From af1e2d5e73343bd9f1cf8210d9d8701228534726 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 12:07:54 -0800 Subject: [PATCH 01/19] first pass at CI testing --- .github/workflows/TagBot.yml | 11 --------- .github/workflows/ci_testing.yml | 40 ++++++++++++++++++++++++++++++++ 2 files changed, 40 insertions(+), 11 deletions(-) delete mode 100644 .github/workflows/TagBot.yml create mode 100644 .github/workflows/ci_testing.yml diff --git a/.github/workflows/TagBot.yml b/.github/workflows/TagBot.yml deleted file mode 100644 index d77d3a0..0000000 --- a/.github/workflows/TagBot.yml +++ /dev/null @@ -1,11 +0,0 @@ -name: TagBot -on: - schedule: - - cron: 0 * * * * -jobs: - TagBot: - runs-on: ubuntu-latest - steps: - - uses: JuliaRegistries/TagBot@v1 - with: - token: ${{ secrets.GITHUB_TOKEN }} diff --git a/.github/workflows/ci_testing.yml b/.github/workflows/ci_testing.yml new file mode 100644 index 0000000..52b5505 --- /dev/null +++ b/.github/workflows/ci_testing.yml @@ -0,0 +1,40 @@ +name: build + +on: + push: + branches: [main] + pull_request: + branches: [main] + +concurrency: + group: 'Controlz' + cancel-in-progress: true + +jobs: + unit-and-doc-tests: + runs-on: ubuntu-latest + timeout-minutes: 30 + + steps: + - name: checkout commit + uses: actions/checkout@main + + - name: set up Julia + uses: julia-actions/setup-julia@latest + with: + version: '1.7.1' + + - name: build package + uses: julia-actions/julia-buildpkg@latest + + - name: run tests + run: julia --project --color=yes -e 'import Pkg; Pkg.test()' + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} + DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} + + - name: build and deploy docs + run: julia --project --color=yes ./docs/make.jl + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} + DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} From 98ea62d9cac9bb5065f06e6fc6ee5cd782d58f6e Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 12:36:18 -0800 Subject: [PATCH 02/19] update project.toml --- Project.toml | 18 ++--- src/development.ipynb | 165 ------------------------------------------ src/hipster.mplstyle | 12 --- 3 files changed, 9 insertions(+), 186 deletions(-) delete mode 100644 src/development.ipynb delete mode 100644 src/hipster.mplstyle diff --git a/Project.toml b/Project.toml index 9f3c86f..e56a782 100644 --- a/Project.toml +++ b/Project.toml @@ -1,7 +1,7 @@ name = "Controlz" uuid = "e034abe6-471a-4d54-96dd-ecd1f4022419" authors = ["SimonEnsemble "] -version = "0.2.1" +version = "0.3.0" [deps] DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa" @@ -9,17 +9,17 @@ DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59" Polynomials = "f27b6e38-b328-58d1-80ce-0feddd5e7a45" Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7" -PyPlot = "d330b81b-6aea-500a-939a-2ce795aea3ee" Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665" +CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0" [compat] -DifferentialEquations = "^6.16.0" -DataFrames = "^0.22.1" -Interpolations = "^0.13.1" -Polynomials = "^0.6.1" -PyPlot = "^2.9.0" -julia = "^1.5" -Roots = "0.8.4" +DifferentialEquations = "^0.7.0" +DataFrames = "^1.3.1" +Interpolations = "^0.13.5" +Polynomials = "^2.0.22" +julia = "^1.7" +Roots = "^1.3.13" +CairoMakie = "^0.6.6" [extras] Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4" diff --git a/src/development.ipynb b/src/development.ipynb deleted file mode 100644 index 4daa76a..0000000 --- a/src/development.ipynb +++ /dev/null @@ -1,165 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "┌ Info: Precompiling Controlz [e034abe6-471a-4d54-96dd-ecd1f4022419]\n", - "└ @ Base loading.jl:1273\n" - ] - } - ], - "source": [ - "using Polynomials\n", - "push!(LOAD_PATH, pwd())\n", - "using Controlz\n", - "using Test\n", - "using DifferentialEquations\n", - "using Logging\n", - "using DataFrames\n", - "using LaTeXStrings\n", - "using PyPlot\n", - "PyPlot.matplotlib.style.use(\"hipster.mplstyle\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = 4 / (4 * s ^ 2 + 0.8 * s + 1)\n", - "u = 1 / s\n", - "t, y = simulate(g * u, (0.0, 50.0))\n", - "\n", - "viz_response(t, y, plot_title=\"SO underdamped step response\")\n", - "savefig(\"../docs/src/example_response.png\", format=\"png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = (s + 2) / (s^2 + 1/4)\n", - "viz_poles_and_zeros(g)\n", - "savefig(\"../docs/src/example_poles_and_zeros.png\", format=\"png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = 1 / (s^2 + s + 1) # https://en.wikipedia.org/wiki/Nyquist_stability_criterion\n", - "nyquist_diagram(g)\n", - "savefig(\"../docs/src/example_nyquist.png\", format=\"png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g_ol = 4 / (s + 3) / (s + 2) / (s + 1)\n", - "\n", - "root_locus(g_ol)\n", - "savefig(\"../docs/src/example_root_locus.png\", format=\"png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = 3 / (s+1)\n", - "\n", - "bode_plot(g)\n", - "savefig(\"../docs/src/example_bode.png\", format=\"png\")" - ] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.3.0", - "language": "julia", - "name": "julia-1.3" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.3.0" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/src/hipster.mplstyle b/src/hipster.mplstyle deleted file mode 100644 index d7cab75..0000000 --- a/src/hipster.mplstyle +++ /dev/null @@ -1,12 +0,0 @@ -font.size : 16 -axes.grid : True -grid.linestyle : -- -axes.facecolor : (1.0, 1.0, 0.94) -lines.linewidth : 3 -font.family : Ubuntu Mono -axes.edgecolor : (0.3, 0.3, 0.3) -text.color : (0.3, 0.3, 0.3) -axes.labelcolor : (0.3, 0.3, 0.3) -xtick.color : (0.3, 0.3, 0.3) -ytick.color : (0.3, 0.3, 0.3) -axes.prop_cycle : cycler('color', [(0.2, 0.8, 0.2), (0.12, 0.56, 1.0), (0.9765625, 0.5, 0.4453125), (0.57421875, 0.4375, 0.85546875), (0.64, 0.64, 0.64)]) From fd8fbdd15572781b20b54a92348871c7d0974281 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 12:37:51 -0800 Subject: [PATCH 03/19] project toml fix --- Project.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Project.toml b/Project.toml index e56a782..d11c7a3 100644 --- a/Project.toml +++ b/Project.toml @@ -13,7 +13,7 @@ Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665" CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0" [compat] -DifferentialEquations = "^0.7.0" +DifferentialEquations = "^7.0.0" DataFrames = "^1.3.1" Interpolations = "^0.13.5" Polynomials = "^2.0.22" From 433c361da7d4a6b187dfc59bcf2fc1f61ed65092 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 13:15:34 -0800 Subject: [PATCH 04/19] compiles and tests run! --- src/Controlz.jl | 6 +++--- src/beavs_theme.jl | 51 +++++++++++++++++++++++++++++++++++++++++++++ src/closed_loops.jl | 6 +++--- src/show.jl | 2 +- src/systems.jl | 2 +- src/tf.jl | 28 ++++++++++++------------- src/viz.jl | 32 ++++++++++++++-------------- test/runtests.jl | 12 +++++------ 8 files changed, 94 insertions(+), 45 deletions(-) create mode 100644 src/beavs_theme.jl diff --git a/src/Controlz.jl b/src/Controlz.jl index 295285f..8d6a75c 100644 --- a/src/Controlz.jl +++ b/src/Controlz.jl @@ -2,14 +2,14 @@ module Controlz using Polynomials using DifferentialEquations -using PyPlot using Interpolations using Printf using Roots using DataFrames +using CairoMakie -# hipster plot theme -PyPlot.matplotlib.style.use(normpath(joinpath(pathof(Controlz), "..", "hipster.mplstyle"))) +# TODO set plot theme +include("beavs_theme.jl") include("tf.jl") include("special_tfs.jl") diff --git a/src/beavs_theme.jl b/src/beavs_theme.jl new file mode 100644 index 0000000..31b1a5b --- /dev/null +++ b/src/beavs_theme.jl @@ -0,0 +1,51 @@ +set_theme!( + Theme( + palette = (color=[c for c in ColorSchemes.Dark2_5], marker=[:circle, :utriangle, :cross, :rect, :diamond, :dtriangle, :pentagon, :xcross]), + textcolor = :gray40, + linewidth=4, + fontsize=20, + font="Courier", + resolution = (520, 400), + Axis = ( + backgroundcolor = RGB(0.96, 1.0, 0.98), + xgridcolor = (:black, 0.15), + ygridcolor = (:black, 0.15), + leftspinevisible = false, + rightspinevisible = false, + ygridstyle=:dash, + xgridstyle=:dash, + bottomspinevisible = false, + topspinevisible = false, + xminorticksvisible = false, + yminorticksvisible = false, + xticksvisible = false, + yticksvisible = false, + xlabelpadding = 3, + ylabelpadding = 3 + ), + Legend = ( + framevisible = true, + titlehalign=:left, + titlesize=16, + labelsize=16, + framecolor=(:black, 0.5) + # padding = (1, 0, 0, 0), + ), + Axis3 = ( + xgridcolor = (:black, 0.07), + ygridcolor = (:black, 0.07), + zgridcolor = (:black, 0.07), + xspinesvisible = false, + yspinesvisible = false, + zspinesvisible = false, + xticksvisible = false, + yticksvisible = false, + zticksvisible = false, + ), + Colorbar = ( + ticksvisible = false, + spinewidth = 0, + ticklabelpad = 5, + ) + ) +) diff --git a/src/closed_loops.jl b/src/closed_loops.jl index a7145ae..1a44f0b 100644 --- a/src/closed_loops.jl +++ b/src/closed_loops.jl @@ -43,11 +43,11 @@ end # p_b(s) + p_c(s) e^ {-ϕs} struct CLTFStandard # numerator - p_a::Poly + p_a::Polynomial θ::Union{Float64, Int} # denominator - p_b::Poly - p_c::Poly + p_b::Polynomial + p_c::Polynomial ϕ::Union{Float64, Int} end diff --git a/src/show.jl b/src/show.jl index d37a96a..785aed0 100644 --- a/src/show.jl +++ b/src/show.jl @@ -1,7 +1,7 @@ """ Convert a polynomial to a string for printing. """ -function poly_to_string(poly::Poly) +function poly_to_string(poly::Polynomial) io = IOBuffer(); printpoly(io, poly, descending_powers=true) return String(take!(io)) diff --git a/src/systems.jl b/src/systems.jl index 2270410..b0f0ede 100644 --- a/src/systems.jl +++ b/src/systems.jl @@ -9,7 +9,7 @@ The characteristic polynomial is $1+g_{ol}(s)$. The roots of the characteristic * `g_ol::TransferFunction`: open loop transfer function # Returns -a polynomial of type `Poly` +a polynomial of type `Polynomial` # Example ``` diff --git a/src/tf.jl b/src/tf.jl index f20fb12..75dc116 100644 --- a/src/tf.jl +++ b/src/tf.jl @@ -20,23 +20,23 @@ tf = TransferFunction([4], [2, 1], 2.2) ``` # Attributes -* `numerator::Poly`: the polynomial in the numerator of the transfer function -* `denominator::Poly`: the polynomial in the denominator of the transfer function +* `numerator::Polynomial`: the polynomial in the numerator of the transfer function +* `denominator::Polynomial`: the polynomial in the denominator of the transfer function * `time_delay::Float64`: the associated time delay """ struct TransferFunction - numerator::Poly - denominator::Poly + numerator::Polynomial + denominator::Polynomial time_delay::Union{Float64, Int} end ArrayOfReals = Union{Array{Float64, 1}, Array{Int64, 1}} TransferFunction(num::ArrayOfReals, den::ArrayOfReals) = - TransferFunction(Poly(reverse(num), :s), Poly(reverse(den), :s), 0.0) + TransferFunction(Polynomial(reverse(num), :s), Polynomial(reverse(den), :s), 0.0) TransferFunction(num::ArrayOfReals, den::ArrayOfReals, td::Union{Float64, Int}) = - TransferFunction(Poly(reverse(num), :s), Poly(reverse(den), :s), td) + TransferFunction(Polynomial(reverse(num), :s), Polynomial(reverse(den), :s), td) const s = TransferFunction([1, 0], [1]) @@ -201,19 +201,17 @@ zeros_poles_k(tf::TransferFunction) = _zeros(tf), _poles(tf), _k(tf) function zeros_poles_k(zeros::Array, poles::Array, k::Union{Float64, Int}; time_delay::Union{Int64, Float64}=0) # construct numerator polynomial - top = length(zeros) == 0 ? Poly(1.0, :s) : poly(zeros, :s) + top = length(zeros) == 0 ? Polynomial(1.0, :s) : fromroots(zeros, var=:s) # construct denominator polynomial - bottom = length(poles) == 0 ? Poly(1.0, :s) : poly(poles, :s) - - # ^ poly is from Polynomails.jl and means "construct polynomial with these roots" + bottom = length(poles) == 0 ? Polynomial(1.0, :s) : fromroots(poles, var=:s) # owing to numerical errors, the coeff's could be imaginary with tiny imaginary parts # let's check that the imaginary parts are tiny, then convert the coefficients to real. - @assert maximum(abs.(imag.(top.a))) < 1e-6 - @assert maximum(abs.(imag.(bottom.a))) < 1e-6 - top = Poly(real.(top.a), :s) # reconstruct a polynomial with real coeffs - bottom = Poly(real.(bottom.a), :s) + @assert maximum(abs.(imag.(top.coeffs))) < 1e-6 + @assert maximum(abs.(imag.(bottom.coeffs))) < 1e-6 + top = Polynomial(real.(top.coeffs), :s) # reconstruct a polynomial with real coeffs + bottom = Polynomial(real.(bottom.coeffs), :s) return TransferFunction(k * top, bottom, time_delay) end @@ -242,7 +240,7 @@ evaluate(tf, 2.0 + 3.0im) # also takes imaginary numbers as input ``` """ function evaluate(tf::TransferFunction, z::Number) - return polyval(tf.numerator, z) / polyval(tf.denominator, z) * exp(-tf.time_delay * z) + return tf.numerator(z) / tf.denominator(z) * exp(-tf.time_delay * z) end """ diff --git a/src/viz.jl b/src/viz.jl index 15c23be..60ee943 100644 --- a/src/viz.jl +++ b/src/viz.jl @@ -17,9 +17,9 @@ e.g. `xlim([0, 1])` can be applied after `viz_response`. # Arguments * `data::DataFrame`: data frame of time series data, containing a `:t` column for times and `:output` column for the outputs. -* `plot_title::Union{String, LaTeXString}`: title of plot -* `plot_xlabel::Union{String, LaTeXString}`: x-label -* `plot_ylabel::Union{String, LaTeXString}`: y-label +* `plot_title::String`: title of plot +* `plot_xlabel::String`: x-label +* `plot_ylabel::String`: y-label * `savename::Union{Nothing, String}`: filename to save as a figure in .png format (dpi 250). # Example @@ -31,13 +31,13 @@ viz_response(data) ``` """ function viz_response(data::DataFrame; - plot_title::Union{String, LaTeXString}="", - plot_xlabel::Union{String, LaTeXString}=L"time, $t$", - plot_ylabel::Union{String, LaTeXString}=L"output, $y(t)$", + plot_title::String="", + plot_xlabel::String=L"time, $t$", + plot_ylabel::String=L"output, $y(t)$", savename::Union{Nothing, String}=nothing ) - figure() + fig = Figure() plot(data[:, :t], data[:, :output], zorder=100) xlabel(plot_xlabel) ylabel(plot_ylabel) @@ -61,7 +61,7 @@ plot the zeros and poles of the transfer function `tf` in the complex plane. function viz_poles_and_zeros(tf::TransferFunction) z, p, k = zeros_poles_gain(tf) - figure() + fig = Figure() scatter(real.