Error using function handles in genetic algorithm.

13 Mai 2024
0 Antworten
Aktualisiert 14 Mai 2024
2 Ansichten (30 Tage)

0 Stimmen

I am getting error:
Unrecognized function or variable 'p'.
clc; clear; close all;
Vs = 250;
k = @(p) p/Vs;
c = @(theta) Vs/sin(theta);
w = 0.001;
d_h = -2;
numElements = 10;
ES = d_h/numElements;
r_s= 2000;
G_s= 1.25e8;
n_s= 0.3;
l_s= 2*n_s*G_s/(1-2*n_s);
a_s= sqrt((l_s+2*G_s)/r_s);
b_s= sqrt(G_s/r_s);
r_g= 24;
G_g= 3e6;
n_g= 0.17;
dl = -5;
%% Genetic Algorithm Parameters
options = optimoptions(@ga,'PopulationSize', 30, 'MaxGenerations', 200,'PlotFcn','gaplotbestf');
% Objective Function
objective_function = @(x_optimal) calculateObjective(x_optimal, Vs, w, r_s, G_s, n_s, k(p), c(theta), r_g, G_g, n_g, dl, d_h, numElements, ES, l_s, a_s, b_s);
A = [];
b = [];
lb = zeros(1, numElements-2);
ub = ones(1, numElements-2);
nonlcon = [];
[x_optimal, fval] = ga(objective_function, numElements-2, A, b, [], [], lb, ub,nonlcon, options);
% function to calculate objective
function answer = calculateObjective(x_optimal, Vs, w, r_s, G_s, n_s, k, c, r_g, G_g, n_g, dl, d_h, numElements, ES, l_s, a_s, b_s);
x = [1, x_optimal, 1];
disp(x_optimal);
% rest of the code
answer = integral2(@(theta,p)arrayfun(@(theta,p)q(theta,p),theta,p),pi/18,pi/6,2*pi,20*pi); % minimize
end

