Hello everyone, I really need your help. Why does NaN appear in my results? I really want to know. Thank you all. here is my code:
clc;
clear all;
close all;
cvx_solver mosek
%轨迹初始化
T = 120; %mission period
delta = T/120; %elemental length
N = T/delta; %number of time slot
vmax=40;
K=6;
w1 = [700ones(N,1),100ones(N,1)];
w2 = [200ones(N,1),450ones(N,1)];
w3 = [-300ones(N,1),450ones(N,1)];
w4 = [-600ones(N,1),200ones(N,1)];
w5 = [-450ones(N,1),-450ones(N,1)];
w6 = [400ones(N,1),-500ones(N,1)];
% 恶意干扰在移动
% 干扰点的初始轨迹
Jx1 =0 ;%圆心
Jy1 = 0;
Jw1 = 200;%radius
theta = 0:2pi/(N-1):2pi;
J11 = Jx1 + Jw1cos(theta);
J21 = Jy1 + Jw1sin(theta);
J11 = J11’;
J21 = J21’;
J = [J11,J21];
% J = [500ones(N,1),800ones(N,1)];%恶意干扰信号位置
pm=10;%1干扰功率
p1 = 1ones(N,1);%为什么当功率初始值为0.01时优化不可行
p2 = 1ones(N,1);
p3 = 1ones(N,1);
p4 = 1ones(N,1);
p5 = 1ones(N,1);
p6 = 1ones(N,1);
pmax=0.1;
B=10;
vmax = 40; %maximum speed
beta_db = -60; %单位距离下信道增益 dB
sigma_db = -148; %噪声强度dB
beta = 10^(beta_db/10);
sigma = 10^(sigma_db/10);
H = 100; %无人机高度
%初始轨迹 初始化不同,轨迹也不同
x11 = 0;%圆心
y11 = 0;
r1 = 200;%radius
theta = 0:2pi/(N-1):2pi;
%初始化无人机轨迹
q11 = x11 - r1cos(theta);
q21 = y11 - r1sin(theta);
% q11 = q11’;
% q21 = q21’;
% q1 = [q11,q21];
q1=[38ones(N,1),5ones(N,1)];
q1s=q1;
%无人机与用户位置d_r,u
for cntTra=1:1:3
d11 = H^2+(q1s(:,1)-w1(:,1)).^2+(q1s(:,2)-w1(:,2)).^2;
d12 = H^2+(q1s(:,1)-w2(:,1)).^2+(q1s(:,2)-w2(:,2)).^2;
d13 = H^2+(q1s(:,1)-w3(:,1)).^2+(q1s(:,2)-w3(:,2)).^2;
d14 = H^2+(q1s(:,1)-w4(:,1)).^2+(q1s(:,2)-w4(:,2)).^2;
d15 = H^2+(q1s(:,1)-w5(:,1)).^2+(q1s(:,2)-w5(:,2)).^2;
d16 = H^2+(q1s(:,1)-w6(:,1)).^2+(q1s(:,2)-w6(:,2)).^2;
d= H^2+(q1s(:,1)-J(:,1)).^2+(q1s(:,2)-J(:,2)).^2;
Is=sigma+(beta.*pm)./d;%初始可行解
Ls1=d11./(beta.*p1);
Ls2=d12./(beta.*p2);
Ls3=d13./(beta.*p3);
Ls4=d14./(beta.*p4);
Ls5=d15./(beta.*p5);
Ls6=d16./(beta.*p6);
LIs1=Ls1.*Is;
LIs2=Ls2.*Is;
LIs3=Ls3.*Is;
LIs4=Ls4.*Is;
LIs5=Ls5.*Is;
LIs6=Ls6.*Is;
A1=-B./(Ls1+Ls1.^2.*Is);%泰勒展开系数
A2=-B./(Ls2+Ls2.^2.*Is);
A3=-B./(Ls3+Ls3.^2.*Is);
A4=-B./(Ls4+Ls4.^2.*Is);
A5=-B./(Ls5+Ls5.^2.*Is);
A6=-B./(Ls6+Ls6.^2.*Is);
C1=-B./(Is+Is.^2.*Ls1);%泰勒展开系数
