
6.0197779e+01 5.8518904e+01 1.2681384e+02
6.1938627e+01 6.1165351e+01 1.2878391e+02
6.3730214e+01 6.3917612e+01 1.3082732e+02
6.5573462e+01 6.6777812e+01 1.3294563e+02
6.7469290e+01 6.9748076e+01 1.3514036e+02
6.9418619e+01 7.2830529e+01 1.3741307e+02
7.1422369e+01 7.6027295e+01 1.3976528e+02
7.3481462e+01 7.9340501e+01 1.4219853e+02
7.5596818e+01 8.2772270e+01 1.4471438e+02
7.7769357e+01 8.6324728e+01 1.4731436e+02
8.0000000e+01 9.0000000e+01 1.5000000e+02四、完整MATLAB代码
