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Merge branch 'main' into analysis_points
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‎.github/workflows/Documentation.yml‎

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@@ -21,4 +21,8 @@ jobs:
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # For authentication with GitHub Actions token
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DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} # For authentication with SSH deploy key
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run: julia --project=docs/ docs/make.jl
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run: julia --project=docs/ --code-coverage=user docs/make.jl
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- uses: julia-actions/julia-processcoverage@v1
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- uses: codecov/codecov-action@v1
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with:
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file: lcov.info

‎.github/workflows/Invalidations.yml‎

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name: Invalidations
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on:
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pull_request:
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concurrency:
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# Skip intermediate builds: always.
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# Cancel intermediate builds: always.
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group: ${{ github.workflow }}-${{ github.ref }}
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cancel-in-progress: true
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jobs:
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evaluate:
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# Only run on PRs to the default branch.
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# In the PR trigger above branches can be specified only explicitly whereas this check should work for master, main, or any other default branch
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if: github.base_ref == github.event.repository.default_branch
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runs-on: ubuntu-latest
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steps:
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- uses: julia-actions/setup-julia@v1
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with:
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version: '1'
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- uses: actions/checkout@v3
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- uses: julia-actions/julia-buildpkg@v1
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- uses: julia-actions/julia-invalidations@v1
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id: invs_pr
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- uses: actions/checkout@v3
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with:
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ref: ${{ github.event.repository.default_branch }}
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- uses: julia-actions/julia-buildpkg@v1
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- uses: julia-actions/julia-invalidations@v1
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id: invs_default
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- name: Report invalidation counts
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run: |
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echo "Invalidations on default branch: ${{ steps.invs_default.outputs.total }} (${{ steps.invs_default.outputs.deps }} via deps)" >> $GITHUB_STEP_SUMMARY
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echo "This branch: ${{ steps.invs_pr.outputs.total }} (${{ steps.invs_pr.outputs.deps }} via deps)" >> $GITHUB_STEP_SUMMARY
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- name: Check if the PR does increase number of invalidations
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if: steps.invs_pr.outputs.total > steps.invs_default.outputs.total
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run: exit 1

‎Project.toml‎

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@@ -7,21 +7,20 @@ version = "1.5.0"
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IfElse = "615f187c-cbe4-4ef1-ba3b-2fcf58d6d173"
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ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
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OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
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OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
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Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"
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[compat]
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IfElse = "0.1"
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ModelingToolkit = "8"
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OffsetArrays = "1"
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OrdinaryDiffEq = "5.56, 6"
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Symbolics = "0.1, 1, 2, 3, 4"
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Symbolics = "4.9"
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julia = "1.6"
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[extras]
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ControlSystemsBase = "aaaaaaaa-a6ca-5380-bf3e-84a91bcd477e"
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OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
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SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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[targets]
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test = ["SafeTestsets", "Test", "ControlSystemsBase"]
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test = ["OrdinaryDiffEq", "SafeTestsets", "Test", "ControlSystemsBase"]

‎README.md‎

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# ModelingToolkitStandardLibrary.jl
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[![CI](https://github.com/SciML/ModelingToolkitStandardLibrary.jl/actions/workflows/CI.yml/badge.svg)](https://github.com/SciML/ModelingToolkitStandardLibrary.jl/actions/workflows/CI.yml)
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[![Join the chat at https://julialang.zulipchat.com #sciml-bridged](https://img.shields.io/static/v1?label=Zulip&message=chat&color=9558b2&labelColor=389826)](https://julialang.zulipchat.com/#narrow/stream/279055-sciml-bridged)
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[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](http://mtkstdlib.sciml.ai/stable/)
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[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](http://mtkstdlib.sciml.ai/dev/)
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[![Global Docs](https://img.shields.io/badge/docs-SciML-blue.svg)](https://docs.sciml.ai/dev/modules/ModelingToolkitStandardLibrary/)
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[![codecov](https://codecov.io/gh/SciML/ModelingToolkitStandardLibrary.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/SciML/ModelingToolkitStandardLibrary.jl)
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[![Build Status](https://github.com/SciML/ModelingToolkitStandardLibrary.jl/workflows/CI/badge.svg)](https://github.com/SciML/ModelingToolkitStandardLibrary.jl/actions?query=workflow%3ACI)
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[![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://github.com/SciML/ColPrac)
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[![SciML Code Style](https://img.shields.io/static/v1?label=code%20style&message=SciML&color=9558b2&labelColor=389826)](https://github.com/SciML/SciMLStyle)
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The ModelingToolkit Standard Library is a standard library of components to model the world and beyond.
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‎docs/src/API/mechanical.md‎

