SciML / SciML/ModelOrderReduction.jl

Frequency-Weighted Balanced Truncation

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new-algorithm
Dominant language
Julia
Stars
43
Forks
8
Avg merge
11h 47m
Merged PRs (30d)
14

Description

From the catch-all tracking issue https://github.com/SciML/ModelOrderReduction.jl/issues/78

Implement frequency-weighted balanced truncation / frequency-weighted reduction for LTI systems (distinct from unweighted BT in #4). Related Julia reference: frequency_weighted_reduction in RobustAndOptimalControl.jl.

https://people.kth.se/~hsan/modred_files/intro_modred.pdf
https://github.com/JuliaControl/RobustAndOptimalControl.jl/blob/master/src/reduction.jl
Reference list (pyMOR LTI MOR checklist): https://github.com/pymor/pymor/issues/388#issuecomment-892486556

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the catch-all issue #78, then read the frequency_weighted_reduction reference in RobustAndOptimalControl.jl and the linked model-reduction PDF. Compare the requested behavior with the unweighted balanced truncation work in #4. Done means frequency-weighted reduction is implemented for LTI systems and is distinct from unweighted BT.

Written by the indexing model from the issue text.

Assessment

Tech stack
julia
Domain
hpc
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Active
Clarity
Needs clarification
Newbie friendliness
35/100

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