C2=-B./(Is+Is.^2.*Ls2);
C3=-B./(Is+Is.^2.*Ls3);
C4=-B./(Is+Is.^2.*Ls4);
C5=-B./(Is+Is.^2.*Ls5);
C6=-B./(Is+Is.^2.*Ls6);
cvx_begin
variable q1(N,2)
variable L1(N)
variable L2(N)
variable L3(N)
variable L4(N)
variable L5(N)
variable L6(N)
variable I(N)
variable eta
variable m(N)
expression qu1(N,1)
maximize eta
subject to
% B.log(1+1./(LIs1))+A1.(L1(:)-Ls1(:))+C1.(I(:)-Is(:))>=eta;%(1-1)
% B.log(1+1./(LIs2))+A2.(L2(:)-Ls2(:))+C2.(I(:)-Is(:))>=eta;
% B.log(1+1./(LIs3))+A3.(L3(:)-Ls3(:))+C3.(I(:)-Is(:))>=eta;
% B.log(1+1./(LIs4))+A4.(L4(:)-Ls4(:))+C4.(I(:)-Is(:))>=eta;
% B.log(1+1./(LIs5))+A5.(L5(:)-Ls5(:))+C5.(I(:)-Is(:))>=eta;
% B.log(1+1./(LIs6))+A6.(L6(:)-Ls6(:))+C6.(I(:)-Is(:))>=eta;
sum(B.log(1+1./(LIs1))+A1.(L1(:)-Ls1(:))+C1.(I(:)-Is(:)))/T>=eta;%(1-1)
sum(B.log(1+1./(LIs2))+A2.(L2(:)-Ls2(:))+C2.(I(:)-Is(:)))/T>=eta;
sum(B.log(1+1./(LIs3))+A3.(L3(:)-Ls3(:))+C3.(I(:)-Is(:)))/T>=eta;
sum(B.log(1+1./(LIs4))+A4.(L4(:)-Ls4(:))+C4.(I(:)-Is(:)))/T>=eta;
sum(B.log(1+1./(LIs5))+A5.(L5(:)-Ls5(:))+C5.(I(:)-Is(:)))/T>=eta;
sum(B.log(1+1./(LIs6))+A6.(L6(:)-Ls6(:))+C6.(I(:)-Is(:)))/T>=eta;
for i=1:1:N
H^2+sum_square_abs(q1(i,:)-w1(i,:))<=beta.*p1.*L1(i)%(1-2)
H^2+sum_square_abs(q1(i,:)-w2(i,:))<=beta.*p2.*L2(i);
H^2+sum_square_abs(q1(i,:)-w3(i,:))<=beta.*p3.*L3(i);
H^2+sum_square_abs(q1(i,:)-w4(i,:))<=beta.*p4.*L4(i);
H^2+sum_square_abs(q1(i,:)-w5(i,:))<=beta.*p5.*L5(i);
H^2+sum_square_abs(q1(i,:)-w6(i,:))<=beta.*p6.*L6(i);
pm*beta.*inv_pos(m(i))+sigma<=I(i)%(1-3)
end
for i=1:1:N
qu1(i)=2*q1s(i,1)q1(i,1)-q1s(i,1)^2+J(i,1)^2-2J(i,1)q1(i,1)+2q1s(i,2)q1(i,2)-q1s(i,2)^2+J(i,2)^2-2J(i,2)*q1(i,2)+H^2;%一阶泰勒
end
m<=qu1;%1-4
m>=0;%(1-5)
q1(1, == [38,5];
q1(N, == [38,5];
for i = 1:1:N-1
norm(q1(i+1,:)-q1(i,:))<=vmax*delta;
end
cvx_end
q1s=q1;
optvalue1(cntTra) = cvx_optval;
end
plot(q1(:,1),q1(:,2),‘r-’);
and the cvx result,
MOSEK Version 9.1.9 (Build date: 2019-11-21 11:34:40)
Copyright © MOSEK ApS, Denmark. WWW: mosek.com
Platform: Windows/64-X86
MOSEK warning 710: #119 (nearly) zero elements are specified in sparse col ‘’ (2) of matrix ‘A’.