6 Kommentare
4 ältere Kommentare anzeigen 4 ältere Kommentare ausblenden

Star Strider
Star Strider am 13 Mai 2024
The missing ‘p’ (used in function ‘k’) is not the only problem.
The ‘answer’ integration uses function ‘q’, however ‘q’ is also nowhere to be found.
Manoj Manoj
Manoj Manoj am 13 Mai 2024
The error I am getting is because of p and theta. q is some function of p and theta.
Unrecognized function or variable 'p'.
Error in matlabanswer>@(x_optimal)calculateObjective(x_optimal,Vs,w,r_s,G_s,n_s,k(p),c(theta),r_g,G_g,n_g,dl,d_h,numElements,ES,l_s,a_s,b_s) (line 27)
objective_function = @(x_optimal) calculateObjective(x_optimal, Vs, w, r_s, G_s, n_s, k(p), c(theta), r_g, G_g, n_g, dl, d_h, numElements, ES, l_s, a_s, b_s);
Error in createAnonymousFcn>@(x)fcn(x,FcnArgs{:}) (line 11)
fcn_handle = @(x) fcn(x,FcnArgs{:});
Error in makeState (line 58)
firstMemberScore = FitnessFcn(state.Population(initScoreProvided+1,:));
Error in galincon (line 24)
state = makeState(GenomeLength,FitnessFcn,Iterate,output.problemtype,options);
Error in ga (line 414)
[x,fval,exitFlag,output,population,scores] = galincon(FitnessFcn,nvars, ...
Error in matlabanswer (line 34)
[x_optimal, fval] = ga(objective_function, numElements-2, A, b, [], [], lb, ub,nonlcon, options);
Caused by:
Failure in initial user-supplied fitness function evaluation. GA cannot continue.
Torsten
Torsten am 13 Mai 2024
Bearbeitet: Torsten am 13 Mai 2024
objective_function = @(x_optimal) calculateObjective(x_optimal, Vs, w, r_s, G_s, n_s, k, c, r_g, G_g, n_g, dl, d_h, numElements, ES, l_s, a_s, b_s);
instead of
objective_function = @(x_optimal) calculateObjective(x_optimal, Vs, w, r_s, G_s, n_s, k(p), c(theta), r_g, G_g, n_g, dl, d_h, numElements, ES, l_s, a_s, b_s);
Remember that in "calculateObjective", k and c will be function handles, not values. Use them correctly in function q.
Star Strider
Star Strider am 13 Mai 2024
The only reference I found to ‘q’ was in the ‘answer’ assignment. I still can’t find the actual function anywhere. I’d have trtied to run the code otherwise.
Manoj Manoj
Manoj Manoj am 14 Mai 2024
This is the complete code
Vs = 250;
k = @(p) p/Vs;
c = @(theta) Vs/sin(theta);
w = 0.001;
d_h = -2;
numElements = 10;
ES = d_h/numElements;
r_s= 2000;
G_s= 1.25e8;
n_s= 0.3;
l_s= 2*n_s*G_s/(1-2*n_s);
a_s= sqrt((l_s+2*G_s)/r_s);
b_s= sqrt(G_s/r_s);
r_g= 24;
G_g= 3e6;
n_g= 0.17;
dl = -5;
%% Genetic Algorithm Parameters
options = optimoptions(@ga,'PopulationSize', 30, 'MaxGenerations', 200,'PlotFcn','gaplotbestf');
% Objective Function
objective_function = @(x_optimal) calculateObjective(x_optimal, Vs, w, r_s, G_s, n_s, k, c, r_g, G_g, n_g, dl, d_h, numElements, ES, l_s, a_s, b_s);
