Parameter estimation Grey-box modeling: Difference between 'lsqnonlin' / 'fmincon' / 'greyest'

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Dear Community,
could anybody please explain me the difference between 'lsqnonlin' / 'fmincon' / 'greyest' in content with Parameter Estimation of Grey-Box models (RC-models)?
Thank you in advance.

Answers (1)

Udit06
Udit06 on 22 Nov 2024 at 8:26
Hi Verena,
Each method uniquely addresses different modeling and optimization requirements.
greyest is designed for linear grey-box models with a known structure, making it highly effective for system identification by using input-output data to estimate parameters.
On the other hand, fmincon serves as a flexible nonlinear optimization tool, ideal for tackling problems with complex constraints by minimizing a scalar objective function within specified bounds.
In contrast, lsqnonlin is adept at handling nonlinear least-squares challenges, concentrating on reducing the sum of squared residuals, which makes it particularly well-suited for curve fitting tasks that do not involve extensive constraints.
You can refer to the following MathWorks documentations for more details:
I hope this helps.

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