Skip to content

Regularisation on state trajectory #154

Description

@CasBex

The identification methods in this package allow adding a regularisation term to the loss for better convergence. It would be nice if we could regularise not only the parameters and obtained system but also on the simulated trajectory. This would allow punishing states which are physically nonsensical (temperatures below 0K...) which would allow some form of "physics-informed system identification" to obtain systems with physically sensible non-observable states. This could be done by adding an argument to the regularisation function in state space identification methods (e.g. going from regularizer = (p, P) -> 0 to regularizer = (p, P, simresult) -> 0).

Activity

  1. baggepinnen commented on Jul 9, 2024

    @baggepinnen
    Member

    Thanks for the feature request! Check out the PR #155, I hope it addresses your request

  2. CasBex commented on Jul 9, 2024

    @CasBex
    Author

    I'll have a look later today, thanks for the quick response

  3. CasBex commented on Jul 9, 2024

    @CasBex
    Author

    Alright, I've tested it and it seems to work. Weighting the various regularisation terms in my problem to get a good result remains rather difficult, but I guess that's application dependent.

    Will you include this in the other state-space models as well or only structured_pem?

  4. baggepinnen commented on May 13, 2026

    @baggepinnen
    Member

    For closure, user-provided regularization cannot easily be added to other methods since they use a black-box basis which the user cannot reason about.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Projects

    No projects

      Milestone

      No milestone

      Relationships

      None yet

      Development

      No branches or pull requests

      Issue actions