A = [];
b = [];
lb = zeros(1, numElements-2);
ub = ones(1, numElements-2);
nonlcon = [];
[x_optimal, fval] = ga(objective_function, numElements-2, A, b, [], [], lb, ub,nonlcon, options);
% function to calculate objective
function answer = calculateObjective(x_optimal, Vs, w, r_s, G_s, n_s, k, c, r_g, G_g, n_g, dl, d_h, numElements, ES, l_s, a_s, b_s);
disp(x_optimal);
l_g= 2*n_g*G_g/(1-2*n_g);
a_g= sqrt((l_g+2*G_g)/r_g);
b_g= sqrt(G_g/r_g);
g_a_g= sqrt((c/a_g)^2-1);
g_b_g= sqrt((c/b_g)^2-1);
theta_g= 2*(b_g/c)^2;
A_g = k*g_a_g*dl;
B_g = k*g_b_g*dl;
C_A_g= cos(A_g);
S_A_g= sin(A_g);
C_B_g= cos(B_g);
S_B_g= sin(B_g);
Gg_inv = [theta_g*C_A_g+(1-theta_g)*C_B_g, 1i*(g_a_g*g_b_g*theta_g*S_B_g+(theta_g-1)*S_A_g)/g_a_g, (-C_A_g+C_B_g)/(c^2*r_g), 1i*(g_a_g*g_b_g*S_B_g+S_A_g)/(c^2*g_a_g*r_g);...
1i*(-g_a_g*g_b_g*theta_g*S_A_g+(1-theta_g)*S_B_g)/g_b_g, theta_g*C_B_g+(1-theta_g)*C_A_g, 1i*(g_a_g*g_b_g*S_A_g+S_B_g)/(c^2*g_b_g*r_g), (-C_A_g+C_B_g)/(c^2*r_g);...
c^2*r_g*theta_g*(theta_g-1)*(C_A_g-C_B_g), 1i*c^2*r_g*(g_a_g*g_b_g*theta_g^2*S_B_g+(theta_g-1)^2*S_A_g)/g_a_g, theta_g*C_B_g+(1-theta_g)*C_A_g, 1i*(g_a_g*g_b_g*theta_g*S_B_g+(theta_g-1)*S_A_g)/g_a_g;...
1i*c^2*r_g*(g_a_g*g_b_g*theta_g^2*S_A_g+(theta_g-1)^2*S_B_g)/g_b_g, c^2*r_g*theta_g*(theta_g-1)*(C_A_g-C_B_g), 1i*(-g_a_g*g_b_g*theta_g*S_A_g+(1-theta_g)*S_B_g)/g_b_g, theta_g*C_A_g+(1-theta_g)*C_B_g];
l_s= 2*n_s*G_s/(1-2*n_s);
a_s= sqrt((l_s+2*G_s)/r_s);
b_s= sqrt(G_s/r_s);
g_a_s= sqrt((c/a_s)^2-1);
g_b_s= sqrt((c/b_s)^2-1);
theta_s= 2*(b_s/c)^2;
A_s = k*g_a_s*d_h;
B_s = k*g_b_s*d_h;
C_A_s= cos(A_s);
S_A_s= sin(A_s);
C_B_s= cos(B_s);
S_B_s= sin(B_s);
Gs_inv = [theta_s*C_A_s+(1-theta_s)*C_B_s, 1i*(g_a_s*g_b_s*theta_s*S_B_s+(theta_s-1)*S_A_s)/g_a_s, (-C_A_s+C_B_s)/(c^2*r_s), 1i*(g_a_s*g_b_s*S_B_s+S_A_s)/(c^2*g_a_s*r_s);...
1i*(-g_a_s*g_b_s*theta_s*S_A_s+(1-theta_s)*S_B_s)/g_b_s, theta_s*C_B_s+(1-theta_s)*C_A_s, 1i*(g_a_s*g_b_s*S_A_s+S_B_s)/(c^2*g_b_s*r_s), (-C_A_s+C_B_s)/(c^2*r_s);...
c^2*r_s*theta_s*(theta_s-1)*(C_A_s-C_B_s), 1i*c^2*r_s*(g_a_s*g_b_s*theta_s^2*S_B_s+(theta_s-1)^2*S_A_s)/g_a_s, theta_s*C_B_s+(1-theta_s)*C_A_s, 1i*(g_a_s*g_b_s*theta_s*S_B_s+(theta_s-1)*S_A_s)/g_a_s;...
1i*c^2*r_s*(g_a_s*g_b_s*theta_s^2*S_A_s+(theta_s-1)^2*S_B_s)/g_b_s, c^2*r_s*theta_s*(theta_s-1)*(C_A_s-C_B_s), 1i*(-g_a_s*g_b_s*theta_s*S_A_s+(1-theta_s)*S_B_s)/g_b_s, theta_s*C_A_s+(1-theta_s)*C_B_s];
B= Gs_inv*Gg_inv;
B1= B(1,1);
B2= B(1,2);
B3= B(1,3);
B4= B(1,4);
B5= B(2,1);
B6= B(2,2);
B7= B(2,3);
B8= B(2,4);
B9= B(3,1);
B10= B(3,2);
B11= B(3,3);
B12= B(3,4);
B13= B(4,1);
B14= B(4,2);
B15= B(4,3);
