飞行仿真-基于Matlab+Simulink实现多固定翼无人机飞行仿真建模-附项目源码+流程教程+效果展示-优质项目实战.zip

# Multiple fixed-wing UAVs flight simulation platform ## 1. Introduction A multiple fixed-wing UAVs flight simulation platform built by matlab and simulink. The example given here has 5 UAVs, but of course you can expand it to 10, 20 or even more if you are willing to take the time. Input: The path of all uavs Output: 13 state quantities per drone per moment pn1 % inertial Northposition pe1 % inertial East position pd1 % inertial Down position u1 % body frame velocities v1 w1 phi1 % roll angle theta1 % pitch angle psi1 % yaw angle p1 % roll rate q1 % pitch rate r1 % yaw rate t1 % time  --- ## 2. The original intention of platform building Recently, there is a need to extend the algorithm of cooperative control to fixed-wing UAVs, but the cooperative control algorithm generally considers first-order and second-order integrators or a bicycle model. Even if a fixed-wing model is considered, it is only a simple fixed-wing dynamics model. But the real fixed-wing UAV flight control model is very complex and has strong nonlinearity. So how to prove that my proposed fixed-wing cooperative control algorithm, or planning algorithm is effective. You know strict mathematical proof is very difficult, but it can be proven to work well in engineering. At this point, it is necessary to use a more realistic fixed-wing flight control model to simulate the real UAV flight state. This is the reason why I built this platform. In fact, Matlab has a simulation tool for fixed-wing UAVs( [Matlab fixed-wing UAV tool ](https://ww2.mathworks.cn/help/uav/ref/fixedwing.html )), but the official documentation is small, and it is not very convenient to use, and the animation display can only show one aircraft. In short, it is not good enough. The code mainly refers to Randal's "Small Unmanned Aircraft Theory and Practice", which the flight control principle used in code I hardly understand. My job is to integrate them and show them inside one screen. As a person who does planning, you don't have to figure out all the underlying control principles.  --- ## 3. How to use The simulation platform can be divided into two parts, one is the calculation part 'uavA1' and the other is the display part 'uavShow'. Just run the main.m file directly. In fact, you can also synchronize the calculation and display, real-time calculation and then display. But personally, I think this will affect the smoothness of the display. The more aircraft the greater the impact will be. ### 3.1 Calculation part The state of each aircraft is calculated in turn over time and will be stored in the x1.mat file (x1 can be x2,x3.... which indicates the number of aircraft). - CalAlluavs.m  ### 3.2 Show part - ShowAlluavs.m The data of each aircraft is stored in x, path, waypoint data. Using all the data, the show part could work. ## 4. How to read path files The folder 'data' provides some path files for 5 aircraft that can be used. If you want to calculate your own route data, you can follow these steps. 1. uavA1/getWpp.m -> load '5jia.mat' 2. uavA1/para_chap1.m -> load '5jia.mat' Find the corresponding code in the file and change the name of '5jia.mat' . 'getWpp.m' Read the path 'para_chap1.m' reads the initial position of the aircraft The simulink time needs to be adjusted according to the length of your path file, if your uav obviously did not run through your path, you need to adjust the time longer. ### Details about--- getWpp( ) function ```matlab function [num_waypoints , wpp] = getWpp(P,uav) load '5jia3.mat' a1 = 2; a2 = 400; num_waypoints = a2/a1; wpp = []; i1 = uav; for i = 1:a1:a2 x = []; x = Xplot2(i,6*i1-5:6*i1-3); x(3) = -x(3); x = [x -9999 Xplot2(i,6*i1-2)]; wpp = [wpp;x]; end ``` 5jia3.mat: The file which stores the states of 5 aircraft 400x30 400:Step length 30: 5x6 6 state quantities for 5 aircraft positions in three directions：x y z velocity :v Two angles of the velocity : theta phi (velocity has no Rolling angle )_ 14-20 line:dealing with the file 5jia3.mat x = Xplot2(i,6*i1-5:6*i1-3): 6*i1-5:6*i1-3 to get the positions x,y,z 6*i1-2 to get the velocity Now I have 400 steps of states to pass, and I don't want to pass each of them. So I'll pass every other one(1 , 3, 5... ), which is a1=2. Every two passes a1=3(1, 4, 7...). If you want to read your own path file, you can follow the format of my "5jia3.mat" file to generate it, or you can set up your own path file. As you can see, I just passed the position and velocity, not the angle of the velocity. So the subsequent flight control is only tracking the position point according to the reference speed when tracking. ## 5. How to increase the number of uavs How to increase the aircraft is actually very easy but a little bit of boring. You need to add some code and change the corresponding numbers. The steps are as follows. ## The steps are as follows: ### 1. main.m First of all, in the 'main.m' file, you can see that the code statements for each aircraft are obvious, add the corresponding sentences. ```matlab %---------------- uavW = 1; save('uavW.mat','uavW'); sim('New_mavsim_chap12'); ii = 1; eval(['x' num2str(ii) '= x;']) eval(['path' num2str(ii) '= path;']) eval(['waypoints' num2str(ii) '= waypoints;']) save('x1.mat','x1','path1','waypoints1'); %---------------- clear; uavW = 2; uavi = uavW; save('uavW.mat','uavW'); sim('New_mavsim_chap12'); ii = 2; eval(['x' num2str(ii) '= x;']) eval(['path' num2str(ii) '= path;']) eval(['waypoints' num2str(ii) '= waypoints;']) save('x2.mat','x2','path2','waypoints2'); %---------------- clear; uavW = 3; save('uavW.mat','uavW'); sim('New_mavsim_chap12'); ii = 3; eval(['x' num2str(ii) '= x;']) eval(['path' num2str(ii) '= path;']) eval(['waypoints' num2str(ii) '= waypoints;']) save('x3.mat','x3','path3','waypoints3'); %---------------- clear; uavW = 4; save('uavW.mat','uavW'); sim('New_mavsim_chap12'); ii = 4; eval(['x' num2str(ii) '= x;']) eval(['path' num2str(ii) '= path;']) eval(['waypoints' num2str(ii) '= waypoints;']) save('x4.mat','x4','path4','waypoints4'); %---------------- clear; uavW = 5; save('uavW.mat','uavW'); sim('New_mavsim_chap12'); ii = 5; eval(['x' num2str(ii) '= x;']) eval(['path' num2str(ii) '= path;']) eval(['waypoints' num2str(ii) '= waypoints;']) save('x5.mat','x5','path5','waypoints5'); ``` ### 2. uavShow/drawEnvironments5.m Add the sentence of uavShow/drawEnvironments5.m. The sentence here looks complicated, but you don't have to figure out what it means. Just add it mechanically and change the numbers. If you look at the file uavShow/drawEnvironments5.m, you'll see what I'm talking about. ```matlab %----------------1----------------------------------- NN = 0; pn1 = uu(1+NN); % inertial North position pe1 = uu(2+NN); % inertial East position pd1 = uu(3+NN); % inertial Down position u1 = uu(4+NN); % body frame velocities v1 = uu(5+NN); w1 = uu(6+NN); phi1 = uu(7+NN); % roll angle theta1 = uu(8+NN); % pitch angle psi1 = uu(9+NN); % yaw angle p1 = uu(10+NN); % roll rate q1 = uu(11+NN); % pitch rate r1 = uu(12+NN); % yaw rate t1 = uu(13+NN); % time NN = NN + 13; path1 = uu(1+NN:13+NN); NN = NN + 13; num_waypoints1 = uu(1+NN); waypoints1 = reshape(uu(2+NN:5*num_waypoints1+1+NN),5,num_waypoints1)'; % define persistent variables