(z), imag.(z), marker="o", label="zeros", color="C1", zorder=100, s=50) scatter(real.(p), imag.(p), marker="x", label="poles", color="C2", s=50, zorder=100) legend() @@ -85,7 +85,7 @@ function nyquist_diagram(tf::TransferFunction; nb_pts::Int=500, ω_max::Float64= g_iω_neg = [evaluate(tf, ω_i * im) for ω_i in ω_neg] g_iω_pos = [evaluate(tf, ω_i * im) for ω_i in ω_pos] - figure() + fig = Figure() plot(real(g_iω_neg), imag(g_iω_neg), zorder=100) plot(real(g_iω_pos), imag(g_iω_pos), zorder=100) draw_axes() @@ -147,7 +147,7 @@ function root_locus(g_ol::TransferFunction; end end - figure() + fig = Figure() # plot poles; corresponds to Kc = 0 scatter(real.(p), imag.(p), marker="x", label="poles", color="k", s=50, zorder=100) @@ -225,15 +225,15 @@ the .gif is saved as a file `savename`. # Arguments * `data::DataFrame`: data frame of time series data, containing a `:t` column for times and `:output` column for the outputs. -* `plot_title::Union{String, LaTeXString}`: title of plot -* `plot_xlabel::Union{String, LaTeXString}`: x-label -* `plot_ylabel::Union{String, LaTeXString}`: y-label +* `plot_title::String`: title of plot +* `plot_xlabel::String`: x-label +* `plot_ylabel::String`: y-label * `savename::String`: filename to save as a .gif. .gif extension automatically appended if not provided. """ function mk_gif(t::Array{Float64}, y::Array{Float64}; - plot_title::Union{String, LaTeXString}="", - plot_xlabel::Union{String, LaTeXString}=L"time, $t$", - plot_ylabel::Union{String, LaTeXString}=L"output, $y(t)$", + plot_title::String="", + plot_xlabel::String=L"time, $t$", + plot_ylabel::String=L"output, $y(t)$", savename::String="response.gif" ) if length(t) > 999 diff --git a/test/runtests.jl b/test/runtests.jl index 4bd2ae9..5570345 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -13,8 +13,8 @@ const s = TransferFunction([1, 0], [1]) @test TransferFunction([1], [3, 2], 0.0) == TransferFunction([1], [3, 2]) tf = TransferFunction([1], [3, 2], 3.2) @test tf.time_delay == 3.2 - @test tf.numerator == Poly([1], :s) - @test tf.denominator == Poly([2, 3], :s) # reverse order + @test tf.numerator == Polynomial([1], :s) + @test tf.denominator == Polynomial([2, 3], :s) # reverse order # special constructors @test first_order_system(5.0, 8.0) == 5 / (8 * s + 1) @test second_order_system(5.0, 8.0, 0.1) == 5 / (8^2 * s^2 + 2*8*0.1*s + 1) @@ -219,7 +219,7 @@ const s = TransferFunction([1, 0], [1]) # characteristic eqn. ### g_ol = 4 / (s + 3) / (s + 2) / (s + 1) - @test isapprox(characteristic_polynomial(g_ol), Poly([10.0, 11, 6, 1], :s)) + @test isapprox(characteristic_polynomial(g_ol), Polynomial([10.0, 11, 6, 1], :s)) ### # order @@ -439,9 +439,9 @@ end # test conversion into standard form cls = Controlz.CLTFStandard(cl) - @test cls.p_a ≈ Poly([3, 300], :s) - @test cls.p_b ≈ Poly([1, 101, 100], :s) - @test cls.p_c ≈ Poly([18, 18], :s) + @test cls.p_a ≈ Polynomial([3, 300], :s) + @test cls.p_b ≈ Polynomial([1, 101, 100], :s) + @test cls.p_c ≈ Polynomial([18, 18], :s) @test cls.ϕ ≈ 1.0 @test cls.θ ≈ 5.0 From 71dd17a4de25c525232903e55057d6e940f27172 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 17:25:56 -0800 Subject: [PATCH 05/19] start on viz to makie --- Project.toml | 4 + docs/src/index.md | 7 +- examples/examples.jl | 186 +++++++++++++++++++++++++++++++++++++++++++ src/Controlz.jl | 9 ++- src/beavs_theme.jl | 51 ------------ src/viz.jl | 146 ++++++++++++++++----------------- 6 files changed, 273 insertions(+), 130 deletions(-) create mode 100644 examples/examples.jl delete mode 100644 src/beavs_theme.jl diff --git a/Project.toml b/Project.toml index d11c7a3..8481eca 100644 --- a/Project.toml +++ b/Project.toml @@ -11,6 +11,8 @@ Polynomials = "f27b6e38-b328-58d1-80ce-0feddd5e7a45" Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7" Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665" CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0" +ColorSchemes = "35d6a980-a343-548e-a6ea-1d62b119f2f4" +Colors = "5ae59095-9a9b-59fe-a467-6f913c188581" [compat] DifferentialEquations = "^7.0.0" @@ -20,6 +22,8 @@ Polynomials = "^2.0.22" julia = "^1.7" Roots = "^1.3.13" CairoMakie = "^0.6.6" +ColorSchemes = "^3.15.0" +Colors = "^0.12.8" [extras] Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4" diff --git a/docs/src/index.md b/docs/src/index.md index 414ce83..c53d113 100644 --- a/docs/src/index.md +++ b/docs/src/index.md @@ -1,6 +1,6 @@ # Controlz.jl -`Controlz.jl` is a [Julia](https://julialang.org/) package to analyze and simulate process dynamics and control systems using transfer function representations. +`Controlz.jl` is a pure-[Julia](https://julialang.org/) package to analyze and simulate process dynamics and control systems using transfer function representations. for example, to simulate the unit step response of a second-order, underdamped system characterized by the transfer function @@ -24,7 +24,6 @@ viz_response(data, plot_title="SO underdamped step response") # install the `Controlz.jl` package in Julia -* in the Julia REPL: go into package mode by typing `]`. then `add Controlz`. then `Backspace` to exit package mode. -* in a Jupyter or Pluto Notebook: `using Pkg; Pkg.add("Controlz")`. (this way also works in the REPL) +`Controlz.jl` is an officially registered Julia package. install in the Julia REPL by typing `]` to go into package mode, then `add Controlz`. -for visualizations, `Controlz.jl` relies on `PyPlot.jl`, a Julia interface to matplotlib in Python. see [here](https://github.com/JuliaPy/PyPlot.jl) if you have trouble installing `PyPlot.jl`. +I highly recommend using interactive [Pluto notebooks](https://github.com/fonsp/Pluto.jl) for coding in Julia, whose automatic package manager installs `Controlz.jl` upon running `using Controlz`. diff --git a/examples/examples.jl b/examples/examples.jl new file mode 100644 index 0000000..0a1fcfd --- /dev/null +++ b/examples/examples.jl @@ -0,0 +1,186 @@ +### A Pluto.jl notebook ### +# v0.17.4 + +using Markdown +using InteractiveUtils + +# ╔═╡ 4952d2aa-6b42-11ec-15ea-ed5764c1810b +import Pkg; Pkg.activate() + +# ╔═╡ 5da3e954-e940-45a7-b355-45e78b5ce38b +using Controlz, DataFrames, CairoMakie, ColorSchemes, Colors + +# ╔═╡ ecab99c5-d929-4a0a-9f81-89ae382aaf45 +set_theme!(cool_theme) + +# ╔═╡ 2136ca01-87b4-47e9-93b1-25892896413b +md" +## First order plus time delay, response to step + +$g(s)=\dfrac{Ke^{-\theta s}}{\tau s + 1}$ + +response to step input $U(s)=1/s$. +" + +# ╔═╡ e664515e-d86b-4a91-9d47-2d77ad19d06a +function sim_first_order_response() + K = 2.0 # gain + τ = 4.0 # time constant + θ = 1.5 # time delay + + g = K * exp(-θ * s) / (τ * s + 1) # FOPTD transfer function + + U = 1 / s # step input + Y = g * U # response + + t_final = 15.0 + data = simulate(Y, t_final) + + fig = viz_response(data, title="FOPTD step response", + savename="../docs/src/FOPTD_step_response.png") + return fig +end + +# ╔═╡ e2f12441-c8e7-486c-99b4-0ba302d41895 +sim_first_order_response() + +# ╔═╡ 5bcd4573-7656-4ebe-ba88-45adf2cc4127 +md" +## Second order underdamped, response to step + +$g(s)=\dfrac{4}{4 s ^2 + 0.8 s + 1}$ + +response to step input $U(s)=1/s$. +" + +# ╔═╡ a25db436-2022-4c33-87fc-36f9b507823f +function sim_second_order_response() + g = 4 / (4 * s ^ 2 + 0.8 * s + 1) + + U = 1 / s + Y = g * U + + data = simulate(Y, 50.0) + + fig = viz_response(data, title="SO underdamped step response", + savename="../docs/src/SO_underdamped_step_response.png") + return fig +end + +# ╔═╡ b4433a1c-7d03-440f-af08-51d6d5f6d822 +sim_second_order_response() + +# ╔═╡ f52a6b52-8202-4c3f-a7b4-4280ffc191d4 +md"## viz poles/zeros of a transfer function" + +# ╔═╡ 4da06cb3-5086-4fe8-b728-a3f8e7e889c7 +function inspect_poles_and_zeros() + g = (s + 2) / (s^2 + 1/4) + viz_poles_and_zeros(g, savename="../docs/src/example_poles_and_zeros.png") +end + +# ╔═╡ 4cb723a0-d3de-4a98-8d41-0e045a161d07 +inspect_poles_and_zeros() + +# ╔═╡ 252f5036-62f7-45ef-b7ca-5865aab4cda8 +md"## Nyquist diagram" + +# ╔═╡ a5c6b75a-be4b-4c82-ab87-2b72463b6303 +function draw_nyquist_diagram() + g = 1 / (s^2 + s + 1) # https://en.wikipedia.org/wiki/Nyquist_stability_criterion + fig = nyquist_diagram(g, savename="../docs/src/example_nyquist.png") + return fig +end + +# ╔═╡ 068905e6-9cde-4cc9-a042-a36b79c1a234 +draw_nyquist_diagram() + +# ╔═╡ 8a3d4776-5968-450d-982f-00249caa82ae +md"## root locus diagram" + +# ╔═╡ bbd279b4-184d-4e6f-bacf-b468d5c1fd36 +function draw_root_locus_diagram() + g_ol = 4 / (s + 3) / (s + 2) / (s + 1) + + fig = root_locus(g_ol, savename="../docs/src/example_root_locus.png") + return fig +end + +# ╔═╡ 24a1c30c-a21c-471d-bcf7-d90fe7200a8c +draw_root_locus_diagram() + +# ╔═╡ afee73f3-740d-4114-96c5-b50b1e025e6c +md"## Bode plot" + +# ╔═╡ d3996cd9-6890-4445-b2fe-c38ecc76ce77 +function draw_bode_plot() + g = 3 / (s+1) + + fig = bode_plot(g, savename="../docs/src/example_bode.png") + return fig +end + +# ╔═╡ 26d9f8ea-5d85-4cdd-b500-0e2d63f60e81 +draw_bode_plot() + +# ╔═╡ 13ce095f-2ba2-42a5-b753-cd6a43f024af +function mybode_plot(g::TransferFunction; log10_ω_min::Float64=-3.0, log10_ω_max::Float64=3.0, nb_pts::Int=300) + ω = 10.0 .^ range(log10_ω_min, log10_ω_max, length=nb_pts) + g_iω = [evaluate(g, im * ω_i) for ω_i in ω] + ∠g_iω = zeros(length(g_iω)) + + circle_counter = 0 + ∠g_iω[1] = angle(g_iω[1]) + for i = 2:length(g_iω) + ∠g_iω[i] = angle(g_iω[i]) - circle_counter * 2 * π + if ∠g_iω[i] - ∠g_iω[i-1] > π + ∠g_iω[i] -= 2 * π + circle_counter += 1 + end + end + + fig = Figure(resolution=(800, 600)) + axs = [Axis(fig[1, 1], xscale=log10, yscale=log10, + ylabel="|g(iω)|", title="Bode plot", + xminorticksvisible=true, xminorgridvisible=true, + yminorticksvisible=true, yminorgridvisible=true), + Axis(fig[2, 1], xscale=log10, + xlabel="ω", ylabel="∠g(iω)", + xminorticksvisible=true, xminorgridvisible=true, + yminorticksvisible=true, yminorgridvisible=true) + ] + # linkxaxes!(axs...) + lines!(axs[1], ω, abs.(g_iω)) + lines!(axs[2], ω, ∠g_iω / π) + # axs[2].yaxis.set_major_formatter(PyPlot.matplotlib.ticker.FormatStrFormatter(L"%g$\pi$")) + return fig +end + + +# ╔═╡ 7310762a-3c02-42e0-bbb7-85011ba4e144 +mybode_plot(3/(s+1)) + +# ╔═╡ Cell order: +# ╠═4952d2aa-6b42-11ec-15ea-ed5764c1810b +# ╠═5da3e954-e940-45a7-b355-45e78b5ce38b +# ╠═ecab99c5-d929-4a0a-9f81-89ae382aaf45 +# ╟─2136ca01-87b4-47e9-93b1-25892896413b +# ╠═e664515e-d86b-4a91-9d47-2d77ad19d06a +# ╠═e2f12441-c8e7-486c-99b4-0ba302d41895 +# ╟─5bcd4573-7656-4ebe-ba88-45adf2cc4127 +# ╠═a25db436-2022-4c33-87fc-36f9b507823f +# ╠═b4433a1c-7d03-440f-af08-51d6d5f6d822 +# ╟─f52a6b52-8202-4c3f-a7b4-4280ffc191d4 +# ╠═4da06cb3-5086-4fe8-b728-a3f8e7e889c7 +# ╠═4cb723a0-d3de-4a98-8d41-0e045a161d07 +# ╟─252f5036-62f7-45ef-b7ca-5865aab4cda8 +# ╠═a5c6b75a-be4b-4c82-ab87-2b72463b6303 +# ╠═068905e6-9cde-4cc9-a042-a36b79c1a234 +# ╟─8a3d4776-5968-450d-982f-00249caa82ae +# ╠═bbd279b4-184d-4e6f-bacf-b468d5c1fd36 +# ╠═24a1c30c-a21c-471d-bcf7-d90fe7200a8c +# ╟─afee73f3-740d-4114-96c5-b50b1e025e6c +# ╠═d3996cd9-6890-4445-b2fe-c38ecc76ce77 +# ╠═26d9f8ea-5d85-4cdd-b500-0e2d63f60e81 +# ╠═13ce095f-2ba2-42a5-b753-cd6a43f024af +# ╠═7310762a-3c02-42e0-bbb7-85011ba4e144 diff --git a/src/Controlz.jl b/src/Controlz.jl index 8d6a75c..3bbe20d 100644 --- a/src/Controlz.jl +++ b/src/Controlz.jl @@ -6,10 +6,9 @@ using Interpolations using Printf using Roots using DataFrames -using CairoMakie +using CairoMakie, ColorSchemes, Colors -# TODO set plot theme -include("beavs_theme.jl") +include("plot_theme.jl") include("tf.jl") include("special_tfs.jl") @@ -38,5 +37,7 @@ export # margins.jl gain_phase_margins, # closedloops.jl - ClosedLoopTransferFunction + ClosedLoopTransferFunction, + # plot_theme.jl + cool_theme end diff --git a/src/beavs_theme.jl b/src/beavs_theme.jl deleted file mode 100644 index 31b1a5b..0000000 --- a/src/beavs_theme.jl +++ /dev/null @@ -1,51 +0,0 @@ -set_theme!( - Theme( - palette = (color=[c for c in ColorSchemes.Dark2_5], marker=[:circle, :utriangle, :cross, :rect, :diamond, :dtriangle, :pentagon, :xcross]), - textcolor = :gray40, - linewidth=4, - fontsize=20, - font="Courier", - resolution = (520, 400), - Axis = ( - backgroundcolor = RGB(0.96, 1.0, 0.98), - xgridcolor = (:black, 0.15), - ygridcolor = (:black, 0.15), - leftspinevisible = false, - rightspinevisible = false, - ygridstyle=:dash, - xgridstyle=:dash, - bottomspinevisible = false, - topspinevisible = false, - xminorticksvisible = false, - yminorticksvisible = false, - xticksvisible = false, - yticksvisible = false, - xlabelpadding = 3, - ylabelpadding = 3 - ), - Legend = ( - framevisible = true, - titlehalign=:left, - titlesize=16, - labelsize=16, - framecolor=(:black, 0.5) - # padding = (1, 0, 0, 0), - ), - Axis3 = ( - xgridcolor = (:black, 0.07), - ygridcolor = (:black, 0.07), - zgridcolor = (:black, 0.07), - xspinesvisible = false, - yspinesvisible = false, - zspinesvisible = false, - xticksvisible = false, - yticksvisible = false, - zticksvisible = false, - ), - Colorbar = ( - ticksvisible = false, - spinewidth = 0, - ticklabelpad = 5, - ) - ) -) diff --git a/src/viz.jl b/src/viz.jl index 60ee943..fa09a7a 100644 --- a/src/viz.jl +++ b/src/viz.jl @@ -1,84 +1,89 @@ -function draw_axes() - axvline(x=0, color="0.8", lw=2, zorder=1) - axhline(y=0, color="0.8", lw=2, zorder=1) +function draw_axes(ax::Axis) + vlines!(ax, 0.0, color=(:gray40, 0.6), linewidth=1) + hlines!