fsolve error using trustnleqn (line 28)
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Bertiningrum Devi
on 10 May 2019
Commented: Bertiningrum Devi
on 19 May 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
0 Comments
Accepted Answer
Matt J
on 10 May 2019
Edited: Matt J
on 10 May 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 Comments
Walter Roberson
on 11 May 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)
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