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fminsearch application for fitting some data

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Angelo Giuseppe Spinosa
Angelo Giuseppe Spinosa 2016 年 5 月 27 日
コメント済み: Star Strider 2016 年 5 月 27 日
Good evening to everybody. I'm trying to find a solution for the following problem. I have a function f = errorFunction(k,R,G,F,cosTheta) in a linear form:
f = (R*G*F*cosTheta)*k
I've created a function like this one below:
function optimalK = fitting(mass,gaugeFactor,resistance,theta)
initK = 1e-2;
optimalK = zeros(1,length(theta));
options = optimset('TolX',1e-8,'MaxIter',Inf,'MaxFunEvals',5000);
for i=1:length(optimalK)
cosTheta = cosd(theta(i));
optimalK(i) = fminsearch(@(k) errorFunction(k,resistance,gaugeFactor,9.81*mass,cosTheta),initK,options);
end
end
Moreover, I have a vector of angles avgCommerc that come from several measurements in which a commercial inclinometer has been used. When I call the function fitting for getting the minimum k of the function errorFunction, like explained here:
%%STEP 2 - Fitting
% Fitting requires the degrees of the commercial inclinometer on the x
% axis and the ratio deltaR/R on the y axis.
mass = 1;
gaugeFactor = 1;
resistance = 1;
optimalK = fitting(mass,gaugeFactor,resistance,avgCommerc);
disp(sprintf('\n--- STEP 2 - Polynomial fitting: COMPLETE'));
the procedure doesn't work well: it gives me the error
Exiting: Maximum number of function evaluations has been exceeded
- increase MaxFunEvals option.
Current function value: -Inf
How can I solve the problem?

回答 (2 件)

Star Strider
Star Strider 2016 年 5 月 27 日
The problem appears to be in ‘errorFunction’. You didn’t post it, so we can’t suggest a specific solution.
It would also help if you told us what you want to do as well as posting your code.
  2 件のコメント
Angelo Giuseppe Spinosa
Angelo Giuseppe Spinosa 2016 年 5 月 27 日
編集済み: Angelo Giuseppe Spinosa 2016 年 5 月 27 日
You are right, I didn't paste the code because the function errorFunction is simply:
function f = errorFunction(k,R,G,F,cosTheta)
% Linear relationship between the function f = deltaR and the
% factor k.
f = (R*G*F*cosTheta)*k;
end
My objective is to find a linear relationship as discussed before, in which k parameter is set for a dimensional compatibility between different physical quantities, like forces, gauge factors and degrees that are derived from a series of sensors. In my case, I would to fit a vector of angles (for which I compute the cosine) with such type of mathematical law.
Star Strider
Star Strider 2016 年 5 月 27 日
you’re asking fminsearch to minimise a linear function. That minimum will be -Inf, by definition.
You simply cannot escape that reality.

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Matt J
Matt J 2016 年 5 月 27 日
編集済み: Matt J 2016 年 5 月 27 日
I see no "error" calculation in your errorFunction. Presumably, it should actually be
function error = errorFunction(k,R,G,F,cosTheta,f)
% Linear relationship between the function f = deltaR and the
% factor k.
error = norm( f - (R*G*F*cosTheta)*k);
end
where f is some measurement vector.
However, it is overkill to use fminsearch for this. A linear fit can be done as simply as
k=(R*G*F*cosTheta)\f;
  2 件のコメント
Angelo Giuseppe Spinosa
Angelo Giuseppe Spinosa 2016 年 5 月 27 日
If I would to follow you suggestions, how may I change the fitting() function? Because I don't understand which is the value of f in both cases: it should be initialized, no?
Matt J
Matt J 2016 年 5 月 27 日
編集済み: Matt J 2016 年 5 月 27 日
In order to "fit" an equation you need measurements of both left and right hand side quantities. In your case, it looks like you have multiple measurements of cosTheta on the right hand side and presumably also multiple corresponding measurements of f on the left hand side.
As I said, your fitting() function could then just calculate k as,
k=(R*G*F*cosTheta(:))\f(:);

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