(ax, 0.0, color=(:gray40, 0.6), linewidth=1) end @doc raw""" viz_response(data, - plot_title="", plot_xlabel="time, t", - plot_ylabel="output, y(t)", + title="", xlabel="time, t", + ylabel="output, y(t)", savename=nothing) plot `data[:, :output]` vs. `data[:, :t]` to visualize the response of a system to an input. typically the data frame, `data`, is returned from [`simulate`](@ref). -note that PyPlot.jl (matplotlib) commands can be invoked after `viz_response` to make further changes to the figure panel. -e.g. `xlim([0, 1])` can be applied after `viz_response`. - # Arguments * `data::DataFrame`: data frame of time series data, containing a `:t` column for times and `:output` column for the outputs. -* `plot_title::String`: title of plot -* `plot_xlabel::String`: x-label -* `plot_ylabel::String`: y-label -* `savename::Union{Nothing, String}`: filename to save as a figure in .png format (dpi 250). +* `title::String`: title of plot +* `xlabel::String`: x-label +* `ylabel::String`: y-label +* `savename::Union{Nothing, String}`: filename to save as a figure in .png format. + +# Returns +`CairoMakie.jl` `Figure` object. this will display in a Pluto.jl notebook. + +`CairoMakie.jl` commands can be invoked after `viz_response` to make further changes to the figure panel by e.g.: +```julia +fig = viz_response(data) +ax = current_axis(fig) +ax.xlabel = "new xlabel" +xlims!(ax, 0, 15) +``` + # Example ``` g = 4 / (4 * s ^ 2 + 0.8 * s + 1) u = 1 / s data = simulate(g * u, (0.0, 50.0)) -viz_response(data) +fig = viz_response(data) ``` """ function viz_response(data::DataFrame; - plot_title::String="", - plot_xlabel::String=L"time, $t$", - plot_ylabel::String=L"output, $y(t)$", - savename::Union{Nothing, String}=nothing + title::String="", + xlabel::String="time, t", + ylabel::String="output, y(t)", + savename::Union{Nothing, String}=nothing ) - + fig = Figure() - plot(data[:, :t], data[:, :output], zorder=100) - xlabel(plot_xlabel) - ylabel(plot_ylabel) - title(plot_title) - draw_axes() + ax = Axis(fig[1, 1], xlabel=xlabel, ylabel=ylabel, title=title) + draw_axes(ax) + lines!(data[:, :t], data[:, :output]) if ! isnothing(savename) - tight_layout() - if ! occursin(".png", savename) - savename *= ".png" - end - savefig(savename, dpi=250, format="png") + save(savename, fig, px_per_unit=1) end - return nothing + return fig end """ - viz_poles_and_zeros(tf) + viz_poles_and_zeros(g, savename=nothing) + +plot the zeros and poles of the transfer function `g` in the complex plane. -plot the zeros and poles of the transfer function `tf` in the complex plane. +returns a `CairoMakie.jl` `Figure` object for further modification. """ -function viz_poles_and_zeros(tf::TransferFunction) +function viz_poles_and_zeros(tf::TransferFunction; savename::Union{Nothing, String}=nothing) z, p, k = zeros_poles_gain(tf) fig = Figure() - scatter(real.(z), imag.(z), marker="o", label="zeros", color="C1", zorder=100, s=50) - scatter(real.(p), imag.(p), marker="x", label="poles", color="C2", s=50, zorder=100) - legend() - draw_axes() - xlabel("Re") - ylabel("Im") - title("poles and zeros") - tight_layout() - return nothing + ax = Axis(fig[1, 1], xlabel="Re", ylabel="Im", title="poles and zeros") + draw_axes(ax) + scatter!(real.(z), imag.(z), marker=:o, label="zeros", markersize=15) + scatter!(real.(p), imag.(p), marker=:x, label="poles", markersize=15) + axislegend() + if ! isnothing(savename) + save(savename, fig, px_per_unit=1) + end + return fig end """ - nyquist_diagram(tf, nb_pts=500, ω_max=10.0) + nyquist_diagram(tf, nb_pts=500, ω_max=10.0, savename=nothing) plot the Nyquist diagram for a transfer function `tf` to visualize its frequency response. `s=-1` is plotted as a red `+`. `nb_pts` changes the resolution. `ω_max` gives maximum frequency considered. """ -function nyquist_diagram(tf::TransferFunction; nb_pts::Int=500, ω_max::Float64=10.0) +function nyquist_diagram(tf::TransferFunction; nb_pts::Int=500, ω_max::Float64=10.0, savename::Union{Nothing, String}=nothing) ω_neg = range(-ω_max, 0.0, length=nb_pts) ω_pos = range(0.0, ω_max, length=nb_pts) @@ -86,19 +91,20 @@ function nyquist_diagram(tf::TransferFunction; nb_pts::Int=500, ω_max::Float64= g_iω_pos = [evaluate(tf, ω_i * im) for ω_i in ω_pos] fig = Figure() - plot(real(g_iω_neg), imag(g_iω_neg), zorder=100) - plot(real(g_iω_pos), imag(g_iω_pos), zorder=100) - draw_axes() + ax = Axis(fig[1, 1], xlabel="Re[G(iω)]", ylabel="Im[G(iω)]", title="Nyquist diagram") + draw_axes(ax) + lines!(real(g_iω_neg), imag(g_iω_neg)) + lines!(real(g_iω_pos), imag(g_iω_pos)) # plot -1 - plot([-1], [0], marker="+", color="r", zorder=1000, markersize=15) - xlabel("Re[G(iω)]") - ylabel("Im[G(iω)]") - title("Nyquist diagram") - tight_layout() + scatter([-1], [0], marker=:+, markersize=15, color="red") + if ! isnothing(savename) + save(savename, fig, px_per_unit=1) + end + return fig end """ - root_locus(g_ol, max_mag_Kc=10.0, nb_pts=500) + root_locus(g_ol, max_mag_Kc=10.0, nb_pts=500, savename=nothing) visualize the root locus plot of an open-loop transfer function `g_ol`. @@ -109,7 +115,7 @@ visualize the root locus plot of an open-loop transfer function `g_ol`. * `nb_pts::Int=500`: the number of gains to explore. increase for higher resolution. """ function root_locus(g_ol::TransferFunction; - max_mag_Kc::Float64=10.0, nb_pts::Int=500) + max_mag_Kc::Float64=10.0, nb_pts::Int=500, savename=nothing) # compute zeros, poles, and gain of open loop transfer function z, p, k = zeros_poles_k(g_ol) @@ -148,25 +154,23 @@ function root_locus(g_ol::TransferFunction; end fig = Figure() + ax = Axis(fig[1, 1], xlabel="Re", ylabel="Im", title="root locus") + draw_axes(ax) # plot poles; corresponds to Kc = 0 - scatter(real.(p), imag.(p), marker="x", label="poles", - color="k", s=50, zorder=100) + scatter!(real.(p), imag.(p), marker=:x, label="poles", markersize=15, color="black") # plot zeros; corresponds to |Kc| → ∞ if length(z) > 0 - scatter(real.(z), imag.(z), marker="o", label="zeros", - color="k", s=50, zorder=100, facecolor="None") + scatter!(real.(z), imag.(z), marker=:o, label="zeros", markersize=15, color="black") end # plot roots traversing plane for i = 1:length(p) - plot(real.(rloc[:, i]), imag.(rloc[:, i]), - zorder=100, color="C$(i-1)") + lines!(real.(rloc[:, i]), imag.(rloc[:, i])) end - xlabel("Re") - ylabel("Im") - draw_axes() - title("root locus") - legend() - tight_layout() + axislegend() + if ! isnothing(savename) + save(savename, fig, px_per_unit=1) + end + return fig end """ @@ -192,11 +196,12 @@ function bode_plot(g::TransferFunction; log10_ω_min::Float64=-3.0, log10_ω_max circle_counter += 1 end end - - fig, axs = subplots(2, 1, sharex=true, figsize=(8, 7)) - axs[1].plot(ω, abs.(g_iω), color="C0") - axs[1].set_ylabel(L"$|g(i\omega)|$") - axs[1].set_title("Bode plot") + + fig = Figure() + axs = [Axis(fig[1, 1], ylabel="|g(iω)|", title="Bode plot"), + Axis(fig[2, 1], xlabel="ω")] + linkxaxes!(axs...) + axs[1].lines!(ω, abs.(g_iω)) axs[1].set_xscale("log") axs[1].set_yscale("log") axs[2].set_xscale("log") @@ -207,7 +212,6 @@ function bode_plot(g::TransferFunction; log10_ω_min::Float64=-3.0, log10_ω_max ax.minorticks_on() ax.grid(b=true, which="minor", alpha=0.25) end - xlabel(L"frequency, $\omega$") tight_layout() return axs end From 3e79fbab07828fae55733fcd3e30567e60df7528 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 18:31:59 -0800 Subject: [PATCH 06/19] add plot theme --- src/plot_theme.jl | 51 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 51 insertions(+) create mode 100644 src/plot_theme.jl diff --git a/src/plot_theme.jl b/src/plot_theme.jl new file mode 100644 index 0000000..8ddc116 --- /dev/null +++ b/src/plot_theme.jl @@ -0,0 +1,51 @@ +cool_theme = Theme( + palette = (color=[c for c in ColorSchemes.Dark2_5], marker=[:circle, :utriangle, :cross, :rect, :diamond, :dtriangle, :pentagon, :xcross]), + textcolor = :gray40, + linewidth=4, + fontsize=20, + font="Courier", + resolution = (520, 400), + Axis = ( + backgroundcolor = RGB(0.96, 1.0, 0.98), + xgridcolor = (:black, 0.15), + ygridcolor = (:black, 0.15), + leftspinevisible = false, + rightspinevisible = false, + ygridstyle=:dash, + xgridstyle=:dash, + bottomspinevisible = false, + topspinevisible = false, + xminorticksvisible = false, + yminorticksvisible = false, + xticksvisible = false, + yticksvisible = false, + xlabelpadding = 3, + ylabelpadding = 3 + ), + Legend = ( + framevisible = true, + titlehalign=:left, + titlesize=16, + labelsize=16, + framecolor=(:black, 0.5) + # padding = (1, 0, 0, 0), + ), + Axis3 = ( + xgridcolor = (:black, 0.07), + ygridcolor = (:black, 0.07), + zgridcolor = (:black, 0.07), + xspinesvisible = false, + yspinesvisible = false, + zspinesvisible = false, + xticksvisible = false, + yticksvisible = false, + zticksvisible = false, + ), + Colorbar = ( + ticksvisible = false, + spinewidth = 0, + ticklabelpad = 5, + ) +) + +set_theme!(cool_theme) From 2a0ae2a4ae390e028f2929abfe24cec2c44e2005 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 19:58:25 -0800 Subject: [PATCH 07/19] update viz --- examples/examples.jl | 66 +++++++++++++----------------- src/plot_theme.jl | 4 +- src/viz.jl | 97 +++++++++++++++++++++++++------------------- 3 files changed, 87 insertions(+), 80 deletions(-) diff --git a/examples/examples.jl b/examples/examples.jl index 0a1fcfd..08b9c64 100644 --- a/examples/examples.jl +++ b/examples/examples.jl @@ -8,7 +8,7 @@ using InteractiveUtils import Pkg; Pkg.activate() # ╔═╡ 5da3e954-e940-45a7-b355-45e78b5ce38b -using Controlz, DataFrames, CairoMakie, ColorSchemes, Colors +using Controlz, DataFrames, CairoMakie, ColorSchemes, Colors, Printf # ╔═╡ ecab99c5-d929-4a0a-9f81-89ae382aaf45 set_theme!(cool_theme) @@ -107,7 +107,10 @@ function draw_root_locus_diagram() end # ╔═╡ 24a1c30c-a21c-471d-bcf7-d90fe7200a8c -draw_root_locus_diagram() +fig = draw_root_locus_diagram() + +# ╔═╡ c7739f1b-f3d9-4473-91fe-947f29b499f0 +current_axis().limits # ╔═╡ afee73f3-740d-4114-96c5-b50b1e025e6c md"## Bode plot" @@ -123,42 +126,27 @@ end # ╔═╡ 26d9f8ea-5d85-4cdd-b500-0e2d63f60e81 draw_bode_plot() -# ╔═╡ 13ce095f-2ba2-42a5-b753-cd6a43f024af -function mybode_plot(g::TransferFunction; log10_ω_min::Float64=-3.0, log10_ω_max::Float64=3.0, nb_pts::Int=300) - ω = 10.0 .^ range(log10_ω_min, log10_ω_max, length=nb_pts) - g_iω = [evaluate(g, im * ω_i) for ω_i in ω] - ∠g_iω = zeros(length(g_iω)) - - circle_counter = 0 - ∠g_iω[1] = angle(g_iω[1]) - for i = 2:length(g_iω) - ∠g_iω[i] = angle(g_iω[i]) - circle_counter * 2 * π - if ∠g_iω[i] - ∠g_iω[i-1] > π - ∠g_iω[i] -= 2 * π - circle_counter += 1 - end - end - - fig = Figure(resolution=(800, 600)) - axs = [Axis(fig[1, 1], xscale=log10, yscale=log10, - ylabel="|g(iω)|", title="Bode plot", - xminorticksvisible=true, xminorgridvisible=true, - yminorticksvisible=true, yminorgridvisible=true), - Axis(fig[2, 1], xscale=log10, - xlabel="ω", ylabel="∠g(iω)", - xminorticksvisible=true, xminorgridvisible=true, - yminorticksvisible=true, yminorgridvisible=true) - ] - # linkxaxes!(axs...) - lines!(axs[1], ω, abs.(g_iω)) - lines!(axs[2], ω, ∠g_iω / π) - # axs[2].yaxis.set_major_formatter(PyPlot.matplotlib.ticker.FormatStrFormatter(L"%g$\pi$")) - return fig -end +# ╔═╡ 2de0d044-1bf6-489f-9e54-026100fd7655 +md"## draw a `.gif` of a response" + +# ╔═╡ b6a45495-e081-4e02-8a0e-cfe1d3df36ba +function test_make_gif() + K = 2.0 # gain + τ = 4.0 # time constant + θ = 1.5 # time delay + + g = K * exp(-θ * s) / (τ * s + 1) # FOPTD transfer function + + U = 1 / s # step input + Y = g * U # response + t_final = 15.0 + data = simulate(Y, t_final) + mk_gif(data) +end -# ╔═╡ 7310762a-3c02-42e0-bbb7-85011ba4e144 -mybode_plot(3/(s+1)) +# ╔═╡ 8acaad0e-951d-4bc9-add8-19315bb9f4e6 +test_make_gif() # ╔═╡ Cell order: # ╠═4952d2aa-6b42-11ec-15ea-ed5764c1810b @@ -179,8 +167,10 @@ mybode_plot(3/(s+1)) # ╟─8a3d4776-5968-450d-982f-00249caa82ae # ╠═bbd279b4-184d-4e6f-bacf-b468d5c1fd36 # ╠═24a1c30c-a21c-471d-bcf7-d90fe7200a8c +# ╠═c7739f1b-f3d9-4473-91fe-947f29b499f0 # ╟─afee73f3-740d-4114-96c5-b50b1e025e6c # ╠═d3996cd9-6890-4445-b2fe-c38ecc76ce77 # ╠═26d9f8ea-5d85-4cdd-b500-0e2d63f60e81 -# ╠═13ce095f-2ba2-42a5-b753-cd6a43f024af -# ╠═7310762a-3c02-42e0-bbb7-85011ba4e144 +# ╟─2de0d044-1bf6-489f-9e54-026100fd7655 +# ╠═b6a45495-e081-4e02-8a0e-cfe1d3df36ba +# ╠═8acaad0e-951d-4bc9-add8-19315bb9f4e6 diff --git a/src/plot_theme.jl b/src/plot_theme.jl index 8ddc116..1ef75a8 100644 --- a/src/plot_theme.jl +++ b/src/plot_theme.jl @@ -3,12 +3,14 @@ cool_theme = Theme( textcolor = :gray40, linewidth=4, fontsize=20, - font="Courier", + font="ubuntu", resolution = (520, 400), Axis = ( backgroundcolor = RGB(0.96, 1.0, 0.98), xgridcolor = (:black, 0.15), ygridcolor = (:black, 0.15), + xminorgridcolor = (:gray, 0.15), + yminorgridcolor = (:gray, 0.15), leftspinevisible = false, rightspinevisible = false, ygridstyle=:dash, diff --git a/src/viz.jl b/src/viz.jl index fa09a7a..3604546 100644 --- a/src/viz.jl +++ b/src/viz.jl @@ -82,6 +82,8 @@ end nyquist_diagram(tf, nb_pts=500, ω_max=10.0, savename=nothing) plot the Nyquist diagram for a transfer function `tf` to visualize its frequency response. `s=-1` is plotted as a red `+`. `nb_pts` changes the resolution. `ω_max` gives maximum frequency considered. + +returns a `CairoMakie.jl` `Figure` object for further modification. """ function nyquist_diagram(tf::TransferFunction; nb_pts::Int=500, ω_max::Float64=10.0, savename::Union{Nothing, String}=nothing) ω_neg = range(-ω_max, 0.0, length=nb_pts) @@ -113,9 +115,12 @@ visualize the root locus plot of an open-loop transfer function `g_ol`. * `max_mag_Kc::Float64=10.0`: the maximum magnitude by which the gain of `g_ol` is scaled in order to see the roots traversing the plane * `nb_pts::Int=500`: the number of gains to explore. increase for higher resolution. + +# returns +a `CairoMakie.jl` `Figure` object for further modification. """ function root_locus(g_ol::TransferFunction; - max_mag_Kc::Float64=10.0, nb_pts::Int=500, savename=nothing) + max_mag_Kc::Float64=10.0, nb_pts::Int=500, savename::Union{Nothing, String}=nothing) # compute zeros, poles, and gain of open loop transfer function z, p, k = zeros_poles_k(g_ol) @@ -180,9 +185,12 @@ draw the Bode plot of a transfer function `tf` to visualize its frequency respon returns the two axes of the plot for further tuning via `matplotlib` commands. adjust the range of frequencies that the Bode plot presents with `log10_ω_min` and `log10_ω_max`. + +returns a `CairoMakie.jl` `Figure` object for further modification. increase the resolution of the Bode plot with `nb_pts`. """ -function bode_plot(g::TransferFunction; log10_ω_min::Float64=-3.0, log10_ω_max::Float64=3.0, nb_pts::Int=300) +function bode_plot(g::TransferFunction; log10_ω_min::Float64=-3.0, log10_ω_max::Float64=3.0, + nb_pts::Int=300, savename::Union{Nothing, String}=nothing) ω = 10.0 .