B16= B(4,4);
c1= -(B1+B2);
c2= -(B3+B4);
c3= -(B5+B6);
c4= -(B7+B8);
c5= -(B9+B10);
c6= -(B11+B12);
c7= -(B13+B14);
c8= -(B15+B16);
x2_inv= [(-b_bar*c3*c8+b_bar*c4*c7+c3*c6*d_bar-c4*c5*d_bar+c5*c8-c6*c7)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (b_bar*c1*c8-b_bar*c2*c7-c1*c6*d_bar+c2*c5*d_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-b_bar*c1*c4+b_bar*c2*c3+c1*c6-c2*c5)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7);...
(a_bar*c3*c8-a_bar*c4*c7-c3*c6*c_bar+c4*c5*c_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-a_bar*c1*c8+a_bar*c2*c7+c1*c6*c_bar-c2*c5*c_bar+c5*c8-c6*c7)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (a_bar*c1*c4-a_bar*c2*c3+c3*c6-c4*c5)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7);...
(a_bar*c4*d_bar-a_bar*c8-b_bar*c4*c_bar+c6*c_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-a_bar*c2*d_bar+b_bar*c2*c_bar-b_bar*c8+c6*d_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-c2*c_bar-c4*d_bar+c8)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (a_bar*c2+b_bar*c4-c6)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7);...
(-a_bar*c3*d_bar+a_bar*c7+b_bar*c3*c_bar-c5*c_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (a_bar*c1*d_bar-b_bar*c1*c_bar+b_bar*c7-c5*d_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (c1*c_bar+c3*d_bar-c7)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-a_bar*c1-b_bar*c3+c5)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7)];
Y2= x2_inv*(B*[0;0;-w;w]);
u_in= (B(1,4)-B(1,3))*c*w;
mag_u_in= abs(u_in);
w_in= (B(2,4)-B(2,3))*c*w;
mag_w_in= abs(w_in);
Input= sqrt(mag_u_in^2+mag_w_in^2);
u_out= c*abs(Y2(1,1));
w_out= c*abs(Y2(2,1));
Output= sqrt(u_out^2+w_out^2);
q= @(theta,p)Output/Input;
answer = integral2(@(theta,p)arrayfun(@(theta,p)q(theta,p),theta,p),pi/18,pi/6,2*pi,20*pi); % minimize
end
Torsten
Torsten am 14 Mai 2024
Bearbeitet: Torsten am 14 Mai 2024
Try this.
I wonder why your function does not depend on "x_optimal" . From your code, you will always get the same value for "answer" from the "integral2" function, and thus "ga" will terminate with the initial condition vector for x_optimal.
Vs = 250;
k = @(p) p/Vs;
c = @(theta) Vs/sin(theta);
w = 0.001;
d_h = -2;
numElements = 10;
ES = d_h/numElements;
r_s= 2000;
G_s= 1.25e8;
n_s= 0.3;
l_s= 2*n_s*G_s/(1-2*n_s);
a_s= sqrt((l_s+2*G_s)/r_s);
b_s= sqrt(G_s/r_s);
r_g= 24;
G_g= 3e6;
n_g= 0.17;
dl = -5;
%% Genetic Algorithm Parameters
options = optimoptions(@ga,'PopulationSize', 30, 'MaxGenerations', 200,'PlotFcn','gaplotbestf');
% Objective Function
