JuliaControl / JuliaControl/ControlSystems.jl

Differentiable control design

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help wanted
Dominant language
Julia
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Merged PRs (30d)
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Description

A number of functions in this package and in RobustAndOptimalControl.jl fail when trying to compute gradients through them using ForwardDiff or Zygote. This issue tries to summarize the current status

Problematic functions
Function AD package Comment
c2d ForwardDiff :zoh requires exp!(::Matrix{Dual}). ForwardDiffChainRules buggy, but manual implementation possible. #844
feedback Zygote try/catch and @warn
are All Handled through ImplicitDiff #844
hinfnorm ForwardDiff Non-smooth. Works for Zygote. See tests for comments and comment. ForwardDiff in #844 but not for MIMO
svd/qr/schur ForwardDiff DifferentiableFactorizations.jl may be helpful
hessenberg ForwardDiff, ReverseDiff GenericLinearAlgebra.Hessenberg has different fieldnames from LinearAlgebra.Hessenberg

c2d example failing

foo(x) = sum(exp(reshape(x, 2, 2)))
v = randn(4)
using ForwardDiff
ForwardDiff.gradient(foo, v)

ERROR: MethodError: no method matching exp(::Matrix{ForwardDiff.Dual...
Related issues:

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 listed problematic functions—especially c2d, feedback, are, hinfnorm, and hessenberg—and reproduce the c2d example using ForwardDiff.gradient. Read the linked ControlSystems.jl pull request, RobustAndOptimalControl.jl test_hinfgrad.jl, and related issue 57; done would require resolving the documented automatic-differentiation failures across the affected functions and packages.

Written by the indexing model from the issue text.

Assessment

Tech stack
julia
Domain
backend
Issue type
Bug
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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