MOSEK warning 710: #119 (nearly) zero elements are specified in sparse col ‘’ (3) of matrix ‘A’.
MOSEK warning 710: #119 (nearly) zero elements are specified in sparse col ‘’ (4) of matrix ‘A’.
MOSEK warning 710: #119 (nearly) zero elements are specified in sparse col ‘’ (5) of matrix ‘A’.
MOSEK warning 710: #119 (nearly) zero elements are specified in sparse col ‘’ (6) of matrix ‘A’.
MOSEK warning 710: #119 (nearly) zero elements are specified in sparse col ‘’ (7) of matrix ‘A’.
Problem
Name :
Objective sense : min
Type : CONIC (conic optimization problem)
Constraints : 2158
Cones : 959
Scalar variables : 4804
Matrix variables : 0
Integer variables : 0
Optimizer started.
Presolve started.
Linear dependency checker started.
Linear dependency checker terminated.
Eliminator started.
Freed constraints in eliminator : 119
Eliminator terminated.
Eliminator started.
Freed constraints in eliminator : 0
Eliminator terminated.
Eliminator - tries : 2 time : 0.00
Lin. dep. - tries : 1 time : 0.01
Lin. dep. - number : 0
Presolve terminated. Time: 0.03
Problem
Name :
Objective sense : min
Type : CONIC (conic optimization problem)
Constraints : 2158
Cones : 959
Scalar variables : 4804
Matrix variables : 0
Integer variables : 0
Optimizer - threads : 8
Optimizer - solved problem : the primal
Optimizer - Constraints : 1911
Optimizer - Cones : 959
Optimizer - Scalar variables : 4545 conic : 3585
Optimizer - Semi-definite variables: 0 scalarized : 0
Factor - setup time : 0.00 dense det. time : 0.00
Factor - ML order time : 0.00 GP order time : 0.00
Factor - nonzeros before factor : 1.46e+04 after factor : 1.63e+04
Factor - dense dim. : 0 flops : 9.18e+05
ITE PFEAS DFEAS GFEAS PRSTATUS POBJ DOBJ MU TIME
0 1.0e+00 1.2e+06 5.6e+06 0.00e+00 -5.634814049e+06 0.000000000e+00 1.0e+00 0.05
1 1.5e-01 1.8e+05 2.2e+06 -1.00e+00 -5.649644305e+06 -1.568614313e+04 1.5e-01 0.13
2 2.2e-02 2.6e+04 8.3e+05 -1.00e+00 -5.678186866e+06 -4.927101573e+04 2.2e-02 0.13
3 2.6e-03 3.1e+03 2.9e+05 -9.98e-01 -5.695087022e+06 -9.595615278e+04 2.6e-03 0.13
4 5.9e-04 7.1e+02 1.4e+05 -9.90e-01 -5.623862993e+06 -9.930221110e+04 5.9e-04 0.14
5 2.7e-04 3.2e+02 9.0e+04 -9.72e-01 -5.763864821e+06 -3.066820719e+05 2.7e-04 0.14
6 7.7e-05 9.1e+01 4.6e+04 -9.55e-01 -6.232046289e+06 -1.008782171e+06 7.7e-05 0.16
7 2.4e-05 2.9e+01 2.4e+04 -8.97e-01 -8.380284687e+06 -3.568447592e+06 2.4e-05 0.16
8 5.0e-06 5.9e+00 8.5e+03 -7.82e-01 -1.332767528e+07 -9.747378562e+06 5.0e-06 0.16
