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Example

Assumptions:

ClearAll[m, F, b, \[Omega], \[Delta]]
$Assumptions = x > 0 && m > 0 && F > 0 && b > 0 && \[Omega] > 0 && \[Delta] > 0;

In the following, $m$ is the mass of the mechanical system and $\delta$ is the phaseshift of the system.

m = 0.17869 + 0.01376/3;
\[Delta] = ArcTan[b/(m*(\[Omega]^2 - x^2))*x];

The experimental data:

data = {{0.7123448644,0.00246},{0.7324185582,0.00266},{0.7861292525,0.00328},{0.8523181889,0.00451},{0.9109116735,0.00647},{0.9282727060,0.00760},{0.9906639165,0.0114},{1.025928514,0.0152},{1.051970063,0.0222},{1.079096676,0.0131},{1.105138225,0.00865},{1.149625870,0.00549},{1.170242096,0.00455},{1.220155065,0.00336},{1.256504727,0.00267},{1.351990405,0.00184}};

The fitting function:

A[x_] := F/(m*\[Omega]^2*
     Sqrt[   (x - \[Delta])^4 
           + ((b/(m*\[Omega]))^2 - 2)*(x - \[Delta])^2 
           + 1])

where $F$, $b$, and $\omega$ are parameters connected to the system.

Determineing the missing parameters:

FindFit[data, A[x], {F, b, \[Omega]}, x]

{F -> 0.00584067, b -> 0.972727, [Omega] -> -1.10514}

F = 0.005840667856395345;
b = 0.9727272619465833;
\[Omega] = -1.105138224999997;

Plot of data and the fitting curve:

Show[Plot[A[x], {x, 0.6, 1.5}, PlotRange -> Full], ListPlot[data, PlotStyle -> Red]]

output

It is obvious that the fitting is all wrong.

How do I get the correct fitting parameters?

I know that the fit should give approximately

F = 0.03
b = 0.14
\[Omega] = 12

P.S. I would think that executing the first command would assure that $\omega > 0$ when finding the fitting parameters, but this is obviously not the case.

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  • 1
    $\begingroup$ There are not enough degrees of freedom in your model to accommodate this shift. Try with Manipulate to see what I mean. $\endgroup$
    – Oleksandr R.
    Jan 2, 2014 at 0:50
  • $\begingroup$ @OleksandrR. So I can't get a correct fit with the data available? $\endgroup$
    – Svend Tveskæg
    Jan 2, 2014 at 1:00
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    $\begingroup$ Apparently not, unless you modify the model to incorporate that small shift. How best to do that while retaining its physical validity (looks like some resonant mechanical system?) will depend on how the measurements are done and so on, and we can't really help you with that for obvious reasons. If these are experimental data, is it possible for example that all readings of x are slightly shifted due to an instrumental effect? Or maybe they're subject to a multiplicative error... $\endgroup$
    – Oleksandr R.
    Jan 2, 2014 at 1:07
  • $\begingroup$ @OleksandrR. I have updated my question. (It is indeed a mechanical system and one can get a phaseshift in order to horizontally correct the fitting function.) $\endgroup$
    – Svend Tveskæg
    Jan 2, 2014 at 6:05
  • $\begingroup$ @Nasser Can I make you write up an answer where the correct fit is obtained? (I have to go now and won't be back for the next 18-20 hours.) $\endgroup$
    – Svend Tveskæg
    Jan 2, 2014 at 15:07

1 Answer 1

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Although you haven't specified everything, here is one way to approach this:

a[x_] := F/(m*ω^2*Sqrt[(x - δ)^4 + ((b/(m*ω))^2 - 2)*(x - δ)^2 + 1]);
sol = NonlinearModelFit[data, a[x], 
   {{F, 0.03}, {b, 0.14}, {ω, 12}, {δ, 1}, {m, 0.17869 + 0.01376/3}}, x];
Show[ListPlot[data], Plot[sol[x], {x, 0.7, 1.4}]]

enter image description here

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