# Challenges in Estimating Wind Turbine Controller Using Universal Differential Equations (UDE) Approach

**URL:** https://discourse.julialang.org/t/challenges-in-estimating-wind-turbine-controller-using-universal-differential-equations-ude-approach/113890
**Category:** Numerics
**Tags:** question, diffeq, sciml, neural-network
**Created:** [May 6, 2024, 9:42am UTC](https://discourse.julialang.org/t/challenges-in-estimating-wind-turbine-controller-using-universal-differential-equations-ude-approach/113890 "2024-05-06T09:42:32Z")
**Posts on this page:** 1
**Showing post:** 6

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### Author: ![Alvaro98](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/alvaro98/32/209043_2.png) [@Alvaro98](https://discourse.julialang.org/u/Alvaro98)
#### Post date: [May 12, 2024, 5:05pm UTC](https://discourse.julialang.org/t/challenges-in-estimating-wind-turbine-controller-using-universal-differential-equations-ude-approach/113890/6 "2024-05-12T17:05:56Z")

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I mean something like this:

> [@Training universal differential equations](https://discourse.julialang.org/t/training-universal-differential-equations/100787):
>
> Hello, In a universal differential equation where the ODE + NN is not able to finish the integration routine, Is there a procedure (best practices) to execute in order to train the ODE? If the integration procedure is not finished the evaluation of the loss will throw an error due to differences in the number of points to evaluate. This will most likely be because the estimation of the NN is not yielding good results and the system will possible become unstable. Is there a procedure to adopt …

Sometimes the training will not finish if the initialization of the weights of the two neural networks makes the system unstable. I want to initialize the weights such that the untrained neural networks produce a value of 1 for the two control variables, for example. I’ve read the responses in that thread but it is still not clear to me how to solve this.

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