一、無人機模型簡介：

單個無人機三維路徑規劃問題及其建模_IT猿手的博客-CSDN博客

參考文獻：

[1]胡觀凱,鐘建華,李永正,黎萬洪.基于IPSO-GA算法的無人機三維路徑規劃[J].現代電子技術,2023,46(07):115-120

二、Tiki-taka算法（TTA）簡介

極致攻守算法（Tiki-Taka Algorithm，TTA）由Mohd Fadzil Faisae Ab. Rashid于2020年提出，該算法受tiki-taka 足球風格的短傳、球員定位和保持控球的特點所啟發。其旨在控制控球權并利用其戰術優勢擊敗對手，TTA算法新穎高效。單目標應用：Tiki-taka算法（TTA）求解太陽能光伏模型MATLAB_IT猿手的博客-CSDN博客

參考文獻：

[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求解無人機路徑規劃

（1）部分代碼

close all
clear??
clc
addpath('./Algorithm/')%添加算法路徑
warning off;
%% 三維路徑規劃模型定義
global startPos goalPos N
N=2;%待優化點的個數(可以修改)
startPos = [10, 10, 80]; %起點(可以修改)
goalPos = [80, 90, 150]; %終點(可以修改)
SearchAgents_no=30; % 種群大小(可以修改)
Function_name='F2'; %F1:隨機產生地圖 F2：導入固定地圖
Max_iteration=50; %最大迭代次數(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);%算法優化求解
AlgorithmName='TTA';%算法名字
figure
semilogy(curve,'Color','g','linewidth',3)
xlabel('迭代次數');
ylabel('飛行路徑長度');
legend(AlgorithmName)
display(['算法得到的最優適應度: ', num2str(Best_score)]);?
Position=[Best_pos(1:dim/3); Best_pos(1+dim/3:2*(dim/3)); Best_pos(1+(2*dim/3):end)]'; %優化點的XYZ坐標（每一行是一個點）
plotFigure(Best_pos,AlgorithmName)%畫最優路徑

