Non-linear least squares estimation with linear constraints in Simulink?
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I'm trying to implement a non-linear least squares solver in Simulink, with linear constraints. However, it seems that only the 'levenberg-marquardt' algorithm can be used in Simulink, which does not have the facility to add linear constraints.
I get the following error message when I try to use the 'interior-point' algorithm:
OPTIMOPTIONS property 'Algorithm' must be one of the following values for lsqcurvefit:
'levenberg-marquardt'
My code is:
options = optimoptions('lsqcurvefit', 'Algorithm', 'interior-point');
x = lsqcurvefit(fun, x0, Q, P, lb, ub, options);
This problem does not occur when I use the lsqcurvefit function in a regular MATLAB script.
Do you have any advice on how I could implement a non-linear least squares solver with linear constraints in Simulink?
Many thanks.
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Torsten
2024년 11월 11일
편집: Torsten
2024년 11월 11일
I vaguely remember that using "lsqcurvefit" within Simulink requires to use the Levenberg-Marquardt algorithm. I can't answer why this is the case (if you are interested, you should ask Technical Support), but you simply have to accept this. But you only seem to have lower and upper bounds on the variables
x = lsqcurvefit(fun, x0, Q, P, lb, ub, options);
- so why don't you try Levenberg-Marquard ?
If this algorithm within "lsqcurvefit" doesn't succeed, what about using "fmincon" instead ?
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Torsten
2024년 11월 11일
If you use
sum((yexp-ysim).^2)
as objective function for "fmincon", you should get the same solution as if you specify
yexp-ysim
in "lsqnonlin" or
ysim
in "lsqcurvefit".
I don't know if special algorithms are excluded if you use "fmincon" within Simulink. Just test it.
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