objective_function = @(x_optimal) driver_calculateObjective(x_optimal, Vs, w, r_s, G_s, n_s, k, c, r_g, G_g, n_g, dl, d_h, numElements, ES, l_s, a_s, b_s);
A = [];
b = [];
lb = zeros(1, numElements-2);
ub = ones(1, numElements-2);
nonlcon = [];
[x_optimal, fval] = ga(objective_function, numElements-2, A, b, [], [], lb, ub,nonlcon, options);
function answer = driver_calculateObjective(x_optimal, Vs, w, r_s, G_s, n_s, k, c, r_g, G_g, n_g, dl, d_h, numElements, ES, l_s, a_s, b_s);
q = @(theta,p)calculate_objective(theta,p,x_optimal,Vs, w, r_s, G_s, n_s, k(p), c(theta), r_g, G_g, n_g, dl, d_h, numElements, ES, l_s, a_s, b_s);)
answer = integral2(@(theta,p)arrayfun(@(theta,p)q(theta,p),theta,p),pi/18,pi/6,2*pi,20*pi); % minimize
end
% function to calculate objective
function answer = calculateObjective(x_optimal, Vs, w, r_s, G_s, n_s, k, c, r_g, G_g, n_g, dl, d_h, numElements, ES, l_s, a_s, b_s);
disp(x_optimal);
l_g= 2*n_g*G_g/(1-2*n_g);
a_g= sqrt((l_g+2*G_g)/r_g);
b_g= sqrt(G_g/r_g);
g_a_g= sqrt((c/a_g)^2-1);
g_b_g= sqrt((c/b_g)^2-1);
theta_g= 2*(b_g/c)^2;
A_g = k*g_a_g*dl;
B_g = k*g_b_g*dl;
C_A_g= cos(A_g);
S_A_g= sin(A_g);
C_B_g= cos(B_g);
S_B_g= sin(B_g);
Gg_inv = [theta_g*C_A_g+(1-theta_g)*C_B_g, 1i*(g_a_g*g_b_g*theta_g*S_B_g+(theta_g-1)*S_A_g)/g_a_g, (-C_A_g+C_B_g)/(c^2*r_g), 1i*(g_a_g*g_b_g*S_B_g+S_A_g)/(c^2*g_a_g*r_g);...
1i*(-g_a_g*g_b_g*theta_g*S_A_g+(1-theta_g)*S_B_g)/g_b_g, theta_g*C_B_g+(1-theta_g)*C_A_g, 1i*(g_a_g*g_b_g*S_A_g+S_B_g)/(c^2*g_b_g*r_g), (-C_A_g+C_B_g)/(c^2*r_g);...
c^2*r_g*theta_g*(theta_g-1)*(C_A_g-C_B_g), 1i*c^2*r_g*(g_a_g*g_b_g*theta_g^2*S_B_g+(theta_g-1)^2*S_A_g)/g_a_g, theta_g*C_B_g+(1-theta_g)*C_A_g, 1i*(g_a_g*g_b_g*theta_g*S_B_g+(theta_g-1)*S_A_g)/g_a_g;...
1i*c^2*r_g*(g_a_g*g_b_g*theta_g^2*S_A_g+(theta_g-1)^2*S_B_g)/g_b_g, c^2*r_g*theta_g*(theta_g-1)*(C_A_g-C_B_g), 1i*(-g_a_g*g_b_g*theta_g*S_A_g+(1-theta_g)*S_B_g)/g_b_g, theta_g*C_A_g+(1-theta_g)*C_B_g];
l_s= 2*n_s*G_s/(1-2*n_s);
a_s= sqrt((l_s+2*G_s)/r_s);
b_s= sqrt(G_s/r_s);
g_a_s= sqrt((c/a_s)^2-1);
g_b_s= sqrt((c/b_s)^2-1);
theta_s= 2*(b_s/c)^2;
A_s = k*g_a_s*d_h;
B_s = k*g_b_s*d_h;
C_A_s= cos(A_s);
S_A_s= sin(A_s);
C_B_s= cos(B_s);
S_B_s= sin(B_s);
Gs_inv = [theta_s*C_A_s+(1-theta_s)*C_B_s, 1i*(g_a_s*g_b_s*theta_s*S_B_s+(theta_s-1)*S_A_s)/g_a_s, (-C_A_s+C_B_s)/(c^2*r_s), 1i*(g_a_s*g_b_s*S_B_s+S_A_s)/(c^2*g_a_s*r_s);...
1i*(-g_a_s*g_b_s*theta_s*S_A_s+(1-theta_s)*S_B_s)/g_b_s, theta_s*C_B_s+(1-theta_s)*C_A_s, 1i*(g_a_s*g_b_s*S_A_s+S_B_s)/(c^2*g_b_s*r_s), (-C_A_s+C_B_s)/(c^2*r_s);...
c^2*r_s*theta_s*(theta_s-1)*(C_A_s-C_B_s), 1i*c^2*r_s*(g_a_s*g_b_s*theta_s^2*S_B_s+(theta_s-1)^2*S_A_s)/g_a_s, theta_s*C_B_s+(1-theta_s)*C_A_s, 1i*(g_a_s*g_b_s*theta_s*S_B_s+(theta_s-1)*S_A_s)/g_a_s;...