^ range(log10_ω_min, log10_ω_max, length=nb_pts) g_iω = [evaluate(g, im * ω_i) for ω_i in ω] ∠g_iω = zeros(length(g_iω)) @@ -197,28 +205,36 @@ function bode_plot(g::TransferFunction; log10_ω_min::Float64=-3.0, log10_ω_max end end - fig = Figure() - axs = [Axis(fig[1, 1], ylabel="|g(iω)|", title="Bode plot"), - Axis(fig[2, 1], xlabel="ω")] + fig = Figure(resolution=(800, 600)) + axs = [Axis(fig[1, 1], xscale=log10, yscale=log10, + ylabel="|g(iω)|", title="Bode plot"), + Axis(fig[2, 1], xscale=log10, + xlabel="ω", ylabel="∠g(iω)") + ] linkxaxes!(axs...) - axs[1].lines!(ω, abs.(g_iω)) - axs[1].set_xscale("log") - axs[1].set_yscale("log") - axs[2].set_xscale("log") - axs[2].plot(ω, ∠g_iω / π, color="C1") - axs[2].yaxis.set_major_formatter(PyPlot.matplotlib.ticker.FormatStrFormatter(L"%g$\pi$")) - axs[2].set_ylabel(L"$\angle g(i\omega)$") - for ax in axs - ax.minorticks_on() - ax.grid(b=true, which="minor", alpha=0.25) + for ax in axs # to make plot easy to read + ax.xticksvisible = true + ax.xminorticksvisible = true + ax.xminorticks = IntervalsBetween(9) + ax.xminorgridvisible = true + + ax.yticksvisible = true + ax.yminorticksvisible = true + ax.yminorticks = IntervalsBetween(9) + ax.yminorgridvisible = true + end + axs[2].yticks = MultiplesTicks(4, pi, "π") + lines!(axs[1], ω, abs.(g_iω)) + lines!(axs[2], ω, ∠g_iω / π) + if ! isnothing(savename) + save(savename, fig, px_per_unit=1) end - tight_layout() - return axs + return fig end @doc raw""" - mk_gif(data, plot_title="", plot_xlabel="time, t", - plot_ylabel="output, y(t)", + mk_gif(data, title="", xlabel="time, t", + ylabel="output, y(t)", savename="response") make a .gif of the process response. @@ -229,38 +245,37 @@ the .gif is saved as a file `savename`. # Arguments * `data::DataFrame`: data frame of time series data, containing a `:t` column for times and `:output` column for the outputs. -* `plot_title::String`: title of plot -* `plot_xlabel::String`: x-label -* `plot_ylabel::String`: y-label +* `title::String`: title of plot +* `xlabel::String`: x-label +* `ylabel::String`: y-label * `savename::String`: filename to save as a .gif. .gif extension automatically appended if not provided. """ -function mk_gif(t::Array{Float64}, y::Array{Float64}; - plot_title::String="", - plot_xlabel::String=L"time, $t$", - plot_ylabel::String=L"output, $y(t)$", - savename::String="response.gif" +function mk_gif(data::DataFrame; + title::String="", + xlabel::String="time, t", + ylabel::String="output, y(t)", + savename::String="response.gif" ) - if length(t) > 999 + if nrow(data) > 999 error("too many points and thus images; reduce the number of points") end - # let matplotlib determine x, y lims: - plot(t, y) - xmin, xmax, ymin, ymax = axis() - close() + # determine x-, y-limits + Δx = maximum(data[:, :t]) - minimum(data[:, :t]) + Δy = maximum(data[:, :output]) - minimum(data[:, :output]) + xlims = (minimum(data[:, :t]) - 0.01 * Δx, maximum(data[:, :t]) + 0.01 * Δx)) + ylims = (minimum(data[:, :output]) - 0.01 * Δy, maximum(data[:, :output]) + 0.01 * Δy) # name to save image i as. step_to_image(i::Int) = @sprintf("__y_of_t_snapshot_%03d.png", i) # save series of images - for i = 2:length(t) - viz_response(t[1:i], y[1:i], plot_title=plot_title, plot_xlabel=plot_xlabel, - plot_ylabel=plot_ylabel) - xlim([xmin, xmax]) - ylim([ymin, ymax]) - tight_layout() - savefig(step_to_image(i), format="png", dpi=100) - close() + for i = 1:length(t) + fig = viz_response(data[1:i, :], title=title, xlabel=xlabel, ylabel=ylabel) + ax = current_axis() + xlims!(ax, xlims...) + ylims!(ax, ylims...) + save(step_to_image(i), fig) end if ! occursin(".gif", savename) @@ -274,7 +289,7 @@ function mk_gif(t::Array{Float64}, y::Array{Float64}; end # clean up - for i = 2:length(t) + for i = 1:nrow(data) rm(step_to_image(i)) end end From 3642825b1b92013e99d87b33f746948918f31375 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 20:02:47 -0800 Subject: [PATCH 08/19] correct ). viz done. --- src/viz.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/viz.jl b/src/viz.jl index 3604546..ea83464 100644 --- a/src/viz.jl +++ b/src/viz.jl @@ -263,7 +263,7 @@ function mk_gif(data::DataFrame; # determine x-, y-limits Δx = maximum(data[:, :t]) - minimum(data[:, :t]) Δy = maximum(data[:, :output]) - minimum(data[:, :output]) - xlims = (minimum(data[:, :t]) - 0.01 * Δx, maximum(data[:, :t]) + 0.01 * Δx)) + xlims = (minimum(data[:, :t]) - 0.01 * Δx, maximum(data[:, :t]) + 0.01 * Δx) ylims = (minimum(data[:, :output]) - 0.01 * Δy, maximum(data[:, :output]) + 0.01 * Δy) # name to save image i as. From c249c816aa95a4047ecbc68b81dfd8283040eca2 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 20:08:10 -0800 Subject: [PATCH 09/19] bug in gif maker --- src/viz.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/viz.jl b/src/viz.jl index ea83464..7a3f001 100644 --- a/src/viz.jl +++ b/src/viz.jl @@ -270,7 +270,7 @@ function mk_gif(data::DataFrame; step_to_image(i::Int) = @sprintf("__y_of_t_snapshot_%03d.png", i) # save series of images - for i = 1:length(t) + for i = 1:nrow(data) fig = viz_response(data[1:i, :], title=title, xlabel=xlabel, ylabel=ylabel) ax = current_axis() xlims!(ax, xlims...) From bdafe2141130a2826689d8e16769e53979d5cb37 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 20:10:22 -0800 Subject: [PATCH 10/19] make images automatically generated --- docs/src/FOPTD_step_response.png | Bin 37868 -> 0 bytes docs/src/SO_underdamped_step_response.png | Bin 41220 -> 0 bytes docs/src/SO_underdamped_step_resposne.png | Bin 32582 -> 0 bytes docs/src/closed_loop_servo_time_delay.png | Bin 39893 -> 0 bytes docs/src/example_bode.png | Bin 126728 -> 0 bytes docs/src/example_nyquist.png | Bin 41965 -> 0 bytes docs/src/example_poles_and_zeros.png | Bin 28119 -> 0 bytes docs/src/example_root_locus.png | Bin 27241 -> 0 bytes docs/src/simple_servo_response.png | Bin 70285 -> 0 bytes docs/src/tcosat.png | Bin 45680 -> 0 bytes test/runtests.jl | 5 +++++ 11 files changed, 5 insertions(+) delete mode 100644 docs/src/FOPTD_step_response.png delete mode 100644 docs/src/SO_underdamped_step_response.png delete mode 100644 docs/src/SO_underdamped_step_resposne.png 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zD+;@T&?TuK8amP#OrruV16a_%Y>^HV^+bl%ZZrVKWC6}h$lWJE8t?19fxbRdIPRb} z3;+Sh^S;c?gq${SnFu?c>K77nzM?ZNG$*T)_yX3Amx~Jly$3XiMyT-u2j<68>nrna zDY$``liAtX6TlIzsH@Au;W^6<-HS>V2^-gsnMQ`axa=&c=Q%ebw&c-pn%}(ptkA1tC2Q zfg903S`LEIH6RBG;YShr4VhV41+68zLR-+cFcoDHy}N3G3TfyUFdMMqg^x87oDD(VCe!3rp|b`@LoSvZ_{`R9oEu zgO!z4X0^OTU+T9j*!Ct!R~K+SykiHcsQ7W8Dp#55>HTYJ(5xMpyfcU7;S*Zkc!M$9 zfnkHwQ86?7>RtO>4$Ler48F^|MXahS_wnNtX}){X!E~IoaBf2C^Yu#M1U^`x2gjh1 zJ9UxQ^K`g*c}ZYUQ?<@#H+^8f`)_1{2a(um)zs25{2BkrWfy-*GUZkCe{QS`aw61; zsf5sefld{$Yf>PP6<_*C mCPILs%*$lS`VJW5^e^A&ZAv9fW(hX}|1PTHurHPI{{I8BCY%5O diff --git a/test/runtests.jl b/test/runtests.jl index 5570345..466c0a1 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -461,3 +461,8 @@ end data_new = simulate(ClosedLoopTransferFunction(gp * gc, gp * gc), 10.0) @test isapprox(data_old[:, :output], data_new[:, :output], atol=0.0001) end + +@test "example notebook (also to generate images for docs)" begin + include(joinpath("..", "examples", "examples.jl")) + @test true +end From c1223377b81b5ad2baa9d51aa07c1a0f6e6c3d11 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 20:14:05 -0800 Subject: [PATCH 11/19] include example runner in tests to generate images for docs --- test/runtests.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/runtests.jl b/test/runtests.jl index 466c0a1..9aa6c72 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -462,7 +462,7 @@ end @test isapprox(data_old[:, :output], data_new[:, :output], atol=0.0001) end -@test "example notebook (also to generate images for docs)" begin +@testset "example notebook (also to generate images for docs)" begin include(joinpath("..", "examples", "examples.jl")) @test true end From 8e441c7d75a468ad58353d7d5408340f12964b7b Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sat, 1 Jan 2022 20:20:08 -0800 Subject: [PATCH 12/19] :circle not :o --- src/viz.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/viz.jl b/src/viz.jl index 7a3f001..ff5e869 100644 --- a/src/viz.jl +++ b/src/viz.jl @@ -69,7 +69,7 @@ function viz_poles_and_zeros(tf::TransferFunction; savename::Union{Nothing, Stri fig = Figure() ax = Axis(fig[1, 1], xlabel="Re", ylabel="Im", title="poles and zeros") draw_axes(ax) - scatter!(real.(z), imag.(z), marker=:o, label="zeros", markersize=15) + scatter!(real.(z), imag.(z), marker=:circle, label="zeros", markersize=15) scatter!(real.(p), imag.(p), marker=:x, label="poles", markersize=15) axislegend() if ! isnothing(savename) @@ -165,7 +165,7 @@ function root_locus(g_ol::TransferFunction; scatter!(real.(p), imag.(p), marker=:x, label="poles", markersize=15, color="black") # plot zeros; corresponds to |Kc| → ∞ if length(z) > 0 - scatter!(real.(z), imag.(z), marker=:o, label="zeros", markersize=15, color="black") + scatter!(real.(z), imag.(z), marker=:circle, label="zeros", markersize=15, color="black") end # plot roots traversing plane for i = 1:length(p) From 6b47b6d2c1322831ae5e486bd09f168a0cdcd89a Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sun, 2 Jan 2022 12:13:20 -0800 Subject: [PATCH 13/19] fix gain margin and crit freq for when it d.n.e., tune plot theme, get examples ready --- src/margins.jl | 13 +++++++++++-- src/plot_theme.jl | 6 +++--- test/runtests.jl | 6 ++++++ 3 files changed, 20 insertions(+), 5 deletions(-) diff --git a/src/margins.jl b/src/margins.jl index 271a9a6..2c75516 100644 --- a/src/margins.jl +++ b/src/margins.jl @@ -30,7 +30,7 @@ margins.phase_margin # phase margin (radians) ``` """ function gain_phase_margins(g_ol::TransferFunction; ω_c_guess::Float64=0.001, ω_g_guess::Float64=0.001) - # ∠ G(i ω_c) = -π + # critical frequency ∠ G(i ω_c) = -π ω_c = NaN try ω_c = fzero(ω -> angle(evaluate(g_ol, im * ω)) + π, ω_c_guess, atol=2*sqrt(eps())) @@ -42,7 +42,12 @@ function gain_phase_margins(g_ol::TransferFunction; ω_c_guess::Float64=0.001, error("something went wrong when computing ω_c") end end - # | G(i ω_g) | = 1 + # check for spurious solution (often ω_c d.n.e.) TODO check issue on Roots.jl + if ! isapprox(angle(evaluate(g_ol, im * ω_c)), -π, rtol=0.01) + ω_c = NaN + end + + # gain cross over frequency | G(i ω_g) | = 1 ω_g = NaN try ω_g = fzero(ω -> abs(evaluate(g_ol, im * ω)) - 1.0, ω_g_guess, atol=2*sqrt(eps())) @@ -54,6 +59,10 @@ function gain_phase_margins(g_ol::TransferFunction; ω_c_guess::Float64=0.001, error("something went wrong when computing ω_g") end end + # check for spurious solution (often ω_c d.n.e.) TODO check issue on Roots.jl + if ! isapprox(abs(evaluate(g_ol, im * ω_g)), 1.0, rtol=0.01) + ω_g = NaN + end # gain margin = 1 / | G(i ω_c) | gm = 1 / abs(evaluate(g_ol, im * ω_c)) # phase margin = ∠ G(i ω_g) + π diff --git a/src/plot_theme.jl b/src/plot_theme.jl index 1ef75a8..7e42971 100644 --- a/src/plot_theme.jl +++ b/src/plot_theme.jl @@ -1,12 +1,12 @@ cool_theme = Theme( - palette = (color=[c for c in ColorSchemes.Dark2_5], marker=[:circle, :utriangle, :cross, :rect, :diamond, :dtriangle, :pentagon, :xcross]), + palette = (color=[c for c in ColorSchemes.seaborn_muted6], marker=[:circle, :utriangle, :cross, :rect, :diamond, :dtriangle, :pentagon, :xcross]), textcolor = :gray40, linewidth=4, fontsize=20, - font="ubuntu", + font="open-sans", resolution = (520, 400), Axis = ( - backgroundcolor = RGB(0.96, 1.0, 0.98), + backgroundcolor = RGB(1.0, 1.0, 1.0), xgridcolor = (:black, 0.15), ygridcolor = (:black, 0.15), xminorgridcolor = (:gray, 0.15), diff --git a/test/runtests.jl b/test/runtests.jl index 9aa6c72..0e3d7f0 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -430,6 +430,12 @@ end m = gain_phase_margins(g_ol) @test isapprox(m.ω_c, 6.32, atol=0.01) @test isapprox(m.gain_margin, 5.397, atol=0.01) + + # check asymptote behavior + g_ol = 1 / (s + 1) # ω_c d.n.e. + m = gain_phase_margins(g_ol) + @test isnan(m.