（2）部分結果

無人機飛行路徑坐標：

? ?1.0000000e+01? ?1.0000000e+01? ?8.0000000e+011.1038557e+01? ?1.2396654e+01? ?7.9835160e+011.2060154e+01? ?1.4689974e+01? ?7.9703710e+011.3065298e+01? ?1.6882604e+01? ?7.9605399e+011.4054500e+01? ?1.8977186e+01? ?7.9539976e+011.5028266e+01? ?2.0976364e+01? ?7.9507189e+011.5987105e+01? ?2.2882782e+01? ?7.9506789e+011.6931527e+01? ?2.4699083e+01? ?7.9538522e+011.7862038e+01? ?2.6427910e+01? ?7.9602140e+011.8779149e+01? ?2.8071906e+01? ?7.9697390e+011.9683367e+01? ?2.9633716e+01? ?7.9824022e+012.0575201e+01? ?3.1115982e+01? ?7.9981784e+012.1455159e+01? ?3.2521348e+01? ?8.0170425e+012.2323749e+01? ?3.3852458e+01? ?8.0389696e+012.3181481e+01? ?3.5111953e+01? ?8.0639343e+012.4028863e+01? ?3.6302479e+01? ?8.0919117e+012.4866402e+01? ?3.7426679e+01? ?8.1228766e+012.5694608e+01? ?3.8487195e+01? ?8.1568040e+012.6513989e+01? ?3.9486671e+01? ?8.1936686e+012.7325054e+01? ?4.0427751e+01? ?8.2334455e+012.8128311e+01? ?4.1313077e+01? ?8.2761096e+012.8924268e+01? ?4.2145294e+01? ?8.3216356e+012.9713434e+01? ?4.2927045e+01? ?8.3699985e+013.0496317e+01? ?4.3660973e+01? ?8.4211733e+013.1273427e+01? ?4.4349722e+01? ?8.4751347e+013.2045270e+01? ?4.4995934e+01? ?8.5318578e+013.2812356e+01? ?4.5602253e+01? ?8.5913173e+013.3575194e+01? ?4.6171324e+01? ?8.6534883e+013.4334291e+01? ?4.6705788e+01? ?8.7183455e+013.5090157e+01? ?4.7208290e+01? ?8.7858639e+013.5843299e+01? ?4.7681472e+01? ?8.8560184e+013.6594226e+01? ?4.8127979e+01? ?8.9287839e+013.7343447e+01? ?4.8550453e+01? ?9.0041352e+013.8091470e+01? ?4.8951539e+01? ?9.0820473e+013.8838803e+01? ?4.9333879e+01? ?9.1624951e+013.9585956e+01? ?4.9700116e+01? ?9.2454534e+014.0333436e+01? ?5.0052895e+01? ?9.3308972e+014.1081751e+01? ?5.0394858e+01? ?9.4188014e+014.1831412e+01? ?5.0728649e+01? ?9.5091408e+014.2582925e+01? ?5.1056912e+01? ?9.6018903e+014.3336799e+01? ?5.1382289e+01? ?9.6970249e+014.4093543e+01? ?5.1707425e+01? ?9.7945194e+014.4853666e+01? ?5.2034961e+01? ?9.8943488e+014.5617675e+01? ?5.2367543e+01? ?9.9964879e+014.6386079e+01? ?5.2707813e+01? ?1.0100912e+024.7159387e+01? ?5.3058415e+01? ?1.0207595e+024.7938107e+01? ?5.3421991e+01? ?1.0316512e+024.8722748e+01? ?5.3801187e+01? ?1.0427639e+024.9513818e+01? ?5.4198643e+01? ?1.0540951e+025.0311825e+01? ?5.4617006e+01? ?1.0656421e+025.1117279e+01? ?5.5058916e+01? ?1.0774025e+025.1930687e+01? ?5.5527019e+01? ?1.0893738e+025.2752557e+01? ?5.6023957e+01? ?1.1015535e+025.3583399e+01? ?5.6552374e+01? ?1.1139391e+025.4423722e+01? ?5.7114913e+01? ?1.1265280e+025.5274032e+01? ?5.7714218e+01? ?1.1393178e+025.6134839e+01? ?5.8352931e+01? ?1.1523059e+025.7006652e+01? ?5.9033697e+01? ?1.1654899e+025.7889978e+01? ?5.9759159e+01? ?1.1788671e+025.8785326e+01? ?6.0531959e+01? ?1.1924352e+025.9693205e+01? ?6.1354742e+01? ?1.2061916e+026.0614124e+01? ?6.2230151e+01? ?1.2201337e+026.1548590e+01? ?6.3160830e+01? ?1.2342591e+026.2497112e+01? ?6.4149421e+01? ?1.2485653e+026.3460198e+01? ?6.5198567e+01? ?1.2630498e+026.4438358e+01? ?6.6310914e+01? ?1.2777100e+026.5432099e+01? ?6.7489103e+01? ?1.2925434e+026.6441930e+01? ?6.8735778e+01? ?1.3075475e+026.7468359e+01? ?7.0053583e+01? ?1.3227199e+026.8511895e+01? ?7.1445161e+01? ?1.3380580e+026.9573047e+01? ?7.2913156e+01? ?1.3535592e+027.0652322e+01? ?7.4460210e+01? ?1.3692212e+027.1750230e+01? ?7.6088967e+01? ?1.3850413e+027.2867279e+01? ?7.7802071e+01? ?1.4010170e+027.4003977e+01? ?7.9602164e+01? ?1.4171460e+027.5160832e+01? ?8.1491891e+01? ?1.4334255e+027.6338354e+01? ?8.3473895e+01? ?1.4498532e+027.7537050e+01? ?8.5550819e+01? ?1.4664265e+027.8757429e+01? ?8.7725306e+01? ?1.4831430e+028.0000000e+01? ?9.0000000e+01? ?1.5000000e+02

四、完整MATLAB代碼