1i*c^2*r_s*(g_a_s*g_b_s*theta_s^2*S_A_s+(theta_s-1)^2*S_B_s)/g_b_s, c^2*r_s*theta_s*(theta_s-1)*(C_A_s-C_B_s), 1i*(-g_a_s*g_b_s*theta_s*S_A_s+(1-theta_s)*S_B_s)/g_b_s, theta_s*C_A_s+(1-theta_s)*C_B_s];
B= Gs_inv*Gg_inv;
B1= B(1,1);
B2= B(1,2);
B3= B(1,3);
B4= B(1,4);
B5= B(2,1);
B6= B(2,2);
B7= B(2,3);
B8= B(2,4);
B9= B(3,1);
B10= B(3,2);
B11= B(3,3);
B12= B(3,4);
B13= B(4,1);
B14= B(4,2);
B15= B(4,3);
B16= B(4,4);
c1= -(B1+B2);
c2= -(B3+B4);
c3= -(B5+B6);
c4= -(B7+B8);
c5= -(B9+B10);
c6= -(B11+B12);
c7= -(B13+B14);
c8= -(B15+B16);
x2_inv= [(-b_bar*c3*c8+b_bar*c4*c7+c3*c6*d_bar-c4*c5*d_bar+c5*c8-c6*c7)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (b_bar*c1*c8-b_bar*c2*c7-c1*c6*d_bar+c2*c5*d_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-b_bar*c1*c4+b_bar*c2*c3+c1*c6-c2*c5)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7);...
(a_bar*c3*c8-a_bar*c4*c7-c3*c6*c_bar+c4*c5*c_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-a_bar*c1*c8+a_bar*c2*c7+c1*c6*c_bar-c2*c5*c_bar+c5*c8-c6*c7)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (a_bar*c1*c4-a_bar*c2*c3+c3*c6-c4*c5)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7);...
(a_bar*c4*d_bar-a_bar*c8-b_bar*c4*c_bar+c6*c_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-a_bar*c2*d_bar+b_bar*c2*c_bar-b_bar*c8+c6*d_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-c2*c_bar-c4*d_bar+c8)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (a_bar*c2+b_bar*c4-c6)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7);...
(-a_bar*c3*d_bar+a_bar*c7+b_bar*c3*c_bar-c5*c_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (a_bar*c1*d_bar-b_bar*c1*c_bar+b_bar*c7-c5*d_bar)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (c1*c_bar+c3*d_bar-c7)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7), (-a_bar*c1-b_bar*c3+c5)/(a_bar*(c1*c4*d_bar-c1*c8-c2*c3*d_bar+c2*c7)+b_bar*(-c1*c4*c_bar+c2*c3*c_bar-c3*c8+c4*c7)+c_bar*(c1*c6-c2*c5)+d_bar*(c3*c6-c4*c5)+c5*c8-c6*c7)];
Y2= x2_inv*(B*[0;0;-w;w]);
u_in= (B(1,4)-B(1,3))*c*w;
mag_u_in= abs(u_in);
w_in= (B(2,4)-B(2,3))*c*w;
mag_w_in= abs(w_in);
Input= sqrt(mag_u_in^2+mag_w_in^2);
u_out= c*abs(Y2(1,1));
w_out= c*abs(Y2(2,1));
Output= sqrt(u_out^2+w_out^2);
answer = Output/Input;
end

Melden Sie sich an, um zu kommentieren.

Melden Sie sich an, um diese Frage zu beantworten.

Antworten (0)

Kategorien

Mehr zu Solver Outputs and Iterative Display finden Sie in Hilfe-Center und File Exchange

Produkte

Version

R2022a

Tags

Gefragt:

Manoj Manoj
Manoj Manoj
am 13 Mai 2024

Bearbeitet:

Torsten
Torsten
am 14 Mai 2024

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by