I have a problem with my parameters on the dynamic system model here which consist of 3 equations and 11 parameters. In the beginning, i thought when i already find the stability conditions for my model, i just need to refer the parameter values from the previous research. But the problem is the parameter value won't fit to the stability constraints obtained by the Lienard-Chipart criterion or Routh-Hurwitz criterion which makes my system unstable.
I heard of Genetic Algorithm technique can be used for this problem, but from what i read it needs experimental data and i dont have that. Does gradient descent method can be applied in this problem of finding optimal parameter? Or is this just Minimization (Optimization) problem?I think this is an optimization problem subject to constraints of stability, but does the system(model) is the objective function that i should be minimized?
Any resources, coding and/or suggestion is very much appreciated.
Thank you.
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$\begingroup$ Maybe have a look at a review of, or textbook on, numerical optimization; documentation of software libraries might also be helpful. $\endgroup$A rural reader– A rural reader2024-12-26 19:13:33 +00:00Commented Dec 26, 2024 at 19:13
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$\begingroup$ Having experimental data you can use the so called "inverse problem" techniques. See for instance math.stackexchange.com/questions/3470910/… $\endgroup$Cesareo– Cesareo2024-12-26 21:42:11 +00:00Commented Dec 26, 2024 at 21:42
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