ω_c) + @test isnan(m.gain_margin) end @testset "closed loop stuff" begin From 98b90241e6abef0151bfc4948983607284d6b02f Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sun, 2 Jan 2022 12:44:20 -0800 Subject: [PATCH 14/19] change how tfs are constructed---enforce they are floats --- src/show.jl | 2 -- src/tf.jl | 21 ++++++++++++--------- 2 files changed, 12 insertions(+), 11 deletions(-) diff --git a/src/show.jl b/src/show.jl index 785aed0..fdf6882 100644 --- a/src/show.jl +++ b/src/show.jl @@ -17,8 +17,6 @@ function Base.show(io::IO, tf::TransferFunction) top = poly_to_string(tf.numerator) bottom = poly_to_string(tf.denominator) - print(io, "\n") - # is this a rational polynomial? then just print the numerator / constant if degree(tf.denominator) == 0 # normalized numerator diff --git a/src/tf.jl b/src/tf.jl index 75dc116..ab14b4f 100644 --- a/src/tf.jl +++ b/src/tf.jl @@ -25,18 +25,21 @@ tf = TransferFunction([4], [2, 1], 2.2) * `time_delay::Float64`: the associated time delay """ struct TransferFunction - numerator::Polynomial - denominator::Polynomial - time_delay::Union{Float64, Int} + numerator::Polynomial{Float64, :s} + denominator::Polynomial{Float64, :s} + time_delay::Float64 end -ArrayOfReals = Union{Array{Float64, 1}, Array{Int64, 1}} +TransferFunction(num::Union{Vector{Int}, Vector{Float64}}, + den::Union{Vector{Int}, Vector{Float64}}, + td::Union{Int, Float64}) = + TransferFunction(Polynomial(reverse(convert(Vector{Float64}, num)), :s), + Polynomial(reverse(convert(Vector{Float64}, den)), :s), + convert(Float64, td)) -TransferFunction(num::ArrayOfReals, den::ArrayOfReals) = - TransferFunction(Polynomial(reverse(num), :s), Polynomial(reverse(den), :s), 0.0) - -TransferFunction(num::ArrayOfReals, den::ArrayOfReals, td::Union{Float64, Int}) = - TransferFunction(Polynomial(reverse(num), :s), Polynomial(reverse(den), :s), td) +TransferFunction(num::Union{Vector{Int}, Vector{Float64}}, + den::Union{Vector{Int}, Vector{Float64}}) = + TransferFunction(num, den, 0.0) const s = TransferFunction([1, 0], [1]) From 0aa7056962e7f014fa7e0d0934be294877269f11 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sun, 2 Jan 2022 13:11:29 -0800 Subject: [PATCH 15/19] k --- docs/make.jl | 3 + docs/src/faq.md | 6 +- docs/src/index.md | 2 +- docs/src/sim.md | 18 +- docs/src/tfs.md | 17 +- docs/src/viz.md | 24 +- examples/examples.ipynb | 567 ---------------------------------------- examples/examples.jl | 110 +++++++- src/tf.jl | 12 +- src/viz.jl | 8 +- 10 files changed, 173 insertions(+), 594 deletions(-) delete mode 100644 examples/examples.ipynb diff --git a/docs/make.jl b/docs/make.jl index d84f0ec..e5b0ca5 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -1,6 +1,9 @@ using Documenter using Controlz +# using Controlz before all docstrings +DocMeta.setdocmeta!(Controlz, :DocTestSetup, :(using Controlz); recursive=true) + makedocs( root = joinpath(dirname(pathof(Controlz)), "..", "docs"), modules = [Controlz], diff --git a/docs/src/faq.md b/docs/src/faq.md index 1526850..222f359 100644 --- a/docs/src/faq.md +++ b/docs/src/faq.md @@ -10,7 +10,7 @@ yes, `Controlz.jl` is free and open. see the associated MIT license [here](https **I'm completely new to Julia and don't know where to start.** -Julia is a free and open-source, high-performance, dynamic programming language designed especially for numerical computing. See [here](https://julialang.org/learning/) for resources on learning Julia. I recommend [Jupyter Lab or Jupyter Notebook](https://jupyter.org/) as an interactive development environment for Julia. +Julia is a free and open-source, high-performance, dynamic programming language designed especially for numerical computing. see [here](https://julialang.org/learning/) for resources on learning Julia. I recommend the interactive [Pluto Notebook](https://github.com/fonsp/Pluto.jl) as an interactive development environment for Julia. **I found a bug.** @@ -18,4 +18,6 @@ please post an issue [here](https://github.com/SimonEnsemble/Controlz.jl/issues) **may I contribute to the package?** -absolutely! especially for fixing bugs, making documentation clearer, providing examples, etc. as for new features, please post an issue with your plan for a pull request first. +absolutely! especially for fixing bugs, making documentation clearer, providing examples, etc. + +as for new features or significant changes, please post an issue with your plan for a pull request first so I can approve. diff --git a/docs/src/index.md b/docs/src/index.md index c53d113..7dcc9ac 100644 --- a/docs/src/index.md +++ b/docs/src/index.md @@ -26,4 +26,4 @@ viz_response(data, plot_title="SO underdamped step response") `Controlz.jl` is an officially registered Julia package. install in the Julia REPL by typing `]` to go into package mode, then `add Controlz`. -I highly recommend using interactive [Pluto notebooks](https://github.com/fonsp/Pluto.jl) for coding in Julia, whose automatic package manager installs `Controlz.jl` upon running `using Controlz`. +I recommend interactive [Pluto notebooks](https://github.com/fonsp/Pluto.jl) for coding in Julia, whose automatic package manager installs `Controlz.jl` upon running `using Controlz`. diff --git a/docs/src/sim.md b/docs/src/sim.md index 51f1aea..439ac9c 100644 --- a/docs/src/sim.md +++ b/docs/src/sim.md @@ -12,18 +12,18 @@ pass the output $Y(s)$ in the frequency domain into the function `simulate` to i ```julia g = 4 / (4 * s ^ 2 + 0.8 * s + 1) # second order transfer function, underdamped -U = 1 / s # unit step input -Y = g * U # system output +U = 1 / s # unit step input +Y = g * U # system output -data = simulate(Y, 50.0) # simulate until t = 50, returns DataFrame -data[:, :t] # array of times, tᵢ's -data[:, :output] # array of outputs, yᵢ's ≈ y(tᵢ)'s +data = simulate(Y, 50.0) # simulate until t = 50, returns DataFrame +data[:, :t] # array of times, tᵢ's +data[:, :output] # array of outputs, yᵢ's ≈ y(tᵢ)'s ``` -we can then plot the time series via: +then plot the time series via: ```julia -viz_response(data, plot_title="SO underdamped step response") +viz_response(data, title="SO underdamped step response") ``` ![](SO_underdamped_step_response.png) @@ -41,7 +41,7 @@ Y = g * U data = simulate(Y, 15.0) # simulate until t = 15 -viz_response(data, plot_title="FOPTD step response") +viz_response(data, title="FOPTD step response") ``` ![](FOPTD_step_response.png) @@ -60,7 +60,7 @@ U = (s^2 - a^2) / (s^2 + a^2) ^ 2 data = simulate(U, 8.0, nb_time_points=300) # simulate until t=8, use 300 time points for high resolution -viz_response(data, plot_title=L"inverting an input $U(s)$", plot_ylabel=L"$u(t)$") +viz_response(data, title="inverting an input U(s)", ylabel="u(t)") ``` the `nb_time_points` argument allows us to return a time series with a higher resolution in time. if the plot of the response appears jagged, likely you need to increase `nb_time_points`. diff --git a/docs/src/tfs.md b/docs/src/tfs.md index 4f4fd32..12a01e9 100644 --- a/docs/src/tfs.md +++ b/docs/src/tfs.md @@ -1,3 +1,8 @@ +```@meta +DocTestSetup = quote + using Controlz +end +``` # transfer functions the response [output $Y(s)$] of a linear, time-invariant system to any input [$U(s)$] is characterized by a transfer function $g(s)=Y(s)/U(s)$. @@ -9,13 +14,21 @@ $$g(s)=\dfrac{5s+1}{s^2 + 4s+5}$$. we can construct $g(s)$ in an intuitive way that resembles the algebraic expression: -```julia +```jldoctest; output=false g = (5 * s + 1) / (s ^ 2 + 4 * s + 5) # way 1 +# output + 5.0*s + 1.0 +--------------------- +1.0*s^2 + 4.0*s + 5.0 ``` alternatively, we can construct a `TransferFunction` using the coefficients associated with the powers of $s$ in the polynomials composing the numerator and denominator, respectively, of $g(s)$. The coefficients of the highest powers of $s$ go first. -```julia +```jldoctest; output=false g = TransferFunction([5, 1], [1, 4, 5]) # way 2 +# output + 5.0*s + 1.0 +--------------------- +1.0*s^2 + 4.0*s + 5.0 ``` note that, under the hood, we defined `s` such that `s == TransferFunction([1, 0], [1])`. diff --git a/docs/src/viz.md b/docs/src/viz.md index 64a438c..9007563 100644 --- a/docs/src/viz.md +++ b/docs/src/viz.md @@ -1,5 +1,7 @@ # Visualization +the visualizations rely on [`CairoMakie.jl`](https://github.com/JuliaPlots/Makie.jl). + ## poles and zeros of a transfer function ```julia @@ -52,20 +54,32 @@ root_locus(g_ol) ![](example_root_locus.png) -## hipster plot theme +## modifying the figures + +all visualization functions return a `Figure` object from `CairoMakie.jl` that can be further modified. for example: + +```julia +g_ol = 4 / (s + 3) / (s + 2) / (s + 1) +fig = root_locus(g_ol) +ax = current_axis(fig) +xlims!(ax, -15, 5) +ax.xlabel = "real numbers" +``` -invoke the hipster plot theme used to make plots for this documentation by: +## cool plot theme +the custom plot theme can be invoked in `CairoMakie.jl` for other plots via: ```julia -using PyPlot -PyPlot.matplotlib.style.use("https://raw.githubusercontent.com/SimonEnsemble/Controlz.jl/master/src/hipster.mplstyle") +using Controlz, CairoMakie +set_theme!(cool_theme) ``` +more, `CairoMakie.jl` offers other themes [here](https://makie.juliaplots.org/dev/documentation/theming/predefined_themes/). ## detailed docs ```@docs - viz_poles_and_zeros viz_response + viz_poles_and_zeros nyquist_diagram bode_plot root_locus diff --git a/examples/examples.ipynb b/examples/examples.ipynb deleted file mode 100644 index 58334f2..0000000 --- a/examples/examples.ipynb +++ /dev/null @@ -1,567 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "using Polynomials\n", - "using Controlz\n", - "using Test\n", - "using DifferentialEquations\n", - "using Logging\n", - "using DataFrames\n", - "using PyPlot\n", - "PyPlot.matplotlib.style.use(\"https://raw.githubusercontent.com/SimonEnsemble/Controlz.jl/master/src/hipster.mplstyle\")" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.6320802858882434" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "τ = 3.45\n", - "g = 1 / (τ * s + 1) # FO system\n", - "data = simulate(g / s, 10.0) # unit step response\n", - "y_at_τ = interpolate(data, τ) # 0.63" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## First order plus time delay, response to step\n", - "\n", - "$g(s)=\\dfrac{Ke^{-\\theta s}}{\\tau s + 1}$\n", - "\n", - "response to step input $U(s)=1/s$." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "\n", - " 2.0\n", - "----------- e^(-1.5*s)\n", - "4.0*s + 1.0" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "K = 2.0 # gain\n", - "τ = 4.0 # time constant\n", - "θ = 1.5 # time delay\n", - "g = K * exp(-θ * s) / (τ * s + 1) # FOPTD transfer function" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "U = 1 / s # step input\n", - "Y = g * U\n", - "\n", - "data = simulate(Y, 15.0);" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject

)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "viz_response(data, plot_title=\"FOPTD step response\")\n", - "tight_layout()\n", - "savefig(\"../docs/src/FOPTD_step_response.png\", format=\"png\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Second order underdamped, response to step\n", - "\n", - "$g(s)=\\dfrac{4}{4 s ^2 + 0.8 s + 1}$\n", - "\n", - "response to step input $U(s)=1/s$." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = 4 / (4 * s ^ 2 + 0.8 * s + 1)\n", - "U = 1 / s\n", - "Y = g * U\n", - "data = simulate(Y, 50.0)\n", - "\n", - "viz_response(data, plot_title=\"SO underdamped step response\")\n", - "tight_layout()\n", - "savefig(\"../docs/src/SO_underdamped_step_response.png\", format=\"png\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## inverting an input\n", - "\n", - "$\\mathcal{L}[t \\cos(at)]= \\dfrac{s^2-a^2}{(s^2+a^2)^2}$" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "a = π\n", - "U = (s^2 - a^2) / (s^2 + a^2) ^ 2\n", - "data = simulate(U, 8.0, nb_time_points=300)\n", - "\n", - "viz_response(data, plot_title=L\"inverting an input $U(s)$\", plot_ylabel=L\"$u(t)$\")\n", - "tight_layout()\n", - "savefig(\"../docs/src/tcosat.png\", format=\"png\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## servo response of a control system\n", - "\n", - "![](simple_servo.png)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "gc = \n", - "1.0*s + 1.0\n", - "-----------\n", - " 1.0*s\n", - "gp = \n", - " 3.0\n", - "-----------\n", - "4.0*s + 1.0\n", - "Y_sp = \n", - " 1\n", - "-----\n", - "1.0*s\n" - ] - } - ], - "source": [ - "Kc = 1.0\n", - "τI = 1.0\n", - "pic = PIController(1.0, 1.0) \n", - "gc = TransferFunction(pic) # controller transfer functio\n", - "@show gc\n", - "\n", - "gp = 3 / (4 * s + 1) # process transfer function\n", - "@show gp\n", - "\n", - "g_ol = gc * gp # open-loop transfer function\n", - "\n", - "g_servo = g_ol / (1 + g_ol) # transfer function for servo response\n", - "\n", - "Y_sp = 1 / s # unit step set point change\n", - "@show Y_sp\n", - "\n", - "Y = g_servo * Y_sp # resulting output\n", - "\n", - "E = Y_sp - Y # error signal\n", - "\n", - "U = gc * E # resulting controller output\n", - "\n", - "# break output into P-action, I-action\n", - "U_Paction = Kc * E\n", - "U_Iaction = Kc * τI / s * E\n", - "\n", - "# simulate for y, u, ysp in the time domain\n", - "final_time = 12.0\n", - "y_data = simulate(Y, final_time)\n", - "u_data = simulate(U, final_time)\n", - "ysp_data = simulate(Y_sp, final_time)\n", - "u_Paction_data = simulate(U_Paction, final_time)\n", - "u_Iaction_data = simulate(U_Iaction, final_time)\n", - "\n", - "fig, ax = subplots(2, 1, sharex=true, figsize=(6, 6))\n", - "xlabel(L\"time, $t$\")\n", - "\n", - "ax[1].plot(y_data[:, :t], y_data[:, :output], label=L\"response $y(t)$\")\n", - "ax[1].plot(ysp_data[:, :t], ysp_data[:, :output], linestyle=\"--\", label=L\"set point $y_{sp}(t)$\")\n", - "ax[1].legend()\n", - "ax[1].set_ylabel(L\"system output $y(t)$\")\n", - "\n", - "ax[2].plot(u_data[:, :t], u_data[:, :output], color=\"C2\", label=\"total\")\n", - "ax[2].plot(u_Paction_data[:, :t], u_Paction_data[:, :output], color=\"C3\", linestyle=\"--\", label=\"P-action\", lw=2)\n", - "ax[2].plot(u_Iaction_data[:, :t], u_Iaction_data[:, :output], color=\"C4\", linestyle=\"-.