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Spring
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Damper
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IdealGear
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RotationalFriction
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```
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### Rotational Sources
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```@docs
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Torque
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```
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Speed
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```
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### Rotational Sensors
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```@docs
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AngleSensor
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SpeedSensor
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TorqueSensor
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RelSpeedSensor
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```

‎docs/src/tutorials/custom_component.md‎

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connect(Ro.n, Gnd.g)
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]
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@named model = ODESystem(connections, t, systems=[L, Ro, G, C1, C2, Nr])
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@named model = ODESystem(connections, t, systems=[L, Ro, G, C1, C2, Nr, Gnd])
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nothing # hide
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```
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‎src/Blocks/Blocks.jl‎

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The module `Blocks` contains common input-output components, referred to as blocks.
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"""
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module Blocks
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using ModelingToolkit, Symbolics, OrdinaryDiffEq
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using ModelingToolkit, Symbolics
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using IfElse: ifelse
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@parameters t

‎src/Blocks/continuous.jl‎

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# Parameters:
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- `k`: Gain
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- `w`: Angular frequency
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- `w`: [`rad/s`] Angular frequency
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- `d`: Damping
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- `x_start`: Initial value of state (output)
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- `xd_start`: Initial value of derivative of state (output)
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- `wd`: [0,1] Set-point weighting in the derivative part.
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- `Nd`: [1/s] Derivative limit, limits the derivative gain to Nd/Td. Reasonable values are ∈ [8, 20]. A higher value gives a better approximation of an ideal derivative at the expense of higher noise amplification.
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- `Ni`: `Ni*Ti` controls the time constant `Ta` of anti-windup tracking. A common (default) choice is `Ta = √(Ti*Td)` which is realized by `Ni = √(Td / Ti)`. Anti-windup can be effectively turned off by setting `Ni = Inf`.
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` `gains`: If `gains = true`, `Ti` and `Td` will be interpreted as gains with a fundamental PID transfer function on parallel form `ki=Ti, kd=Td, k + ki/s + kd*s`
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- `gains`: If `gains = true`, `Ti` and `Td` will be interpreted as gains with a fundamental PID transfer function on parallel form `ki=Ti, kd=Td, k + ki/s + kd*s`.
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# Connectors:
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- `reference`
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end
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@named input = RealInput(nin = nu)
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@named output = RealOutput(nout = ny)
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@variables x[1:nx](t) = x_start
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@variables x(t)[1:nx] = x_start
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# pars = @parameters A=A B=B C=C D=D # This is buggy
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eqs = [ # FIXME: if array equations work
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[Differential(t)(x[i]) ~ sum(A[i, k] * x[k] for k in 1:nx) +

‎src/Blocks/utils.jl‎

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if nin == 1
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@variables u(t)=u_start [input = true]
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else
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@variables u[1:nin](t)=u_start [input = true]
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@variables u(t)[1:nin]=u_start [input = true]
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u = collect(u)
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end
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ODESystem(Equation[], t, [u...], []; name = name)
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if nout == 1
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@variables u(t)=u_start [output = true]
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else
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@variables u[1:nout](t)=u_start [output = true]
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@variables u(t)[1:nout]=u_start [output = true]
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u = collect(u)
2929
end
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ODESystem(Equation[], t, [u...], []; name = name)
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"""
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SISO(;name, u_start=0.0, y_start=0.0)
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Single Input Single Output continuous control block.
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Single input single output (SISO) continuous system block.
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# Parameters:
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- `u_start`: Initial value for the input
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"""
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MIMO(;name, nin=1, nout=1, u_start=zeros(nin), y_start=zeros(nout))
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Base class for a multiple Input multiple Output continuous control block.
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Base class for a multiple input multiple output (MIMO) continuous system block.
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- `nin`: Input dimension
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@named input = RealInput(nin = nin, u_start = u_start)
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@named output = RealOutput(nout = nout, u_start = y_start)
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@variables begin
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u[1:nin](t) = u_start
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y[1:nout](t) = y_start
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u(t)[1:nin] = u_start
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y(t)[1:nout] = y_start
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end
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eqs = [
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[u[i] ~ input.u[i] for i in 1:nin]...,

‎src/Electrical/Electrical.jl‎

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"""
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module Electrical
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using ModelingToolkit, Symbolics, IfElse, OrdinaryDiffEq
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using ModelingToolkit, Symbolics, IfElse
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using OffsetArrays
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@parameters t

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