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：
1Ab. 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
2Zamli, 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
1.0564074e+01 1.0627730e+01 8.0798930e+01
1.1087311e+01 1.1173012e+01 8.1542587e+01
1.1571621e+01 1.1639444e+01 8.2233212e+01
1.2018920e+01 1.2030621e+01 8.2873045e+01
1.2431118e+01 1.2350141e+01 8.3464328e+01
1.2810129e+01 1.2601600e+01 8.4009300e+01
1.3157866e+01 1.2788595e+01 8.4510202e+01
1.3476242e+01 1.2914723e+01 8.4969274e+01
1.3767169e+01 1.2983581e+01 8.5388758e+01
1.4032560e+01 1.2998766e+01 8.5770893e+01
1.4274328e+01 1.2963874e+01 8.6117921e+01
1.4494385e+01 1.2882502e+01 8.6432081e+01
1.4694645e+01 1.2758247e+01 8.6715614e+01
1.4877020e+01 1.2594706e+01 8.6970762e+01
1.5043423e+01 1.2395476e+01 8.7199763e+01
1.5195767e+01 1.2164153e+01 8.7404860e+01
1.5335964e+01 1.1904333e+01 8.7588292e+01
1.5465927e+01 1.1619615e+01 8.7752300e+01
1.5587570e+01 1.1313595e+01 8.7899124e+01
1.5702804e+01 1.0989869e+01 8.8031006e+01
1.5813543e+01 1.0652034e+01 8.8150185e+01
1.5921699e+01 1.0303688e+01 8.8258902e+01
1.6029186e+01 9.9484265e+00 8.8359398e+01
1.6137915e+01 9.5898466e+00 8.8453913e+01
1.6249800e+01 9.2315453e+00 8.8544688e+01
1.6366754e+01 8.8771192e+00 8.8633963e+01
1.6490689e+01 8.5301653e+00 8.8723979e+01
1.6623518e+01 8.1942802e+00 8.8816977e+01
1.6767153e+01 7.8730608e+00 8.8915196e+01
1.6923509e+01 7.5701039e+00 8.9020877e+01
1.7094497e+01 7.2890062e+00 8.9136262e+01
1.7282029e+01 7.0333646e+00 8.9263590e+01
1.7488020e+01 6.8067759e+00 8.9405102e+01
1.7714382e+01 6.6128368e+00 8.9563039e+01
1.7963027e+01 6.4551442e+00 8.9739641e+01
1.8235868e+01 6.3372948e+00 8.9937149e+01
1.8534818e+01 6.2628854e+00 9.0157803e+01
1.8861790e+01 6.2355129e+00 9.0403843e+01
1.9218697e+01 6.2587740e+00 9.0677511e+01
1.9607451e+01 6.3362656e+00 9.0981047e+01
2.0029965e+01 6.4715843e+00 9.1316691e+01
2.0488152e+01 6.6683271e+00 9.1686684e+01
2.0983925e+01 6.9300906e+00 9.2093266e+01
2.1519196e+01 7.2604718e+00 9.2538679e+01
2.2095879e+01 7.6630674e+00 9.3025162e+01
2.2715885e+01 8.1414742e+00 9.3554956e+01
2.3381129e+01 8.6992889e+00 9.4130302e+01
2.4093522e+01 9.3401084e+00 9.4753439e+01
2.4854977e+01 1.0067530e+01 9.5426610e+01
2.5667407e+01 1.0885149e+01 9.6152054e+01
2.6532726e+01 1.1796564e+01 9.6932011e+01
2.7452845e+01 1.2805370e+01 9.7768723e+01
2.8429677e+01 1.3915166e+01 9.8664430e+01
2.9465136e+01 1.5129547e+01 9.9621372e+01
3.0561133e+01 1.6452110e+01 1.0064179e+02
3.1719583e+01 1.7886452e+01 1.0172792e+02
3.2942397e+01 1.9436171e+01 1.0288202e+02
3.4231488e+01 2.1104862e+01 1.0410630e+02
3.5588770e+01 2.2896122e+01 1.0540303e+02
3.7016154e+01 2.4813549e+01 1.0677444e+02
3.8515554e+01 2.6860739e+01 1.0822276e+02
4.0088883e+01 2.9041289e+01 1.0975025e+02
4.1738052e+01 3.1358796e+01 1.1135913e+02
4.3464976e+01 3.3816856e+01 1.1305166e+02
4.5271567e+01 3.6419067e+01 1.1483006e+02
4.7159737e+01 3.9169024e+01 1.1669659e+02
4.9131399e+01 4.2070326e+01 1.1865348e+02
5.1188466e+01 4.5126568e+01 1.2070298e+02
5.3332852e+01 4.8341348e+01 1.2284732e+02
5.5566468e+01 5.1718261e+01 1.2508874e+02
5.7891227e+01 5.5260906e+01 1.2742948e+02
6.0309043e+01 5.8972879e+01 1.2987179e+02
6.2821828e+01 6.2857777e+01 1.3241791e+02
6.5431494e+01 6.6919196e+01 1.3507007e+02
6.8139955e+01 7.1160733e+01 1.3783052e+02
7.0949123e+01 7.5585985e+01 1.4070150e+02
7.3860912e+01 8.0198549e+01 1.4368525e+02
7.6877233e+01 8.5002022e+01 1.4678400e+02
8.0000000e+01 9.0000000e+01 1.5000000e+02四、完整MATLAB代码