9 1.4e-06 1.7e+00 2.5e+03 -3.42e-01 -8.284920382e+06 -6.287267148e+06 1.4e-06 0.16
10 1.2e-06 1.4e+00 2.0e+03 3.72e-01 -6.751654569e+06 -5.004240253e+06 1.2e-06 0.16
11 3.7e-07 4.4e-01 3.4e+02 4.98e-01 -2.716411372e+06 -2.101315368e+06 3.7e-07 0.17
12 3.6e-08 4.3e-02 9.7e+00 8.97e-01 -2.700101022e+05 -2.092838589e+05 3.6e-08 0.17
13 5.7e-11 6.8e-05 5.8e-04 9.96e-01 -4.847685805e+02 -3.887267339e+02 5.7e-11 0.17
14 4.0e-12 4.7e-06 1.1e-05 9.91e-01 -4.539855750e+01 -3.861045693e+01 4.0e-12 0.17
15 2.7e-12 1.2e-06 1.5e-06 9.08e-01 -1.592128186e+01 -1.410469848e+01 9.9e-13 0.19
16 2.6e-12 1.2e-06 1.5e-06 8.04e-01 -1.585841787e+01 -1.404821190e+01 9.8e-13 0.19
17 2.6e-12 1.2e-06 1.5e-06 8.04e-01 -1.585055398e+01 -1.404115558e+01 9.8e-13 0.20
18 1.2e-12 5.2e-07 5.0e-07 8.04e-01 -6.872241777e+00 -5.978292074e+00 4.3e-13 0.20
19 4.6e-13 2.0e-07 1.4e-07 8.32e-01 -3.255482987e+00 -2.865309861e+00 1.7e-13 0.20
20 2.2e-13 9.9e-08 5.5e-08 7.40e-01 -6.112237008e-01 -3.917522776e-01 8.3e-14 0.22
21 2.2e-13 9.9e-08 5.5e-08 8.69e-01 -6.112237008e-01 -3.917522776e-01 8.3e-14 0.22
22 2.2e-13 9.9e-08 5.5e-08 9.22e-01 -6.110700817e-01 -3.916564226e-01 8.3e-14 0.23
23 2.2e-13 9.9e-08 5.5e-08 9.30e-01 -6.106432433e-01 -3.913322366e-01 8.3e-14 0.23
24 2.2e-13 9.9e-08 5.5e-08 9.30e-01 -6.106432433e-01 -3.913322366e-01 8.3e-14 0.23
25 2.1e-13 9.1e-08 4.8e-08 9.77e-01 -5.448428642e-01 -3.425804225e-01 7.7e-14 0.25
26 2.1e-13 9.0e-08 4.8e-08 9.81e-01 -5.370402990e-01 -3.367845338e-01 7.6e-14 0.25
27 2.1e-13 9.0e-08 4.7e-08 9.81e-01 -5.331878888e-01 -3.339127867e-01 7.5e-14 0.25
28 2.1e-13 9.0e-08 4.7e-08 9.81e-01 -5.331878888e-01 -3.339127867e-01 7.5e-14 0.25
29 2.1e-13 9.0e-08 4.7e-08 9.89e-01 -5.331878888e-01 -3.339127867e-01 7.5e-14 0.27
Optimizer terminated. Time: 0.31
Interior-point solution summary
Problem status : UNKNOWN
Solution status : UNKNOWN
Primal. obj: -5.3318788877e-01 nrm: 4e+09 Viol. con: 6e-03 var: 3e-08 cones: 0e+00
Dual. obj: -3.3391278675e-01 nrm: 4e+12 Viol. con: 0e+00 var: 3e-02 cones: 0e+00
Optimizer summary
Optimizer - time: 0.31
Interior-point - iterations : 30 time: 0.28
Basis identification - time: 0.00
Primal - iterations : 0 time: 0.00
Dual - iterations : 0 time: 0.00
Clean primal - iterations : 0 time: 0.00
Clean dual - iterations : 0 time: 0.00
Simplex - time: 0.00
Primal simplex - iterations : 0 time: 0.00
Dual simplex - iterations : 0 time: 0.00
Mixed integer - relaxations: 0 time: 0.00
Status: Failed
Optimal value (cvx_optval): NaN
Why does NaN appear in my second iteration? thank you.