Parameterized odesolve solve block?

[rgunwaldsen]

I am trying to fit data to a "First Order Plus Dead Time" model. I can optimize the fit by using the solution to the FOPDT equation, but, simply as an intellectual exercise, I would like to also be able to do this using the FOPDT differential equation. I have Python code that can do this (it takes an incredibly long time to run; I would guess that Mathcad would take much more time).

The nub problem of the problem as I see it, is that I think I need an optimization solve block to do the least squares fit which, in turn, then needs to call an odesolve solve block with parameters.

I quickly realized that I don't have a clue as to how to do this, and I haven't found any "parameterized solve block" examples that return odesolve solutions.

Attached are my Prime 6 worksheet, text file of data, and PDF of worksheet.

Many thanks,

Roger Gunwaldsen

[Werner_E]

Something like the attached?

[rgunwaldsen · Accepted solution]

Thanks,  Werner!

[FDS]

Werner, would it be possible to attach your file as a mathcad 15 file or pdf? Thank you in advance!

[Werner_E]

Unfortunately there is no way to convert a Prime file to real Mathcad format.

Attached is a pdf print of the file. I only made the few changes to the original file that are highlighted in yellow just to show how the solve block could be parametrized.

[FDS]

Thank you!

[rgunwaldsen]

FWIW,   here is my final P6 worksheet which utilizes Werner's  suggestion plus a modified optimization to be able to repetitively call the odesolve block.

[Werner_E]

Shame on me!

In my sheet y.ode never changes and uses just the guess values!

I forgot to make y.ode dependent on the current values of K, theta and tau 😞