fsolve error using trustnleqn (line 28)

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Bertiningrum Devi
Bertiningrum Devi el 10 de Mayo de 2019
Comentada: Bertiningrum Devi el 19 de Mayo de 2019
Hello everyone,
I'm trying to solve non linear equations system using fsolve. I'm beginner in matlab I just have no idea what's going on with my program when I tried to run it, there's an error message in the command window:
Error using trustnleqn (line 28)
Objective function is returning undefined values at initial point. FSOLVE cannot continue.
Error in fsolve (line 408)
trustnleqn(funfcn,x,verbosity,gradflag,options,defaultopt,f,JAC,...
Error in singletray (line 10)
x = fsolve(fun,x0);
what does that mean? and what am I supposed to do to get it solved?
here is the function file:
function F = equilibrium(x)
rec_a=0.7;
rec_b=0.9;
HCOin=1.72e-8;
HSin=0.1128;
a=(1-rec_a)*HCOin;
b=(1-rec_b)*HSin;
F(1)=x(1)*a/(x(2)*x(3)) - 32.1421;
F(2)=x(1)*b/(x(2)*x(4)) - 16.7567;
F(3)=x(5)/(a*x(6)) - 3.508e-13;
F(4)=x(1)*x(6)/x(2) - .32134475;
F(5)=x(7)/(x(8)*x(9)) - 2.246e10;
F(6)=x(9)*x(6) - 7.573e-11;
F(7)=x(1)+x(9)+x(7)-b-a-2*x(5)-x(6);
F(8)=2.93-x(8)-x(7);
F(9)=28.27-x(2)-x(1);
end
I run it in :
%Reactive desorption modeling
%assumption: isothermal & only 1 tray
clc;
clear;
%solving 7 unknowns
options = optimoptions('fsolve','Display','iter');
[x,fval] = fsolve(@equilibrium,[0;0;0;0;0;0;0;0;0],options);
Any help would be appreciated. Thank you so much

Respuesta aceptada

Matt J
Matt J el 10 de Mayo de 2019
Editada: Matt J el 10 de Mayo de 2019
The initial point is [0;0;0;0;0;0;0;0;0]. Calling your function at this point gives something with NaNs
>> equilibrium([0;0;0;0;0;0;0;0;0])
ans =
NaN NaN NaN NaN NaN -0.0000 -0.0113 2.9300 28.2700
because of divisions by zero. You must use a different initial point, where your function is actually defined.
  5 comentarios
Walter Roberson
Walter Roberson el 11 de Mayo de 2019
The terms used in the variable names and comments are seldom associated with negative values, so you can probably impose a lower bound of 0 for all of you values.
You divide by several of your x values, so you can probably impose a lower bound of realmin() for those, or more likely sqrt(realmin)
Bertiningrum Devi
Bertiningrum Devi el 19 de Mayo de 2019
Thank you Matt, Thank you Walter, your information helps me so much.

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