【路径规划】基于matlab无线充电车辆路径和速度预测【含Matlab源码 1473期】

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二、部分源代码

clc;
clear all;
close all;

global Qk ax ay Dik tou beta indA indB

%% Intialization 
Nnodes=1;
Emax=1000;
Emin=5;
nk=8;
V=20;
Ra=10+(100-10).*rand(1,nk); % data rate
%% New
T=50; %patrolling cycle time constraint
% v,a---velocity and accelration
%% Charging behavior eqn 1
Ptx=10;
Gtx=3;
Grx=2;
lamda=20e-3;
Lp=0.3;
eta=0.9;
beta=0.2316;

tou= ((Gtx.*Grx.*eta./Lp).*(lamda./4.*pi).^2).*Ptx
   % Distance4 bw node and chaerger
   d=10; %--- Modified
   
   Prx=@(d)(tou./(d+beta).^2)
   
   Prx(2)
   % Tx power of Charger
   
   
D=15;
itr=5;
for i1=1:itr
    
noOfNodes=nk; 
figure(1); 
axis tight manual
clf; 
hAx1 = axes;
hold on; 

a=1;
b=nk;
r =floor( a + (b-a).*(rand(2,1)));

while(r(1)==r(2))
    r =floor( a + (b-a).*(rand(2,1)));
end
sor =r(1);%source node 
des=r(2);%destination node
R =5.5; %node transmission range 
a=1;
b=noOfNodes;
%X=floor(a + (b-a).*rand(1,noOfNodes));
%Y=floor(a + (b-a).*rand(1,noOfNodes));
X = 1+(30-1)*rand(1,nk);
Y = 1+(30-1)*rand(1,nk);

 X1= 10+(20-10)*rand(1,1);
 Y1= 10+(20-5)*rand(1,1);
% 
 X2= 5+(15-5)*rand(1,1);
 Y2= 10+(10-5)*rand(1,1);


%Z =[1 0.1 0.6 0.8 0.6 0 0.1 1 1 1];

%plotting network topology 
%i2=1;
for i2 = 1:noOfNodes 
 plot(X(i2),Y(i2),'o','LineWidth',1,...
              'MarkerEdgeColor','k',...
              'MarkerFaceColor','y',...
              'MarkerSize',8'); 
          xlabel('X in m')
          ylabel('Y in m')
    text(X(i2), Y(i2), num2str(i2),'FontSize',10); 
    

    %% Destination
      plot(X2,Y2,'^','LineWidth',1,...
              'MarkerEdgeColor','k',...
              'MarkerFaceColor','r',...
              'MarkerSize',14'); 
             
hold on

end 
axis([0 40 -5 40])
M_max = 14; %// number of cells in vertical direction
N_max = 10; %// number of cells in horizontal direction
trans = 1;  %// hexagon orientation (0 or 1)

%// Do the plotting:
hold on

C11={};
C={};

ab=1;
ik=1;
for x=0:7%:2;
      ik=x;
  for y=0:5
  
  if(mod(ik,2))
      x0=3+4.3*x;
      y0=3+3*2*y;
      hexagon(2,x0,y0);
      C11{x+1,y+1}=[x0;y0];
%       C{ab}=[x0;y0];
      hold on
      plot(x0,y0,'ok','MarkerFaceColor','k')
       
       cote=2;
       x1=cote*sqrt(2)*[-1 -0.5 0.5 1 0.5 -0.5 -1]+x0;
       y1=cote*sqrt(9)*[0 -0.5 -0.5 0 0.5 0.5 0]+y0;
       
       
  else
       x0=3+4.3*x;
       y0=3*2*y;
       hexagon(2,x0,y0);
       C11{x+1,y+1}=[3+4.3*x;3*2*y];
      
       hold on
       plot(3+4.3*x,3*2*y,'ok', 'MarkerFaceColor','k')
       
       
       cote=2;
       x1=cote*sqrt(2)*[-1 -0.5 0.5 1 0.5 -0.5 -1]+x0;
       y1=cote*sqrt(9)*[0 -0.5 -0.5 0 0.5 0.5 0]+y0;
       
          
  end  
    C{ab}=[x0,y0];
 %% Inside the polygon or not
    [in,on] = inpolygon(X,Y,x1,y1);
    
     Nk(ab)=numel(find(in==1));% set of sensor node
     ind=[];
     ind=find(in==1);
     if(isempty(ind))
     Dik{ab}=0; 
     Qk(ab)=0;  
     else
     Dik{ab}=sqrt((X(ind)-x0).^2 +(Y(ind)-y0).^2 ); % distance froom node i to its cell center
     Qk(ab)=1;
     end
     %Tk --> Time stays of WCV     
     
     ab=ab+1;
  

  end
end


% axis([0 30 0 30]) 
% grid 
%% Travelling path Model
k=ab-1;
Z=ones(1,k); %% important
aa=cell2mat(C.');
Xa=aa(:,1);
Ya=aa(:,2);


    %% WCV
     plot(Xa(1)+2,Ya(1)+2,'o','LineWidth',1,...
              'MarkerEdgeColor','k',...
              'MarkerFaceColor','g',...
              'MarkerSize',12'); 
     plot(Xa(1),Ya(1),'o','LineWidth',1,...
              'MarkerEdgeColor','k',...
              'MarkerFaceColor','k',...
              'MarkerSize',14'); 
          xlabel('X in m')
          ylabel('Y in m')
    hold on      
    text(Xa(1), Ya(1),'Vechile Stay Room','FontSize',10);
    
    hold on
    
    
saveas(gcf,'fileint.fig','fig')
% %% Existing Routing
 s=cell2mat(C.');
 ax=s(:,1);
 ay=s(:,2);
 
%%   Routing

  indA=find(Qk==1);
  indB=find(Qk~=1);
  G=randperm(numel(indA));
  path1 = indA(G);
   
%% OPTIMIZATION    
% %% Problem Definition
CostFunction=@(x) Sphere(x);        % Cost Function

ik=1;
  %cost1=1000;
  eff1=inf;
  
while(ik<=4000)
    T1=1000.*rand(1);  
    T=CostFunction(T1);
    eff=(T);
  if(eff<=eff1)
     eff1=eff;
     TT=T1;
  end
  costh1(ik)=eff1;
  costh(ik)=eff;
  ik=ik+1;
end

  

 

  
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三、运行结果

四、matlab版本及参考文献

1 matlab版本
2014a

2 参考文献
[1] 包子阳,余继周,杨杉.智能优化算法及其MATLAB实例（第2版）[M].电子工业出版社，2016.
[2]张岩,吴水根.MATLAB优化算法源代码[M].清华大学出版社，2017.

文章来源: qq912100926.blog.csdn.net，作者：海神之光，版权归原作者所有，如需转载，请联系作者。

原文链接：qq912100926.blog.csdn.net/article/details/121054731