\", label=\"I-action\", lw=2)\n", - "ax[2].legend()\n", - "ax[2].set_ylabel(L\"controller output $u(t)$\")\n", - "tight_layout()\n", - "savefig(\"../docs/src/simple_servo_response.png\", format=\"png\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## a full feedback control system\n", - "\n", - "![](full_feedback_control_system.png)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## viz poles and zeros of a transfer function" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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rh5tuuglDhw51/4eGhmthxcXFIS0tDZmZmaioqIDD4UBQUBCCgoIQHR3d4qnb9goPD8c//vEPfPHFF/jmm2+Ql5eH+vp6+Pv7o0ePHujduzfGjBnj9ut09GhbR7LqqD59+uDVV1/FypUrsXv37jbdy/Kxxx7Dtm3bnJcnqaqqgq+vLyIiIpCYmIjp06df8t6tREaTdHdnvhJRl1RYWOi8vdEbb7zBX0ZERF0Y55ARERERGYwFGREREZHBWJARERERGYwFGREREZHBOKmfiIiIyGC87EUn0DQNpaWl8Pf3b/N9/oiIiMi76bqO2tpahIaGQpYvfVKSBVknKC0txbx584zuBhERERngvffeQ3h4+CW3YUHWCfz9/QEA7733CiwWf4/u2253IC0tA1OmJMFsZpzejnmKh5mKhXmKJzPzNHJz8xAXF4uhQ6/26L6t1lrMm/eosw64FL6bOkHjaUqLxf+yFGQ+Pj6wWPz55SAA5ikeZioW5ikePz8/+Pj4wM/Pz+O/oxu1ZboSV1l6OZNJwdSp42EyXfpWNuQdmKd4mKlYmKd4JElCTEyM4XO8WZAJoLa2zugukAcxT/EwU7EwT/Goqmp0F1iQeTuHQ0V6+m44HMa/mch9zFM8zFQszFM8uq6jsLAQRl8FjAUZERERkcFYkBEREREZjAWZADi5VCzMUzzMVCzMUzxGT+gHeNkLr2c2mzBt2vVGd4M8hHmKh5mKhXmKR5ZlxMbGtnol/cuNBVkX53Col5w8qmkaysqqEBISZPibidzXXJ6yLMNsVrrEX3DUfpqmoaSkHOHh3fkZFQDzFIN6+AhQVQklKQm6rsNms8FksjQ8lpEBBHWDkji4U/vEgqyLslrrUFJSgZqaSy+vbrhPVh0qKmr5C1sALeVpNisICrIgPLwbFIW/BLyJqmrIyMjE1Knj+QtcAMzT+6mHj0BdvRrQdUAHdEskSkpKEBAQB3VHBtQNG4Afvn87syhjQdYF1dc7kJtbArNZQXR0KHx9zWip1tI0HdXVVgQGWiDLLMi83cV56nrD9XGqq20oL69GbW0d4uIiWJQREXWASzEGQN2wAaGDRyDbHIjQk99BPbKvYUNdb9gOnVeUsSDrgoqKyqEoEhISIlv9xatpOurr6+Hn58OCTAAt5RkY6I/g4ADk5BShpKQSPXp0N66TRETeqqrSWYw1ijqyDxPNPvCz17tuq+sN23cS/pndxei6Dqu1DsHBAW06CiJJDXOMeLZSDJfK09/fB926WVBVZTX8AobUdpIEBAVZ+BkVBPP0bkpSEpTJk5u0NynGACiTJ0NJSuqMbgFgQdbl2O0OqKoGf3/fNm0vSRK6dQvg/DFBtJZnUJA/7HYVdjuvEu4tTCYTkpPHwGTiCQkRME/vp4xrvihz2WbyZCjjOq8YA1iQdTma1nDko61zhHRdR11dPY+YCKK1PBWl4fpHmqZ1ZrfIDZqmITs7n5kJgnmKQRmXBAQFNf9gUFCnF2MAC7Iuq60HvHS94Ua3rMfE0FqePBDqfVRVw4EDJ6Cq/AUuAuYpBnVHBlBV1fyDVVUNj3cyFmRERER0xXBe2uJS22zY0OlFGQsyIiIiuiKoGc0XYzazT9NtN2xouEhsJ+GsRC8nSQ33VeOpLDEwT/FIkoSIiBAuvBEE8/RyQd0avmgvmBdSMHgEjgaGYVD1eUQ1XocM+GFJbbdO6xoLMi8nSRICAy1Gd4M8hHmKx2RSMG7cNUZ3gzyEeXq3xou8Nl4cVpk8GeWBUYiwqyiPiUJsTJjzSv3KjBm8Uj+1XcM9uBouJMq/2Lwf8xSPqmrIyspG374JvMOCAJin93MWWY33sjx4GhUVFQgLC2lYXSnBkHtZ8t3k5XQdP1wmweiekCcwT/Fomobjx7N5mQRBME8xKImDnRd91XUdVVVVzssNKUlJnV6MASzIiIiIiAzHgoycbA6guEaCzWF0T4iIiK4snEPm5SQJ8PExubUqb3eegnf2+WLDaRM0XYIs6Zh8tQMPjKzDqJiue4ue6dPvafGxRx99AJMm3eD8/7ZtO/H55+tx+nQOTCYF/fv3wezZMzBgQB+X55WXV+Cbb3bh4MEjyM3NR3l5BWy2Ovj7+yEuLhZ//evTLnO79u3LxKpVn+HUqe+hKAoGDuyH2bPvQN++Vzfp0+bN2/Hll5uQk3MWdrsd3boFISqqB6ZPvwnjxo0G4Jk8qWuRZQnx8VEuN4sn78U8xWSxGL+YigWZl5MkCRaLf4ef/+FBHzyT7gdZAjS94QtG0yVsPG1C2ikT/pxsw91Dm950tSu49toRLv+32x3Yty8TANC9e3dn+7vvfoTU1K/g6+uDPn2ugs1Wh/37D+Hw4WP4y1+exMCB/Zzb7t17EG+++QEAIDIyHFdfnQBfX19UV1dD13WXYmz9+nS8/vqSHwqxvqivt2Pv3oM4cOAwFi58DCNH/rgSa+3aDXjzzQ/g42NGnz5Xw2LxR2VlFc6cyUZFRaVzO3fzpK5HURQMHz7A6G6QhzBP8ciyjNDQUMiysScNWZB5OV3XUVtrg7+/X7tX5e3OU/BMuh90SFAvmkSu/lCc/WGzHwaEq13ySNnChY+7/P/115cAAG66aSJGjhwKoOEIVmrqV+jTpxcWLnwcYWEhABqOmC1e/G8sWZKCF198psm+f/azWzB37l0tvvb582V4++0P4e/vh0WLnkavXvHO13vuub/jn/98C++88zJ8fRsuNpiW9jXMZjP+85/FiIgIc+7H4XDAbv/xHLE7eVLXpKoqMjOzMHRoX+e9SMl7MU/xaJqG0tJSl+9mI3AOmZfTdaC+3tGhVXnv7PNFa0fdZalhu65u69YMfPXVZlx9dQJ+9asfT2WuW7cRAPDEE/OdxRgAXH/9WPTr1xvHjmWhurqmyf5aW87+9dffoL7ejqlTb3QWYwAwYsRQjBs3BhUVldi9e7+z3Ww2Q5IaVlBeyGQywd/fz/l/d/KkrknTdOTkFEDTGKoImKeYrFar0V3gEbIrlc0B55yxS1F1CWmnTLA5AL8u+m4pKCjC668vgcXij9/97n9hNpudjx0/fhImk4KlSz9u8rySklIAQGFhMQIDA9r1mllZpwEA11zTdGn0sGGJ2L79W2Rlncb48dcCAH7xixlYtOgVPPLIAiQnj8eNN96AAQP6tus1iYhIXF30VyxdblV1UqvFWCNNl1BVJ8HP1PX+IlRVDS+99B9YrbV47LEHERPTw+Xx6morVFXFt9/ua2EPQG2trd2vW1PT8NdUSEhwk8ca2xq3ARqOnL344rNYsWINNm7cgrS0r9GrVzxmz74DY8eOavfrExGRWFiQeTlJAnx9fdq9Ki/IV4cs6W0qymRJR5Bv1yvGAODTT9fh+PGTGDduNJKTxzd5PCDAAputDitXvu3RCZsBAQ0rcsrKKhAf39PlsbKyCpdtGvXqFY8FCx7F+fNl2LJlB9asWYsXXngF99xzJ+68czqAjudJXZcsy+jfP8HwCcPkGcxTPJIkISgoyPB5u3xHeTlJkuDv79vuN5KfCZh8tQOKdOlCS5F0TOnt6JKnK/PzC7BixWoEBQXioYf+p9lt+vbthfr6ehw/ftKjr914WYvMzKNNHjt48LDLNhcLCwvBjBnT8PrrLyI4uBuWL18Nm63hKF1H86SuS1FkDBjQi7fZEQTzFI8kSQgODjb8e5fvKC+n6zqqq63OWz60x/0j6tDavFRNb9iuK3rnnY9QX2/HPffciW7dgprd5qc/nQQA+Ne/3sGZMzkuj+m63mSSfVtNnDgePj4+WLduI7Kzc53t+/cfwjff7EZISDDGjBnubN+z5wAqK6tc9iFJEhRFhqqqzpWW7uRJXZPDoWLHjoNwOLreSmVqP+YpHk3TUFxcbPjtsLrgcQ9qD11v+ILQdbT7NNfoWBV/TrbhD5sbrkOmXnD6UpF0aDrw52Rbl7zkxeHDx7BnzwFIkoQ9ew5i796DLo9ff/1Y3HBDEsaMGYHbbrsZqalf4fHHn0bPnjGIjAxHXV09cnLO4p57ZmLKlAntfv3Q0O548MF78dpr7+Lxx5/BwIF9Ybc7cOLESciygkcf/RV8fHyc27/88puwWmsRHd0DERFhcDgcOHnyDGprbRgzZgSCggIBuJcndU26rqO4uIxFtiCYp5jq6ow/8MCC7Ap399B6DAhX8c4+X6SduuBK/b0duH9E171Sf2FhEYCGL8ddu5pO2O/VK8H571/+cg6GDBmIdes2ISvrNPLzC9G9ezDi43uiR4+IDvdh8uSfIDw8FCtXpuLEiVNQFAUjRlzT5Er9qqph1qzbsWPHbpw7V4jMzEKYzSZERUVi7NhR+NnPbulwH4iISAwsyAijYlSMirHC5mhYfRnkq3fJOWMXmjTpBpdbI7VmzJgRGDNmRKvbtXe/w4cPwfDhQy65jaLIuPXWm3DrrTe1eb9ERHRl6eK/dqk1koQfJoG7vy8/E7rkpS2uJJ7Mk7oGRZExbFg/TgIXBPMUjyRJCAkJMXxSPwsyLydJkvP2POT9mKd4ZFlGQkKM0d0gD2Ge4pEkCQEBAYYXZCzxvZyu66isrOEEU0EwT/E4HA5s3rwLDoej9Y2py2Oe4tE0DQUFBYavsmRB5uV0veHNxN/fYmCe4tF1oKrKykwFwTzF1BUKbBZkRERERAYTYg6ZrutYu3Yt1q5di6KiIoSEhCA5ORkzZ86EyeS5Ie7cuRN//etfER4ejnfeecdj+yUiIqIrmxBHyN5//3289dZbKC8vx+DBg1FfX4+UlBT8/e9/99hrnDp1Cv/4xz8MP8d8MUkCAgL8uSpPEMxTPIoiIylpKFflCYJ5ikeSJISHhxs+qd/rj5BlZ2cjNTUVERERWLx4MUJDQ2G1WrFgwQLs2LEDe/fuxciRI916jerqajz//PMIDQ1FTU2Nh3ruGZIkwWz2+hjpB8xTPLIsIzIy1OhukIcwT/FIkgQ/Pz/DCzKvL/E3b94MTdMwY8YMhIY2fEgsFgvmzJkDANi4caPbr/Gf//wHNTU1ePrpp+Hr6+v2/jxJ03SUl1dBa+2mlOQVmKd47HYH1q7d5rxfKXk35ikeTdOQl5dn+Bkwr/9T/MiRIwCAESNcr8KemJgIk8mEo0ePurX/rVu3Ytu2bXj88cfRs2fPNj3HbrfDbrc7/2+1Wn9odzg/xLIsQVEUqKrq8stXVRveELquu7RLUkMVr+v6Rat79Au2h8v2De2ufWupXZab7rul1+ys9ouLkithTD9e7qLh+c2t5NJ1HXa7w3nKRJIAk8kETdOc75+GdgkmkwJV1Vy+aFp678myDEWRf7iX5o/tiiJDlmU4HA6X/jS2X/yLyWRSAKDJzZdbajebm+u7OGOy2x1wOFQ4HGoLY/W+Mf3Yd3Fyas+YHA611e9ybxuTiDm1dUxA4+9QzdlXT42pPZcw8vqC7Ny5czCZTIiOjkZ6ejrefPNNPPjgg5g4cSJCQ0NRVFQEm80GPz+/du/barXinXfeQVJSEiZOnNjm561atQopKSlN2tPSMpw3nI6Pj8Lw4QOQmZmFnJwC5zZ9+8ZDksywWm2oq6t3tvv7+8LX1wdVVVaXN5nF0jCuqirXU6lBQRZIkozKymqX9m7dAqHrGqqqrC7t3bsHweFQUVNT62yTZRndugWgvt6O2tofb7xqMikIDLTAZqt36aOPjwkWiz9qa22or//xzerr6wN/f1/U1NS6vFlbGlNAgD/MZlOTvl9JY2ooxpqOyc/PF5qmY+vWfc5l2kFBFiQnj0FubgEOHDjh3DYiIgTjxl2DrKxsHD+e7Wxv6b3Xv38CBgzohV27DqO4uMzZPmxYPyQkxGDr1n0u/UlKGorIyFCkpWW4/AwmThwNf39frFu33aXvU6eOR21tHdLTd7v83KdNux4lJeXIyMh0+bmINqYdOw5i0iSxxiRiTq2N6dSpXADAhg07hRmTiDm1Z0yNcnPzkJub59ExTZjQ9ilTku7lV6CcMWMGLBYLli1bhj/96U/Yu3cvRo0ahWeeeQaPP/44Tp06hSVLliAsLKzd+3777bexYcMG/Pvf/0ZERMNNqO+//34AuOQqy+aOkM2bNw8ffvg6LBZ/AC1X6/X1DuTkFOOqqyJdrth+qSNklZU1CApyvcrwlXA0ScQx6bqOqqoadOsW8MN+XMdUX2/H6dMFiIsLh5+fj3Mf/Ou3647Jbndgw4admDIlCf7+vkKM6ce+i5NTW8dks9Vj/fodmDx5LMxmkxBjEjGn9ozp0KEzyM7ORVxcLIYM6eXRMdXX12P27AeRkpICi8WCS/H6I2QXGj9+PI4ePYpx48a5tHdkol5+fj7WrVuHO++801mMtZXZbIbZbG6m3dRkwraiKFCUH//f+MaSJAmy3LTfkiS5rMDT9Ya/FGRZanacLQ29ufaL9210e3Pjb9i+2eYu1feOjqkxz4bnt7zv5t5Lsiw7D79fSFHkZleEXfzea9T4xdK0vfmvi5YWIbSnvaW+izAmk0nBxImjnQW0CGNqa7uIY/L1NTuPhlz4nevNYxIxp/aMSZIk9OjRA4qiNHltd8d04cGZ1nh9Qebv7++cozVp0iRMmjTJ+Vh1dcNpoNaq0uakpKTA19cX06dP90xHLyNJ8vq1GXQB5ikef/+utRiI3MM8xaM0V3l2Mq8vyKKjo3HixAkUFBQgKirK2W6z2XD+/HmEhIR0aP7Y9u3b4XA48Itf/KLZx6dPn45Zs2a1+Hhn0XWgsrIa3boFtnjkiNpm+fLVSElZ49L28MO/xJQpEzqtD8xTPA6HinXrtmPq1PG8pIkAmKd4dF1Hfn4+EhLiDO2H17+bBg0ahBMnTmDfvn2YOnWqs/3w4cNwOBwYOHBgs89bv3493n//fVx33XV4+OGHmzze0rXL9u/fDwAYPnx4m1ddknfo2TMa117bsFr37NlzyMs7Z3CPiIjoSuH1BVlycjJSU1OxevVqJCUlISQkBDabDcuXLwcAl1OYF1q2bBlqamqQlpaG22+/vUlxtXDhwmaf1zipv6XHyXvdcEMSbrghCUDzR8uIiIguF68vyK666ipMnz4dqamp+PWvf42+ffvi+++/R1lZGcaOHYvRo0e3ug+jLwZHREREVzYhZg/PmzcP999/P4KDg3Ho0CGYTCbcdddd+L//+78WnzNnzhwEBARg0qRJiI+P78TeepYkwa35RurhI1AzMpp/LCMD6uEjbvSO2svdPKnrMZkUTJ06vsWVaeRdmKd4JElCTExMh67I4Elef4QMaPhhTp8+vV0rIm+++WbcfPPN7X6tS11/zCi6rnVoZZ56+AjU1at/uAopoIxL+vGxHRlQN2xwXo9BSRzssf56wpkzOVi5MhWnT2fj/PkyaJqGHj3CMX78WNxxx1Tn9d6AhiOg69ZtxPr16cjPL0RgoAWjRw/HL37xM4SGdnerH1lZp7FyZSoOHz4Gu92BuLgY3HrrTUhOHt9k282bt+PLLzchJ+cs7HY7unULQlRUD0yffhPGjfvxSG5H86Suq7a2DkFB7V/tTV0T8xSPqqowuiTit76X03Wgqsra7C12LsWlGAOgbtgAdUfDkTJnMfbDC6irV3e5I2WnT3+Pb77ZherqGgwe3B+DB/dHZWU1Pv74Uzz11F9gtf54df5//vMtvPXWhzh/vgyJiQMQEBCAtLSv8ZvfPIPi4pIO92HHjt34/e+fw+7d+xEZGYE+fXohJycP//znm1izZp3LtmvXbsA///kmzpzJRq9eCRg2bAjCw8Nw5kw2Kioqndt1NE/quhwOFenpu5tcMJK8E/MUj67rKCwsbNdtji4HIY6QUQdUVTa5tL26YQPUnTuBqirXbXW9Yfsu6Kc/Tcbdd98JAKitteGll17Hrl378dFH/8UDD9yDHTt24+uvv0GvXgl4/vmnEBgYAABYtmwVVq78DG+++QGefvqJdr9uZWUVXnnlLfj5+eHZZ3+L/v37AADOns3H7373HJYv/wRTpkxAQEDDX9FpaV/DbDbjP/9ZjIiIH+8a4XA4eJNiIiLiEbIrlZKUBGXy5KYPXFyMAVAmT4aSlNR02y7G398PDz/8S/j5+WLjxq1wOBxIS/saAHDffXc5izEAmDXrDoSHh2L37gMoKytv92tt3rwdtbU23HPPnc5iDAB69ozBTTdNRF1dPQ4d+s7ZbjabIUlwuU8m0HAVaH//9l8nj4iIxMIjZFewxjljztOTzW0zebLL3LKurnv3YFx99VU4evQ4cnPzcfLkGciyhKFDB7lsZzKZkJg4EF9//Q1Onvweo0cPa9frHD9+EgCwffu32Lcv0+WxwsJiAEBBQZGz7Re/mIFFi17BI48sQHLyeNx44w0YMKBvB0ZI3ogTwMXCPMVj9IR+gAWZ15NlCd27B3X4+cq4pOZPUwJAUJBXFWONwsJCAAA1NTWoqbEiMDCw2dtidO/ezblde1VXNzznwqNgF7PZbM5/jxgxFC+++CxWrFiDjRu3IC3ta/TqFY/Zs+/A2LGjnNu5myd1PWazCdOmXW90N8hDmKd4ZFlGbGxss/fE7EwsyLycrutwOFSYTEqHKnx1R0bzxRgAVFVB3ZHhdUVZVVXDPUz9/f0REGBBdXU1VFVtUpSVlzfMi7vwVGaj1n6UjXPDXnzxWQwY0OfSG/+gV694LFjwKM6fL8OWLTuwZs1avPDCK7jnnjtx550NK4TdzZO6Hk3TUFJSjvDw7oZ/4ZP7mKd4dF2HzWaDyWTsylm+m7ycrgM1NbUdWpXnspqypW0uWH3pDerq6pCVdRomkwk9e8agb99e0DQdmZlHXbZzOBw4fPgYJElC7969muwnIKChSLPZ6pp9nb59rwaAJvtti7CwEMyYMQ2vv/4igoO7Yfny1c6jae7kSV2TqmrIyMiEqvIC1CJgnuLRdR0lJSWGr7JkQXaFUjNaKMaCmp4uUzdsaPHisUbLzy+Ew9GwSlHXdbz//seoqbEiKWkkfH19cNNNyQCADz5Y6TzNCAArV6aipOQ8rr12BEJCgpvst/G054EDh5xtdrvD+VrJyePh5+eLlStTsXPnnibPv/B0JQDs2XMAlZWuRyIlSYKiyFBVlSstiYiucDxleaUK6tZwXu6CvwgaJ/A3OXImSQ3bd0Hbt3+LgweP4OqrE1BSUoq8vHMIDu6Ge++9CwAwduxIJCePx+bN2/Hgg79F375Xo7i4BLm5+QgPD8WvfnVvs/sdOnQQ/P39sGfPQTz++B9gsfjj++9zsXDhYxg0qD9CQrrj0Ud/hZde+g9eeOEVREaGIyYmCpIk4dy5Qgwc2BePPz7fub+XX34TVmstoqN7ICIiDA6HAydPnkFtrQ1jxoxAUFBgp/y8iIioa2JB5uUkqWFCYnunGzVeeb/x4rAXrqZ0WX0pSVBmzOhyV+pvNHhwf9TV1ePEiVNQFAXjx1+Le++diR49IpzbPPLIA+jT52p89dUmHDr0HQIDLZgyZcIlr9QfFBSIhQsfx/vvpyA7+yxMJgV9+vSCxfLjHIPrrhuD2NhorF69FocOHcXhw98hICAAkZHh6Nu3t3M7VdUwa9bt2LFjN86dK0RmZiHMZhOioiIxduwo/Oxntzi37Wie1HVJEhAUZGGmgmCeYjKZjC+HjO8BuUWSJHTr1nRSels4i6yqyibXGVPGJQESgKBuXbYYAxoKssYLw7ZElmXccstk3HJLM9ddu4ShQwfhH/947pLbXHVVHJ54Yv4lt1EUGbfeehNuvfWmVl/TnTypazKZTEhOHmN0N8hDmKd4ZFlGVFSU4Ys0OIfMy+m6jrq6+g5PRlQSB7d40VclKalLF2MicjdP6no0TUN2dj40jZPARcA8xaPrOmpqagz/3mVB5uV0veFGt/z9LQbmKR5V1XDgwAmuyhME8xSPrusoKytjQUZERER0peMcMvJKkybdgEmTbjC6G0RERB7BI2ReTpLww1Xdje4JeQLzFI8kSYiICOGdFwTBPMXk6+trdBd4hMzbSZKEwEBjb/dAnsM8xWMyKRg37hqju0EewjzFI8syIiIiuMqS3KPr+g+TwDkLXATMUzyqquHYsTOcBC4I5ikeXddRUVFh+PcuC7Iuqq3vC13HD5dJuLz9oc7RWp5Gf2FQ+2mahuPHs3mZBEEwT/Houo6qqirDv19ZkHUxitIQCe9tSM2pq2t4X5hMisE9ISIiT2JB1sWYzSb4+ppRUWH8Reqoa1FVDaWlVQgI8GVBRkQkGE7q74LCw7shL+88zp4tQXBwAMxmU4ur7nRdd17dnat+vN/Feep6QyFWW1uHiooaaJqO6OgQo7tJ7SDLEuLjoyDL/HyKgHmK6cL7FBuFBVkX1K1bwxujpKQSeXnnDe4NdQWKIsNi8UVkZHf4+PBj600URcHw4QOM7gZ5CPMUjyzLCA0NNXyVJb/Zu6hu3Szo1s0Cu91xydU8qqri+PFs9O+fAEXhaSxv11yesiz9cJSUf5F7I1VVkZmZhaFD+/IzKgDmKR5N01BaWoqIiDBD+8GCrIszm00wm1t+3G53IDe3AEOG9IHZzDi9HfMUj6bpyMkpQGJiH/D3t/djnmKyWq0AjC3IOKmfiIiIyGAsyIiIiIgMxoLMy8myjP79EwyfjEiewTzFw0zFwjzFI0kSgoKCDJ+ny0kqXk5RZAwY0MvobpCHME/xMFOxME/xSJKE4OBgwwsylvhezuFQsWPHQTgcqtFdIQ9gnuJhpmJhnuLRNA3FxcWG3w6LBZmX03UdxcVlvKq/IJineJipWJinmOrq6ozuAgsyIiIiIqOxICMiIiIyGAsyL6coMoYN6wdFYZQiYJ7iYaZiYZ7ikSQJISEhhk/q5ypLLyfLMhISYozuBnkI8xQPMxUL8xSPJEkICAgwvCBjie/lHA4HNm/eBYfDYXRXyAOYp3iYqViYp3g0TUNBQQFXWZJ7dB2oqrKCC37EwDzFw0zFwjzF1BUKbBZkRERERAZjQUZERERkMBZkXk5RZCQlDeWKH0EwT/EwU7EwT/FIkoTw8HDDJ/VzlaWXk2UZkZGhRneDPIR5ioeZioV5ikeSJPj5+RlekLHE93J2uwNr126D3W78hERyH/MUDzMVC/MUj6ZpyMvL4ypLch9vcisW5ikeZioW5imernBvUhZkRERERAZjQUZERERkMBZkXs5kUjBx4miYTIrRXSEPYJ7iYaZiYZ7ikSQJPXr04KR+cp+/v6/RXSAPYp7iYaZiYZ7iURTjC2wWZF7O4VCxbt12TjIVBPMUDzMVC/MUj67ryM/PN3xiPwsyIiIiIoMJcWFYXdexdu1arF27FkVFRQgJCUFycjJmzpwJk6njQ8zLy8Mnn3yCAwcOoLy8HN27d8fw4cNx9913IyQkxIMjICIioiuZEEfI3n//fbz11lsoLy/H4MGDUV9fj5SUFPz973/v8D4PHz6MRx99FBs3bkRgYCAGDx6M2tpabNiwAQsWLIDdbvfgCIiIiOhK5vVHyLKzs5GamoqIiAgsXrwYoaGhsFqtWLBgAXbs2IG9e/di5MiR7d7vVVddhSFDhuDuu+9G7969AQBVVVV48sknkZubi2+//Rbjx4/39HDazWRSMHXqeK74EQTzFA8zFQvzFI8kSYiJieEqS3dt3rwZmqZhxowZCA1tuL+YxWLBnDlzAAAbN27s0H4DAwPx7LPPOosxAAgKCsKkSZMAAGfPnnWz555TW1tndBfIg5ineJipWJineFTV+EUaXn+E7MiRIwCAESNGuLQnJibCZDLh6NGjHn29urqGD2JwcHCL29jtdpdTmlar9Yd2h/P+Z7IsQVEUqKoKTftxZYcsy1AUGQ6H6rLiQ1FkyLIMh8OBCxeCaJqO9PTdmDx5LMzmH+Ns/Ovt4pVALbWbzSZomgZV/fFeXpIEmEzNtUswmRSoquZy7y9Pjamx/eJ7xV0JY7LbHUhP342f/vQ6mM0mIcbUWrvoY2rMdMqUJPj7+woxph/7Lk5ObR1TXZ3d5TtXhDGJmFN7xqTrOgoLCxEXF+vsq6fG1J6Vm15fkJ07dw4mkwnR0dFIT0/Hm2++iQcffBATJ05EaGgoioqKYLPZ4Ofn5/Zr2e12bNq0CQEBAbjuuuta3G7VqlVISUlp0p6WlgEfHx8AQHx8FIYPH4DMzCzk5BQ4t+nfPwEDBvTCrl2HUVxc5mwfNqwfEhJisHXrPlRVWZ3to0cPBgCkp+92eSNMnDga/v6+WLduu0sfpk4dj9raOqSn73a2mUwKpk27HiUl5cjIyHS2BwVZkJw8Brm5BThw4ISzPSIiBOPGXYOsrGwcP57tbPfUmJKShiIyMhRpaRlX7JgcDhU2W71QYxIxp/aMaceOg5g0SawxiZhTa2M6dSoXALBhw05hxiRiTu0ZU6Pc3Dzk5uZ5dEwTJrR9ypSkG33hDTfNmDEDFosFy5Ytw5/+9Cfs3bsXo0aNwjPPPIPHH38cp06dwpIlSxAWFub2a7388stIT0/H/PnzMXXq1Ba3a+4I2bx58/Dhh6/DYvEH4NkjZF999Q2PkAkyJrvdgQ0bdvIImUBjasyUR8jEGJPNVo/163fwCJlAYzp06Ayys3MRFxeLIUN6eXRM9fX1mD37QaSkpMBiseBSvP4I2YXGjx+Po0ePYty4cS7tnpio9+abbyI9PR0333zzJYsxADCbzTCbzc20m1yKJqDh6sDNXSC4pQmjF1/Gw253wGRSmt1342s238em7bLc8EZra7uiNHw4m7a7N6ZL9bG97d44JpNJgSRJkCRJmDG11i76mEwmxdkHUcbUlnZRx9Tcd663j0nEnNozJkmSIMtyk9d2d0ztuSKD1xdk/v7+zjlakyZNck66B4Dq6moAaLUqbc3bb7+NtWvXYsKECZg/f75b+/I0s9mEadOuN7ob5CHMUzzMVCzMUzyyLCM2NrbZwq5T+2Hoq3tAdHQ0HA4HCgoKXNptNhvOnz+PkJAQt+aPrVy5Ep9//jluuOEGPProo4YHdjFN01BUVOpyaJa8F/MUDzMVC/MUj67rsNlsvHWSuwYNGgQA2Ldvn0v74cOH4XA4MHDgwGaft379esyePRuvvfZai/s+evQoli9fjiFDhuCxxx7rEjcfvZiqasjIyHQ5h07ei3mKh5mKhXmKR9d1lJSUsCBzV3JyMiRJwurVq1FW1rDqw2azYfny5QDgcgrzQsuWLUNNTQ3S0tJavKbYBx98AB8fHzzxxBNu3YKJiIiI6FK8vsq46qqrMH36dKSmpuLXv/41+vbti++//x5lZWUYO3YsRo8e3eo+mjv0XFxcjKNHjyIwMBBvvPFGs8/79a9/je7du7s7BCIiIrrCeX1BBgDz5s1DREQEvvzySxw6dAghISG46667MHPmzBafM2fOHCxduhRjx45FfHx8k8eLi4sBNCwM+Pbbb5vdx/333++ZAbhBkhqux2LwHR/IQ5ineJipWJinmLrCWTCvvw6ZN7BarZg1axZSUt5yXoeMiIiIjJeZeQZ2uwqzWcHQob08um+rtRazZv2qTdch8/o5ZFc6TdOQnZ3PFT+CYJ7iYaZiYZ7i0XUdNTU1nNRP7lFVDQcOnOCKH0EwT/EwU7EwT/Houo6ysjIWZERERERXOhZkRERERAZjQeblJElCRESIR+7XScZjnuJhpmJhnmLy9fU1ugtiXPbiSmYyKRg37hqju0EewjzFw0zFwjzFI8syIiIiDL81Io+QeTlV1XDs2BlOMBUE8xQPMxUL8xSPruuoqKjgpH5yj6ZpOH48m0uwBcE8xcNMxcI8xaPrOqqqqliQEREREV3pWJARERERGYwFmZeTZQnx8VGQZa74EQHzFA8zFQvzFFNrtzXqDFxl6eUURcHw4QOM7gZ5CPMUDzMVC/MUjyzLCA0N5SpLco+qqti//xhUVTW6K+QBzFM8zFQszFM8mqahtLTU8IUaLMi8nKbpyMkpgKYZuzqEPIN5ioeZioV5islqtRrdBRZkREREREZjQUZERERkMBZkXk6WZfTvn2D4ZETyDOYpHmYqFuYpHkmSEBQUZPj9SbnK0sspiowBA3oZ3Q3yEOYpHmYqFuYpHkmSEBwcbHhBxhLfyzkcKnbsOAiHgyt+RMA8xcNMxcI8xaNpGoqLi7nKktyj6zqKi8sMvwcXeQbzFA8zFQvzFFNdXZ3RXWBBRkRERGQ0FmREREREBmNB5uUURcawYf2gKIxSBMxTPMxULMxTPJIkISQkxPBJ/Vxl6eVkWUZCQozR3SAPYZ7iYaZiYZ7ikSQJAQEBhhdkLPG9nMPhwObNu+BwOIzuCnkA8xQPMxUL8xSPpmkoKCjgKktyj64DVVVWcMGPGJineJipWJinmLpCgc2CjIiIiMhgLMiIiIiIDMaCzMspioykpKFc8SMI5ikeZioW5ikeSZIQHh5u+KR+rrL0crIsIzIy1OhukIcwT/EwU7EwT/FIkgQ/Pz/DCzKW+F7Obndg7dptsNuNn5BI7mOe4mGmYmGe4tE0DXl5eVxlSe7jTW7FwjzFw0zFwjzF0xXuTcqCjIiIiMhgLMiIiIiIDMaCzMuZTAomThwNk0kxuivkAcxTPMxULMxTPJIkoUePHpzUT+7z9/c1ugvkQcxTPMxULMxTPIpifIHNgszLORwq1q3bzkmmgmCe4mGmYmGe4tF1Hfn5+YZP7GdBRkRERGQwFmREREREBmNBRkRERGQwFmRezmRSMHXqeK74EQTzFA8zFQvzFI8kSYiJieEqS3JfbW2d0V0gD2Ke4mGmYmGe4lFV4xdpsCDzcg6HivT03VzxIwjmKR5mKhbmKR5d11FYWMhVlkRERERXOhZkRERERAZjQSYATi4VC/MUDzMVC/MUj9ET+gHA5Imd1NfXIysrC8XFxdA0rcXtkpOTPfFydAGz2YRp0643uhvkIcxTPMxULMxTPLIsIzY2FrJs7DEqtwuyrKwsLFq0CKWlpZecECdJEguyy8BaryH7XCUSorvB4sMDnt5O0zSUlJQjPLy74V8O5BnMVCzMUzy6rsNms8FkshjaD7cLstdffx0VFRX4n//5H/Tq1cuQN6iu61i7di3Wrl2LoqIihISEIDk5GTNnzoTJ5N4Q9+/fjxUrVuD06dPw8/PDqFGjMHfuXISEhHio9x2zO0/BO/t8seG0CZoeAlnSMflqBx4YWYdRMVz9461UVUNGRiamTh3PL3tBMFOxME/x6LqOkpISBATEGdoPtwuywsJCDBo0CLfddpsn+tMh77//PtasWYOAgAAMHjwY33//PVJSUpCTk4Mnn3yyw/vdtWsXXnjhBUiShEGDBqGsrAybN2/Gd999h5deegmBgYEeHEXbfXjQB8+k+0GWAE1vOO+t6RI2njYh7ZQJf0624e6h9Yb0jYiIiNrP7YJs5MiR2LlzJz777DPYbDbnHDJ/f/9OKdKys7ORmpqKiIgILF68GKGhobBarViwYAF27NiBvXv3YuTIke3er91uxxtvvAEA+POf/4zExETouo7XX38d69evx3//+1/cd999Hh5N63bnKXgm3Q86JKgXnSFWfyjO/rDZDwPCVR4pIyIi8hJuH28dP3486uvr8e677+Kjjz7CihUrsGLFCqxZs8YT/WvV5s2boWkaZsyYgdDQUACAxWLBnDlzAAAbN27s0H4PHDiAkpISjB07FomJiQAa5sHNnTsXiqI4X7ezvbPPF3Iri0FkqWE78j6SBAQFWdAFFvyQhzBTsTBPMbk7vckjfXB3BytXrkS3bt3wm9/8BtHR0c6lo511bv3IkSMAgBEjRri0JyYmwmQy4ejRox3ab+PzLt5vYGAg+vTpg+PHjyM/Px89e/Zs8ly73Q673e78v9VqBQBkZjbMQ2sky3KTok6SJEiS1Gx7vSYj7dRQ6Lj0N4GqS1h/0oRd+87AR266HwBNFmDIsgxd1z3S3p4xtbe9ub6LNqbQ0DAcOZIj1Jgu1X4ljCk0NAyHD2cLNSZ32r19TI15ijQmEXNq65hUVUdkZCTsdhUHDpzy6Jjq6tp+my23C7Lc3Fz0798fw4YNc3dXHXLu3DmYTCZER0cjPT0db775Jh588EFMnDgRoaGhKCoqgs1mcymE2rpfAOjZsydycnLwhz/8Addeey0eeugh9OzZE8ePH8e5c+eaLchWrVqFlJSUJu25uXnw8fEB0HAULzQ0FKWlpc6CDQCCgoIQHByM4uJilyBDQkJgNwe3Wow10iGholaHtSTXpT0mJgaqqqKwsNDZJkkSYmNjYbPZUFJS4mw3mUyIiopCTU0NysrKnO2+vr6IiIhARUUFqqqqnO0dGVNAQAAKCgrgcDic7eHh4fDz80NeXp7Lm7tHjx5QFAX5+fnCjyk6Ohqapgk1JhFz4pg4Jo7J+8fUrVs3FBUVufTdU2MKCwtDW0m6mzdv+tWvfoWqqiqMHTv20i8kSXjkkUfcealmzZgxAxaLBcuWLcOf/vQn7N27F6NGjcIzzzyDxx9/HKdOncKSJUva9UMBgGeeeQYHDhzAa6+9ht27d2Pp0qXw9fXFqlWr8O677yI1NRW/+c1v8JOf/KTJc5s7QjZv3jwsWPCk20fIZm5p/QgZAEjQ8fENB3mEzMvGpGkacnPzEB/f09kfbx9Ta+2ij6kx07i4WJhMJiHG5G67N49JVVXk5JxFXNyP163y9jGJmFN7xlRf70B+fj6ioqLg62v26Jjq6urw/POLkJKSAovl0pfVcPsI2bBhw7B+/Xps3rz5kttdroLsQuPHj8fRo0cxbty4Jq/dXhf+UEeMGIFPP/0UY8aMadNzzWYzzGZzk/ahQ6+GxeLf7r5caMpZBzaeNjkn8DdHkXRM7u3AmBG93Hot6nx2uwO5uXlITLwKZrPxcxrIfY2ZDhnSi5kKwG53ICfnLPMUSONpSl9fM4YN6+3RfVuttW3e1u1300MPPYSHHnrI3d10mL+/v/Pw46RJkzBp0iTnY9XV1QDQalXanICAAOc+Bg0ahA8//NAj+3XX/SPqkHbq0rFpesN2RERE5B28/qp20dHRcDgcKCgocGm32Ww4f/48QkJC2j1/rHG/AJqcDwaAvLw8l2060+hYFX9OtkGCDkVyPTSqSDok6Phzso2XvPBSkiQhIiKkQ0d1qWtipmJhnmLy9TX+ygQdKsiKi4tRWVnZ5u0rKytRXFzckZdq1aBBgwAA+/btc2k/fPgwHA4HBg4c2Ozz1q9fj9mzZ+O1115r136tViuysrIQHByMmJgYd7vfIXcPrceqmTWY3NsB+YeiTP7hNOWqmTW8KKwXM5kUjBt3DW9eLBBmKhbmKR5ZlhEREWH4nRc69OoPPPAA/v3vf7d5+9deew0PPPBAR16qVcnJyZAkCatXr3autLDZbFi+fDkAuJzCvNCyZctQU1ODtLQ0nD17tsnjw4YNQ1hYGDIyMlwunbF06VKoqork5GRDwxsVo+KNW6w4NL8cKyYexqH55XjjFiuPjHk5VdVw7NgZqGrnX+OOLg9mKhbmKR5d11FRUdFkQn5n69AcsuZWLxjlqquuwvTp05Gamopf//rX6Nu3L77//nuUlZVh7NixGD16dKv7aO4Cr2azGQ8++CAWLVqEhQsXYtCgQSgvL0dubi6ioqJw5513Xo7htJuPrKHo+1PwGRQNAc5AX/E0TcPx49no3TsOisI8RcBMxcI8xaPrOqqqqhAa2t3QfnR4Uv/Zs2fx0UcftWnb3Nzc1jdyw7x58xAREYEvv/wShw4dQkhICO666y7MnDmzxefMmTMHS5cuxdixYxEfH9/sNmPHjsUzzzyDlJQUHD9+HL6+vpg4cSLuu+8+w+5jSUREROLpcEGWn5+PlStXtnn7yzkBUpIkTJ8+HdOnT2/zc26++WbcfPPNrW43cuTIDt0Lk4iIiKitOlyQXX311Zg2bVqbtv3iiy9w5syZjr4UXYIsS4iPj4Lc2g0uySswT/EwU7EwTzEZcRmri3W4IAsPD29xwvzFvv32WxZkl4miKBg+fIDR3SAPYZ7iYaZiYZ7ikWUZoaGh3rnKsr260iIA0aiqiv37j0FVubpSBMxTPMxULMxTPJqmobS0tNkFfp2pQ0fIUlNT27X9woULO/Iy1AaapiMnpwCJiX2g8LI4Xo95ioeZioV5iqnhjj/tu+e1p3HNLhEREZHBWJARERERGYwFmZeTZRn9+ycYPhmRPIN5ioeZioV5ikeSJAQFBRl+f9IOr7KkrkFRZAwY0MvobpCHME/xMFOxME/xSJKE4OBgwwsylvhezuFQsWPHQTgcXPEjAuYpHmYqFuYpHk3TUFxcbPgqSxZkXk7XdRQXl/GyIoJgnuJhpmJhnmKqq6szugssyIiIiIiMxoKMiIiIyGAsyLycosgYNqwfFIVRioB5ioeZioV5ikeSJISEhBg+qZ+rLL2cLMtISIgxuhvkIcxTPMxULMxTPJIkISAgwPCCjCW+l3M4HNi8eRccDofRXSEPYJ7iYaZiYZ7i0TQNBQUFXGVJ7tF1oKrKCi74EQPzFA8zFQvzFFNXKLBZkBEREREZjAUZERERkcFYkHk5RZGRlDSUK34EwTzFw0zFwjzFI0kSwsPDDZ/Uz1WWXk6WZURGhhrdDfIQ5ikeZioW5ikeSZLg5+dneEHGEt/L2e0OrF27DXa78RMSyX3MUzzMVCzMUzyapiEvL4+rLMl9vMmtWJineJipWJineLrCvUlZkBEREREZjAUZERERkcFYkHk5k0nBxImjYTIpRneFPIB5ioeZioV5ikeSJPTo0YOT+sl9/v6+RneBPIh5ioeZioV5ikdRjC+wWZB5OYdDxbp12znJVBDMUzzMVCzMUzy6riM/P9/wif0syIiIiIgMxoKMiIiIyGAsyIiIiIgMxoLMy5lMCqZOHc8VP4JgnuJhpmJhnuKRJAkxMTFcZUnuq62tM7oL5EHMUzzMVCzMUzyqavwiDRZkXs7hUJGevpsrfgTBPMXDTMXCPMWj6zoKCwu5ypKIiIjoSseCjIiIiMhgLMgEwMmlYmGe4mGmYmGe4jF6Qj8AmIzuALnHbDZh2rTrje4GeQjzFA8zFQvzFI8sy4iNjYUsG3uMikfIvJymaSgqKoWmaUZ3hTyAeYqHmYqFeYpH13XYbDZO6if3qKqGjIxMqCq/HETAPMXDTMXCPMWj6zpKSkpYkBERERFd6ViQERERERmMBZmXkyQgKMiCLrBAhDyAeYqHmYqFeYrJZDJ+jaPxPSC3mEwmJCePMbob5CHMUzzMVCzMUzyyLCMqKoqrLMk9mqYhOzufK34EwTzFw0zFwjzFo+s6ampqOKmf3KOqGg4cOMEVP4JgnuJhpmJhnuLRdR1lZWUsyIiIiIiudCzIiIiIiAzGgszLSZKEiIiQLnEfLnIf8xQPMxUL8xSTr6+v0V3gKktvZzIpGDfuGqO7QR7CPMXDTMXCPMUjyzIiIiIMX2UpREG2ZcsWrF69Gnl5eQgMDMR1112HOXPmwGKxdHif58+fx+rVq7F7926UlJQgMDAQQ4YMwZw5cxATE+PB3rtHVTVkZWWjb98EKAoPeHo75ikeZioW5ikeXddRUVGBsLAQQ/vh9e+mtWvX4qWXXkJeXh4GDhwIk8mEzz//HH/84x/hcDg6tM+zZ8/if//3f/H5559DURQkJiZC13Vs27YNv//971FeXu7ZQbhB0zQcP57NJdiCYJ7iYaZiYZ7i0XUdVVVVhq+y9OojZBUVFVi6dCksFgsWL16MuLg4OBwOvPDCC9izZw/S0tIwderUdu83KioKiYmJmDp1KoYNGwYAqKurw3PPPYdDhw5h06ZN+NnPfubh0RAREdGVyquPkG3fvh02mw033XQT4uLiADRcRXnu3LkAgE2bNnVovyaTCQsWLHAWY0DDhL+f/vSnAIC8vDz3Ok5ERER0Aa8+Qnb06FEAwIgRI1zaExISEBoaipMnT6Kurs5jqyfq6uoAAMHBwZfczm63w263O/9vtVp/aHfAbm84jSrLEhRFgaqq0LQfD5PKsgxFkeFwqC6HTxVFhizLcDgcuPioanx8FFRVdWkzmRQAgMPRtnaz2QRN01wudihJDcVp03YJJpMCVdVcDtt7akyN7Y0/qytpTKqqomfPSEhSw2F0EcbUWrvoY2rMtLG/Iozpx76Lk1Nbx6TrOnr2jHR+54owJhFzas+YAMDf3x+apjn76qkxtec0qFcXZOfOnQMA9OzZE5mZmfjrX/+K22+/HTNnzkRsbCxKS0tRWFiI+Ph4t19L13WsX78eiqIgOTn5ktuuWrUKKSkpTdrT0jLg4+MDoKGIGj58ADIzs5CTU+Dcpn//BAwY0Au7dh1GcXGZs33YsH5ISIjB1q37UFVldbYnJQ3F8OEDsHbtNpc3wsSJo+Hv74t167a79GHq1PGora1DevpuZ5vJpGDatOtRUlKOjIxMZ3tQkAXJyWOQm1uAAwdOONsjIkIwbtw1yMrKxvHj2c52T44pMjIUaWkZV+yYhg7th6oqq1BjEjGn9oypoqJauDGJmFNrYzp9+izOni3C2bNFwoxJxJzaMyZZlqFpGnJz85Cbm+fRMU2YMBJtJelGz2Jzw/z585Gfn4+VK1diyZIl+PLLLxEXF4d///vfWLRoETIyMvC3v/0NAwcOdPu1PvroI3z88ceYMWMG7rvvvktu29wRsnnz5uHDD1+HxeIPwLNHyA4fPomBA3tBURRnW1f7C0TEv6ou1xGyI0dO4Zpr+kFRFCHG1Fq76GNqzDQxsQ98fX2EGNOPfRcnp7aOqb7ejkOHsjB4cG8oiiLEmETMqT1jOnToDIqKShAeHoohQ3p5dEz19fWYPftBpKSktHrlhy55hGzJkiWtrpCcNWuWyxti7Nix2Lp1K66//nqX7Txx8b41a9bg448/xqhRo3DPPfe0ur3ZbIbZbG6m3QSz2fVHrigKLqijnBrDbdru+ny73YGcnAIkJvZpsu/G12y+j03bZVlu9josLbUritzssm93x3SpPra33RvHdPZsEYYO7QdJkoQZU2vtoo+pMdOL21377l1jaku7iGOSJMmZ54X78+YxiZhTe8dUW1sLWZabvLa7Y7rw4ExrumRB9sUXX7Q6iOnTpyMgIAAAUFNTg+HDh2PFihXOx6urqwHArWuRAUBqaiqWLFmCa665Bk8++aTLUSgiIiIiT+iSBdknn3zSpu2io6Nx8uRJ5OXlISwszOWx/Px8SJKEHj16dLgfW7ZswbvvvoshQ4bg6aefds7/IiIiIvIkr77sRePcsH379rm05+Tk4Pz58+jdu3ezKyz37NmDOXPm4LnnnmuyOrHRuXPn8OqrryIuLg4LFizoEve5ao4sy85JieT9mKd4mKlYmKd4JElCUFCQ4fcn9ep31Pjx4+Hr64v169c7rw2mqio++OADAMCkSZOafd6KFStQVVWFPXv24MCBAy1uY7fb8cQTTzhPjXZFiiJjwIBevIWHIJineJipWJineCRJQnBwsOEFWZc8ZdlW3bt3x7333ou3334bjz32GAYOHIj8/HwUFRWhX79+mDJlSqv7aG6Rqd1ux44dO2AymZq9fAUA3H333UhISHB7DO5yOFTs2nUYY8YktjjRkrwH8xQPMxUL8xSPpmkoLi5GVFSkof3w6oIMAG699VYEBQVhzZo1OHLkCAIDAzFt2jTcc889za50BIC77roLr7zyCvr27Yvhw4c3ebyiogL19fUAgG+//bbZfUyfPt1zg3CDrusoLi4z/B5c5BnMUzzMVCzMU0yNF343ktcXZAAwYcIETJgwoc3bjxkzBh999FGLj4eHh+Ozzz7zQM+IiIiIWseT4EREREQGY0Hm5RRFxrBh/TjBVBDMUzzMVCzMUzySJCEkJIST+sk9siwjISHG6G6QhzBP8TBTsTBP8UiShICAAMMLMpb4Xs7hcGDz5l2t3mqKvAPzFA8zFQvzFI+maSgoKHC596URWJB5OV0HqqqsTW44Tt6JeYqHmYqFeYqpKxTYLMiIiIiIDMaCjIiIiMhgLMi8nKLISEoayhU/gmCe4mGmYmGe4pEkCeHh4YZP6ucqSy8nyzIiI0ON7gZ5CPMUDzMVC/MUjyRJ8PPzM7wgY4nv5ex2B9au3Qa73fgJieQ+5ikeZioW5ikeTdOQl5fHVZbkPodDNboL5EHMUzzMVCzMUzxd4d6kLMiIiIiIDMaCjIiIiMhgLMi8nMmkYOLE0TCZFKO7Qh7APMXDTMXCPMUjSRJ69OjBSf3kPn9/X6O7QB7EPMXDTMXCPMWjKMYX2CzIvJzDoWLduu2cZCoI5ikeZioW5ikeXdeRn59v+MR+FmREREREBmNBRkRERGQwFmREREREBmNB5uVMJgVTp47nih9BME/xMFOxME/xSJKEmJgYrrIk99XW1hndBfIg5ikeZioW5ikeVTV+kQYLMi/ncKhIT9/NFT+CYJ7iYaZiYZ7i0XUdhYWFXGVJREREdKVjQUZERERkMBZkAuDkUrEwT/EwU7EwT/EYPaEfAExGd4DcYzabMG3a9UZ3gzyEeYqHmYqFeYpHlmXExsZClo09RsUjZF5O0zQUFZVC0zSju0IewDzFw0zFwjzFo+s6bDYbJ/WTe1RVQ0ZGJlSVXw4iYJ7iYaZiYZ7i0XUdJSUlLMiIiIiIrnQsyIiIiIgMxoLMy0kSEBRkQRdYIEIewDzFw0zFwjzFZDIZv8bR+B6QW0wmE5KTxxjdDfIQ5ikeZioW5ikeWZYRFRXFVZbkHk3TkJ2dzxU/gmCe4mGmYmGe4tF1HTU1NZzUT+5RVQ0HDpzgih9BME/xMFOxME/x6LqOsrIyFmREREREVzoWZEREREQGY0Hm5SRJQkRESJe4Dxe5j3mKh5mKhXmKydfX1+gucJWltzOZFIwbd43R3SAPYZ7iYaZiYZ7ikWUZERERXGVJ7lFVDceOneEEU0EwT/EwU7EwT/Houo6KigpO6if3aJqG48ezuQRbEMxTPMxULMxTPLquo6qqigUZERER0ZWOBRkRERGRwViQeTlZlhAfHwVZ5oofETBP8TBTsTBPMVksFqO7wFWW3k5RFAwfPsDobpCHME/xMFOxME/xyLKM0NBQrrIk96iqiv37j0FVVaO7Qh7APMXDTMXCPMWjaRpKS0sNX6jBgszLaZqOnJwCaJqxq0PIM5ineJipWJinmKxWq9FdYEFGREREZDQWZEREREQGE2JS/5YtW7B69Wrk5eUhMDAQ1113HebMmePRVRMnTpzAggULUF9fj88++8xj+3WXLMvo3z/B8MmI5BnMUzzMVCzMUzySJCEoKMjw+5N6/Ttq7dq1eOmll5CXl4eBAwfCZDLh888/xx//+Ec4HA6PvEZRURH+8pe/oL6+3iP78yRFkTFgQC8oitdHSWCeImKmYmGe4pEkCcHBwSzI3FFRUYGlS5fCYrHg5Zdfxp///Ge88cYbGDVqFI4dO4a0tDS3X8Nut+OFF16ApmmIjY31QK89y+FQsWPHQTgcXPEjAuYpHmYqFuYpHk3TUFxczFWW7ti+fTtsNhtuuukmxMXFAQBMJhPmzp0LANi0aZPbr7F8+XJkZ2fjySefREhIiNv78zRd11FcXGb4PbjIM5ineJipWJinmOrq6ozugnfPITt69CgAYMSIES7tCQkJCA0NxcmTJ1FXVwdfX98O7f+7777DmjVrMGvWLCQmJrb5eXa7HXa73fn/xuW0drsDdnvDaVRZlqAoClRVdVk+LcsyFEWGw6G6fOAVRYYsy3A4HLjwe6DxuY37bWQyKQDQ5K+4ltrNZhM0TYOq/vgXgiQ1FLhN2yWYTApUVXP5i8JTY2psvxLH1Pi4ruvQdV2IMbXWLvqYGvflcKgtjNX7xvRj38XJqT1jAuDx73KjxyRiTm0dUyNN+/Hz6qkxtadw9+qC7Ny5cwCAnj17IjMzE3/9619x++23Y+bMmYiNjUVpaSkKCwsRHx/f7n2rqorXX38dffr0wZ133tmu565atQopKSlN2tPSMuDj4wMAiI+PwvDhA5CZmYWcnALnNv37J2DAgF7YteswiovLnO3DhvVDQkIMtm7dh6qqH6+XMnr0YABAevpulzfCxImj4e/vi3Xrtrv0YerU8aitrUN6+m5nm8mkYNq061FSUo6MjExne1CQBcnJY5CbW4ADB0442yMiQjBu3DXIysrG8ePZznZPjSkpaSgiI0ORlpZxxY7J4VBhs9ULNSYRc2rPmHbsOIhJk8Qak4g5tTamU6dyAQAbNuwUZkwi5tSeMTXKzc1Dbm6eR8c0YcJItJWke/Fx1/nz5yM/Px8rV67EkiVL8OWXXyIuLg7//ve/sWjRImRkZOBvf/sbBg4c2O59p6amYsmSJfj73/+OPn36AAAWLFiAw4cPt7rKsrkjZPPmzcOHH74Oi8UfgOf+ApEkCXl5hYiKCnep9LvaXyAi/lV1OcakaRry8gqRkBDzw368f0yttYs+psZMe/aMgo+PWYgx/dh3cXJq65jsdgdyc88hNrYHZFkWYkwi5tSeMR0+/D3KyyvRrVsgEhOv8uiY6uvrMXv2g0hJSWn1yg9d8gjZkiVLWl0hOWvWLJc3xNixY7F161Zcf/31Ltt1ZNVEdXU1UlJSMGHCBGcx1h5msxlms7mZdhPMZtcfuaIoUJSm+2gMt2l708gSEmIu0ZfmI26uveHLpem0wpbaFUVudqWRJ8bUUh/b2+6NY7r66rhLbu+NY2qtXfQxXZipKGNqS7uIYzKbTS55NvLmMYmYU3vGJEkSAgMDoShKk9d2d0wXHpxpTZcsyL744otWBzF9+nQEBAQAAGpqajB8+HCsWLHC+Xh1dTWAjt3B/dNPP0VtbS1mzpzZ7ud2NofDga1b9+GGG0a0+MYh78E8xcNMxcI8xaNpGgoKChAbG21oP7rku+mTTz5p03bR0dE4efIk8vLyEBYW5vJYfn4+JElCjx492v3627dvh6ZpmD9/frOPT58+HcnJyXjsscfavW9P03WgqsoK7z3xTBdinuJhpmJhnmLy1HVL3dElC7K2GjhwILZt24Z9+/Zh6NChzvacnBycP38effr0aXaF5Z49e/Dyyy+jf//+WLhwIZSLjl8mJiY6L6NxoaNHj6KqqgrXXnstevfu7fkBERER0RXJqwuy8ePHY+nSpVi/fj0mT56M2NhYqKqKDz74AAAwadKkZp+3YsUKVFVVYc+ePThw4ABGjnRdBfHwww83+7zGSf0LFy707ECIiIjoiubVBVn37t1x77334u2338Zjjz2GgQMHIj8/H0VFRejXrx+mTJnS6j68eJEpgIaJi0lJQ3kbD0EwT/EwU7EwT/FIkoTw8HDeOsldt956K5544gnExMTgyJEjsNvtmDZtGp577rlmVzoCwF133YWgoCCMGDECw4cP7+Qee5Ysy4iMDOWNbgXBPMXDTMXCPMUjSRL8/PwML8i8+ghZowkTJmDChAlt3n7MmDH46KOP2v06L7zwQrufc7nZ7Q6kpWVgypSkFpfhkvdgnuJhpmJhnuJpuFZgHuLjexraD5b4AuBNbsXCPMXDTMXCPMXTFaYvsSAjIiIiMhgLMiIiIiKDsSDzciaTgokTR7d4KwvyLsxTPMxULMxTPI0XkTd6Uj8LMgH4+ze9+C15L+YpHmYqFuYpnosvEG8EFmRezuFQsW7ddk4yFQTzFA8zFQvzFI+u68jPzzd8Yj8LMiIiIiKDsSAjIiIiMhgLMiIiIiKDsSDzciaTgqlTx3PFjyCYp3iYqViYp3gkSUJMTAxXWZL7amvrjO4CeRDzFA8zFQvzFI+qGr9IgwWZl3M4VKSn7+aKH0EwT/EwU7EwT/Houo7CwkKusiQiIiK60rEgIyIiIjIYCzIBcHKpWJineJipWJineIye0A8AJqM7QO4xm02YNu16o7tBHsI8xcNMxcI8xSPLMmJjYyHLxh6j4hEyL6dpGoqKSqFpmtFdIQ9gnuJhpmJhnmJQDx+BmpEBoGFSv81mc07qVzMyoB4+0ul9YkHm5VRVQ0ZGJlSVXw4iYJ7iYaZiYZ7eTz18BOrq1VDTNkDdkQFd11FSUgJd16HuyGhoX72604syFmRERER0RWgsxtB4NGzDBoSe/A4AEHryO6gbNjRsqOudXpRxDhkRERFdGaoqncVYo6gj+zDR7AM/e73rtrresH0n4REyLydJQFCQBV1ggQh5APMUDzMVC/P0bkpSEpTJk5u0NynGACiTJ0NJSuqMbgHgETKvZzKZkJw8xuhukIcwT/EwU7EwT++njGsospynJ5vbZvJk53adhUfIvJymacjOzueKH0EwT/EwU7EwTzEo45KAoKDmHwwK6vRiDGBB5vVUVcOBAye44kcQzFM8zFQszFMM6o4MoKqq+Qerqhoe72QsyIiIiOiKoe7IuOTpSqDhdGZnF2UsyIiIiOiKoGY0X4zZzD5Nt92wwXnx2M7ASf1eTpIkRESEdIn7cJH7mKd4mKlYmKeXC+rWsFT2gktfFAwegaOBYRhUfR5RR/b9uK0kNWzfSViQeTmTScG4cdcY3Q3yEOYpHmYqFubp3ZTEwQDgvDisMnkyygOjEGFXUR4ThdiYsIYjaJIEZcYM5/adgQWZl1NVDVlZ2ejbNwGKwjPQ3o55ioeZioV5ej9nkVVVCSUpCfrB06ioqEBYWEjD6koJQFC3Ti3GAM4h83qapuH48WwuwRYE8xQPMxUL8xSDkjjYedFXXddRVVXlvLm4kpTU6cUYwIKMiIiIyHAsyIiIiIgMxoLMy8myhPj4KMgyV/yIgHmKh5mKhXmKyWKxGN0FTur3doqiYPjwAUZ3gzyEeYqHmYqFeYpHlmWEhoZClo09RsUjZF5OVVXs338Mqqoa3RXyAOYpHmYqFuYpHk3TUFpaavhCDRZkXk7TdOTkFEDT9NY3pi6PeYqHmYqFeYrJarUa3QUWZERERERG4xyyTtB4bROrtdbj+7bbHaivr4fVWguzmXF6O+YpHmYqFuYpHpvNhvr6ethsNo//nm7cn663fkRV0tuyFbmlpKQE8+bNM7obREREZID33nsP4eHhl9yGBVknaJww6O/v7/Eb0lqtVsybNw/vvfdel1i2S+5hnuJhpmJhnuK5nJnquo7a2to2reLk8dZOIMtyq5WxuywWC78cBMI8xcNMxcI8xXO5Mg0ICGjTdpzUT0RERGQwFmREREREBmNB5uXMZjNmzZoFs9lsdFfIA5ineJipWJineLpKppzUT0RERGQwHiEjIiIiMhgLMiIiIiKDsSAjIiIiMhgLMiIiIiKDsSAjIiIiMhiv1N+FZWVlYfXq1Th69CiqqqoQHh6Oa6+9FrNnz3b7asJZWVn44IMPcOLECciyjCFDhuC+++5DTEyMh3pPl/Lpp5/ivffew8MPP4wpU6a4vb/HHnsMp0+fbtIeFhaGJUuWuL1/ap2nM+Vn1BhbtmzB6tWrkZeXh8DAQFx33XWYM2eO29+5/IxefrquY+3atVi7di2KiooQEhKC5ORkzJw5EyaTe+XO/v37sWLFCpw+fRp+fn4YNWoU5s6di5CQEA/1ngVZl7Vlyxa8/PLLAIDevXujZ8+eOH78OFJTU3H69Gk8//zzHd53VlYWnnrqKdTX12PAgAGor6/Hzp07cfToUbz00kvo0aOHp4ZBF6mtrcWSJUvw1VdfeXS/NpsNAQEBSExMdGnv1q2bR1+HmrocmfIzaoy1a9fizTffhI+PDwYOHIhz587h888/R1ZWFl544QW3fqnzM3r5vf/++1izZg0CAgIwePBgfP/990hJSUFOTg6efPLJDu93165deOGFFyBJEgYNGoSysjJs3rwZ3333HV566SUEBgZ6pP8syLqo/v37Y8SIEbj//vudfxEXFhbit7/9LQ4dOoQTJ06gX79+Hdr3G2+8gfr6ejzxxBOYMGECAGDlypVYtmwZli5dit/97neeGgb9wG6344svvsAnn3yCyspKhIWF4fz58x7bv9VqRa9evbBw4UKP7ZMu7XJmys9o56uoqMDSpUthsViwePFixMXFweFw4IUXXsCePXuQlpaGqVOndnj//IxeXtnZ2UhNTUVERAQWL16M0NBQWK1WLFiwADt27MDevXsxcuTIdu/XbrfjjTfeAAD8+c9/RmJiInRdx+uvv47169fjv//9L+677z6PjIFzyLqoqKgoPPPMMy6nJ3r06IHrrrsOAJCXl9eh/ebk5CArKwt9+vRxftEDwM9+9jMEBwdj586dqK6udqvv1JQkSUhNTUVISAj+8Ic/YPLkyR7df01NDW903MkuV6b8jBpj+/btsNlsuOmmmxAXFwcAMJlMmDt3LgBg06ZNbu2fn9HLa/PmzdA0DTNmzEBoaCiAhpuFz5kzBwCwcePGDu33wIEDKCkpwdixY51HNyVJwty5c6EoivN1PYEFmZepq6sD0PHD3EeOHAEAjBgxwqVdURQMHToUDocDJ06ccK+T1ITJZMLixYvx6quvYvTo0R7dt81mg91uR/fu3T26X7q0y5UpP6PGOHr0KICmP/eEhASEhobi5MmTzu/f9uJn9PJr6XOTmJgIk8nkzLe9WnpfBAYGok+fPigvL0d+fn6H9n0xFmRepKKiAhkZGejRoweGDh3aoX2cO3cOANCzZ0+UlZXhV7/6FZ577jln24XbkGdFRERclv2WlpYCAE6dOoUPP/wQaWlpKCgouCyvRa4uR6b8jBrjwp97ZmYmfvGLX2DlypUAgNjYWOi6jsLCwg7tm5/Ry+/cuXMwmUyIjo5Geno6Zs2ahfT0dPj7+yM0NBRlZWWw2Wwd2i/Q8L7IycnB3Llz8frrrzvbLtzGXZxD5iUcDgf+/ve/o7a2Fr/97W87fBNUq9UKAAgICMCRI0dQUFCAgoICVFRUICgoCEDDoXXyHjU1Nc5f3v/973+h6zokScKECRPw8MMPG37DXGoffkaNceHP/ZtvvkF1dTW2bNmCmTNnOidtd/Tnzs/o5VdbW+s8Jbx161ZYrVZs27YNEydORFBQEIqKilBTUwM/P7927bfxfREYGIjdu3ejrKwM6enpeOihh5zvi8Zt3MWCrJMtWbIEDofjktvMmjXL+cULNBRjL774Ig4ePIi5c+di1KhRHunLoEGDEBkZiZiYGJdToJIkeWT/V4KO5Olpffv2df7FZrPZkJmZiY8++gjp6ekwm814+OGHL9tri6grZNqIn1H3tTVPXded/x87diy2bt2K66+/3mW7jv7c+RntXOPHj8fRo0cxbtw4l/aO5Hfh+2LEiBH49NNPMWbMGLf72BwWZJ3siy++gN1uv+Q206dPd37Zq6qKxYsXY+fOnbjzzjvxs5/9zK3Xb/wLoqamBqGhoXjnnXecjzVOFObE07Zrb56Xm5+fH8aMGYPExEQ8+OCD2LhxI+69914urW8HozPlZ9Sz2ppnQEAAgIaf+/Dhw7FixQrn4578ufMzenn4+/s7j1RNmjQJkyZNcj7mTn6N74vq6moMGjQIH374oUf22xwWZJ3sk08+adf2b7zxBjIyMjBjxgzcc889br9+dHQ0ADQ7CbFx5WbjNtS69ubZWSwWCwYPHowdO3bg7NmzGDRokNFd8hpGZ8rPqGe1Nc/o6GicPHkSeXl5CAsLc3ksPz8fkiR59Ppv/Ix6VnR0NE6cOIGCggJERUU52202G86fP4+QkJB2n65s3C/Q8B64OCNPfx45qb8L27JlC9avX4+f/OQnbb7OyZ49ezBnzhw899xzUFW1yeONb6h9+/a5tGuahszMTCiK0uHrm5HntZbnpVRVVQEAfHx8LkfXqIP4Ge2aBg4cCKDpzz0nJwfnz59H79694evr2+R5/Ix2DS19bg4fPgyHw+HM92Lr16/H7Nmz8dprr7Vrv1arFVlZWQgODvbY3TNYkHVRqqpi2bJlCA8Px0MPPdTm561YsQJVVVXYs2cPDhw40OTxhIQE9OnTBydOnMC2bduc7WvWrEFZWRmuvfZaj111mNzXWp4AcPbs2SZtmzdvxqFDhxAUFISrrrrq8naS2oWf0a5p/Pjx8PX1xfr1651HPlRVxQcffAAALqfALsTPaNeQnJwMSZKwevVqlJWVAWg4OrZ8+XIALee3bNky1NTUIC0trdmchg0bhrCwMGRkZLhcOmPp0qVQVRXJycmQZc+UUjxl2UUdO3YMhYWFCAsLwz/+8Y9mt2ntis8XTka80Pz587FgwQL8/e9/d86vOHnyJIKCgjx2xWFqaufOndi5cycA4MyZMwAaLlZ49OhRdOvWDfPmzbvk85vLU1VVPPHEEwgMDETPnj1hMplw7tw55OXlQZZlPPDAA27fw41adjkyBfgZNUL37t1x77334u2338Zjjz2GgQMHIj8/H0VFRejXr1+b7k/Kz6hxrrrqKkyfPh2pqan49a9/jb59++L7779HWVkZxo4d26ZrBTZ3gVez2YwHH3wQixYtwsKFCzFo0CCUl5cjNzcXUVFRuPPOOz02Bklv6RuBDJWenu68l2VLPvvssyZtu3btwiuvvIK+ffviD3/4AxRFafa5jTcuPn78uMuNi2NjYz3Sf2pq+fLlSElJafaxyMhIl8nbjVrLs76+HitXrsT+/fuRl5eHuro6dOvWDQMGDMDtt9/e4mF68ozLkWkjfkaN8fXXX2PNmjU4e/YsAgMDMW7cONxzzz0tTtzmZ7Tr0HUdn3/+Ob788ksUFha63Fy8pUuLfPXVV1i6dCnGjh2LRx99tMV97927FykpKThz5gx8fX0xatQo3HfffR69uTgLMiIiIiKDcQ4ZERERkcFYkBEREREZjAUZERERkcFYkBEREREZjAUZERERkcFYkBEREREZjAUZERERkcFYkBEREREZjAUZERERkcFYkBEREREZjAUZERERkcF4i3kiog566623sHXrVlRXV0PXdVgsFvTs2RMTJkzAzTff3OKNw4mILsaCjIiog77//ntUVlZi6NCh8Pf3R2VlJbKysnD8+HEcPHgQCxYsMLqLROQlWJAREbnpoYceQkxMDADg/PnzeOqpp7Bz507s378fw4cPN7h3ROQNWJAREXlQWFgYZs6ciX/96184ePCgS0G2bds2fP755zh9+jRMJhP69++P2bNnY8CAAQb2mIi6AhZkREQe1r17dwCA1Wp1tr377rtITU2Fr68v+vTpA5vNhv379+Pw4cP4y1/+goEDBxrUWyLqCliQERF52KlTpwAA0dHRAIB9+/YhNTUVffr0wcKFCxEWFgag4YjZ4sWLsWTJErz44ouG9ZeIjMfLXhAReYCqqjh//jzWrl2Ljz/+GP7+/pg4cSIAYN26dQCAJ554wlmMAcD111+Pfv364dixY6iurjak30TUNfAIGRGRm+bPn+/y/6CgIPzud79znro8fvw4TCYTli5d2uS5JSUlAIDCwkIEBgZe9r4SUdfEgoyIyE3XXHMN/Pz8kJ+fj9zcXNx///245pprnI9XV1dDVVV8++23Le6jtra2M7pKRF0UCzIiIjf9v//3/xATE4OysjI88sgjWLZsGcaNGwdfX18AQEBAAGw2G1auXAlZ5kwRImqK3wxERB4SEhKC++67D8XFxVi1apWzvW/fvqivr8fx48cN7B0RdWUsyIiIPCg5ORlxcXH49NNPcf78eQDAT3/6UwDAv/71L5w5c8Zle13XUVdX1+n9JKKuhQUZEZEHSZKEn//856ivr8fKlSsBAGPGjMFtt92GvLw8PP7443j44Yfx3HPPYeHChbj33nuxZcsWg3tNREZjQUZE5GE33HADoqKisGHDBhQXFwMAfvnLX+Lpp5/GsGHDUFZWhgMHDuDcuXOIj49Hjx49DO4xERlN0nVdN7oTRERERFcyHiEjIiIiMhgLMiIiIiKDsSAjIiIiMhgLMiIiIiKDsSAjIiIiMhgLMiIiIiKDsSAjIiIiMhgLMiIiIiKDsSAjIiIiMhgLMiIiIiKDsSAjIiIiMhgLMiIiIiKD/X93G3zffHtURQAAAABJRU5ErkJggg==", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = (s + 2) / (s^2 + 1/4)\n", - "viz_poles_and_zeros(g)\n", - "tight_layout()\n", - "savefig(\"../docs/src/example_poles_and_zeros.png\", format=\"png\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Nyquist diagram" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = 1 / (s^2 + s + 1) # https://en.wikipedia.org/wiki/Nyquist_stability_criterion\n", - "nyquist_diagram(g)\n", - "tight_layout()\n", - "savefig(\"../docs/src/example_nyquist.png\", format=\"png\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## root locus diagram" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g_ol = 4 / (s + 3) / (s + 2) / (s + 1)\n", - "\n", - "root_locus(g_ol)\n", - "tight_layout()\n", - "savefig(\"../docs/src/example_root_locus.png\", format=\"png\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Bode plot" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "g = 3 / (s+1)\n", - "\n", - "bode_plot(g)\n", - "tight_layout()\n", - "savefig(\"../docs/src/example_bode.png\", format=\"png\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "gain and phase margins, critical frequency, gain crossover frequency" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "-- gain/phase margin info--\n", - "\tcritical frequency ω_c [rad/time]: 60578352361124176.00000\n", - "\tgain crossover frequency ω_g [rad/time]: 2.82843\n", - "\tgain margin: 20192784120374724.00000\n", - "\tphase margin: 1.91063\n" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "margins = gain_phase_margins(g)" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Figure(PyObject
)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# PI controller transfer function\n", - "pic = PIController(1.0, 3.0)\n", - "gc = TransferFunction(pic)\n", - "\n", - "# process, sensor dynamics\n", - "gu = 2 / (4 * s + 1) * exp(-0.5 * s)\n", - "gm = 1 / (s + 1) * exp(-0.75 * s)\n", - "gd = 6 / (6 * s + 1)\n", - "\n", - "# open-loop transfer function\n", - "g_ol = gc * gu * gm\n", - "\n", - "# closed-loop transfer function for regulator response\n", - "gr = ClosedLoopTransferFunction(gd, g_ol)\n", - "\n", - "# closed-loop transfer function for servo response\n", - "gs = ClosedLoopTransferFunction(g_ol, g_ol)\n", - "\n", - "# response to unit set point change\n", - "Y = gs / s\n", - "data = simulate(Y, 50.0)\n", - "\n", - "# # response to unit step in disturbance d\n", - "# Y = gr / s\n", - "# data = simulate(Y, 45.0)\n", - "\n", - "viz_response(data)\n", - "xlim([-1, 50])\n", - "title(\"closed-loop servo response\")\n", - "tight_layout()\n", - "savefig(\"../docs/src/closed_loop_servo_time_delay.png\", format=\"png\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "ename": "LoadError", - "evalue": "we cannot add two transfer functions with two different time delays.\n\nif you are trying to construct a closed-loop transfer function with a time delay,\ninstead use `ClosedLoopTransferFunction`.", - "output_type": "error", - "traceback": [ - "we cannot add two transfer functions with two different time delays.\n\nif you are trying to construct a closed-loop transfer function with a time delay,\ninstead use `ClosedLoopTransferFunction`.", - "", - "Stacktrace:", - " [1] error(s::String)", - " @ Base ./error.jl:33", - " [2] +(tf1::TransferFunction, tf2::TransferFunction)", - " @ Controlz ~/.julia/dev/Controlz/src/tf.jl:84", - " [3] +(tf::TransferFunction, x::Int64)", - " @ Controlz ~/.julia/dev/Controlz/src/tf.jl:95", - " [4] -(x::Int64, tf::TransferFunction)", - " @ Controlz ~/.julia/dev/Controlz/src/tf.jl:98", - " [5] top-level scope", - " @ In[16]:4", - " [6] eval", - " @ ./boot.jl:360 [inlined]", - " [7] include_string(mapexpr::typeof(REPL.softscope), mod::Module, code::String, filename::String)", - " @ Base ./loading.jl:1094" - ] - } - ], - "source": [ - "# TODO rectangular pulse\n", - "M = 3.2\n", - "θ = 2.03\n", - "U = M / s * (1 - exp(-θ * s))\n", - "t, u = simulate(U, 12.0)\n", - "rec_pulse(t::Float64) = ((t < 0.0) || (t > θ)) ? 0.0 : M\n", - "@test isapprox(u, _rec_pulse.(t), rtol=0.001)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "@webio": { - "lastCommId": null, - "lastKernelId": null - }, - "kernelspec": { - "display_name": "Julia 1.6.0", - "language": "julia", - "name": "julia-1.6" - }, - "language_info": { - "file_extension": ".jl", - "mimetype": "application/julia", - "name": "julia", - "version": "1.6.0" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/examples.jl b/examples/examples.jl index 08b9c64..6a88012 100644 --- a/examples/examples.jl +++ b/examples/examples.jl @@ -117,7 +117,7 @@ md"## Bode plot" # ╔═╡ d3996cd9-6890-4445-b2fe-c38ecc76ce77 function draw_bode_plot() - g = 3 / (s+1) + g = 3 / (s + 1) fig = bode_plot(g, savename="../docs/src/example_bode.png") return fig @@ -126,6 +126,107 @@ end # ╔═╡ 26d9f8ea-5d85-4cdd-b500-0e2d63f60e81 draw_bode_plot() +# ╔═╡ cb5572cd-4c1d-4291-bfa3-4b83f9c9c784 +md"## servo response of a control system" + +# ╔═╡ 08722d92-f2cd-4ec1-bfca-e21ebdb47ad7 +function sim_servo_response() + Kc = 1.0 + τI = 1.0 + pic = PIController(1.0, 1.0) + gc = TransferFunction(pic) # controller transfer functio + + gp = 3 / (4 * s + 1) # process transfer function + + g_ol = gc * gp # open-loop transfer function + + g_servo = g_ol / (1 + g_ol) # transfer function for servo response + + Y_sp = 1 / s # unit step set point change + + Y = g_servo * Y_sp # resulting output + + E = Y_sp - Y # error signal + + U = gc * E # resulting controller output + + # break output into P-action, I-action + U_Paction = Kc * E + U_Iaction = Kc * τI / s * E + + # simulate for y, u, ysp in the time domain + final_time = 12.0 + y_data = simulate(Y, final_time) + u_data = simulate(U, final_time) + ysp_data = simulate(Y_sp, final_time) + u_Paction_data = simulate(U_Paction, final_time) + u_Iaction_data = simulate(U_Iaction, final_time) + + fig = Figure(resolution=(800, 600)) + axs = [Axis(fig[1, 1], ylabel="system output y(t)"), + Axis(fig[2, 1], xlabel="time, t", ylabel="controller output u(t)") + ] + + lines!(axs[1], y_data[:, :t], y_data[:, :output], label="response y(t)") + lines!(axs[1], ysp_data[:, :t], ysp_data[:, :output], linestyle=:dash, label="set point yₛₚ(t)") + axislegend(axs[1], position=:rb) + + lines!(axs[2], u_data[:, :t], u_data[:, :output], label="total") + lines!(axs[2], u_Paction_data[:, :t], u_Paction_data[:, :output], linestyle=:dash, label="P-action", linewidth=2) + lines!(axs[2], u_Iaction_data[:, :t], u_Iaction_data[:, :output], linestyle=:dot, label="I-action", linewidth=2) + axislegend(axs[2]) + + Controlz.draw_axes.(axs) + save("../docs/src/simple_servo_response.png", fig) + return fig +end + +# ╔═╡ b87d02fc-2c8c-4536-b244-f7573e11ac4e +sim_servo_response() + +# ╔═╡ 3f41f47d-68ef-4845-96ff-03f62f0a4652 +cool_theme[:palette] + +# ╔═╡ 80e11f0b-f06c-4abb-b1b7-45a47032b8b8 +md"## closed loop servo response with time delay" + +# ╔═╡ d9b1ad99-adcb-49e2-be52-2f194400dec9 +function sim_servo_response_w_delay() + + # PI controller transfer function + pic = PIController(1.0, 3.0) + gc = TransferFunction(pic) + + # process, sensor dynamics + gu = 2 / (4 * s + 1) * exp(-0.5 * s) + gm = 1 / (s + 1) * exp(-0.75 * s) + gd = 6 / (6 * s + 1) + + # open-loop transfer function + g_ol = gc * gu * gm + + # closed-loop transfer function for regulator response + gr = ClosedLoopTransferFunction(gd, g_ol) + + # closed-loop transfer function for servo response + gs = ClosedLoopTransferFunction(gu * gc, g_ol) + + # response to unit set point change + Y = gs / s + data = simulate(Y, 50.0) + + # # response to unit step in disturbance d + # Y = gr / s + # data = simulate(Y, 45.0) + + fig = viz_response(data, title="closed-loop servo response", + savename="../docs/src/closed_loop_servo_time_delay.png") + return fig +end + +# ╔═╡ 6a68842e-ecb7-45d3-86b1-2744752ad3b0 +sim_servo_response_w_delay() + # ╔═╡ 2de0d044-1bf6-489f-9e54-026100fd7655 md"## draw a `.gif` of a response" @@ -171,6 +272,13 @@ test_make_gif() # ╟─afee73f3-740d-4114-96c5-b50b1e025e6c # ╠═d3996cd9-6890-4445-b2fe-c38ecc76ce77 # ╠═26d9f8ea-5d85-4cdd-b500-0e2d63f60e81 +# ╟─cb5572cd-4c1d-4291-bfa3-4b83f9c9c784 +# ╠═08722d92-f2cd-4ec1-bfca-e21ebdb47ad7 +# ╠═b87d02fc-2c8c-4536-b244-f7573e11ac4e +# ╠═3f41f47d-68ef-4845-96ff-03f62f0a4652 +# ╟─80e11f0b-f06c-4abb-b1b7-45a47032b8b8 +# ╠═d9b1ad99-adcb-49e2-be52-2f194400dec9 +# ╠═6a68842e-ecb7-45d3-86b1-2744752ad3b0 # ╟─2de0d044-1bf6-489f-9e54-026100fd7655 # ╠═b6a45495-e081-4e02-8a0e-cfe1d3df36ba # ╠═8acaad0e-951d-4bc9-add8-19315bb9f4e6 diff --git a/src/tf.jl b/src/tf.jl index ab14b4f..c3f7859 100644 --- a/src/tf.jl +++ b/src/tf.jl @@ -4,7 +4,7 @@ import Base.*, Base./, Base.+, Base.-, Base.==, Base.^, Base.exp, Base.isapprox tf = TransferFunction([1, 2], [3, 5, 8]) tf = TransferFunction([1, 2], [3, 5, 8], 3.0) -Construct a transfer function representing a linear, time-invariant system. +construct a transfer function representing a linear, time-invariant system. # Example to construct the transfer function @@ -15,13 +15,17 @@ G(s) = \frac{4e^{-2.2s}}{2s+1} in Julia: -```julia +```jldoctest tf = TransferFunction([4], [2, 1], 2.2) +# output + 4.0 +----------- e^(-2.2*s) +2.0*s + 1.0 ``` # Attributes -* `numerator::Polynomial`: the polynomial in the numerator of the transfer function -* `denominator::Polynomial`: the polynomial in the denominator of the transfer function +* `numerator::Polynomial{Float64, :s}`: the polynomial in the numerator of the transfer function +* `denominator::Polynomial{Float64, :s}`: the polynomial in the denominator of the transfer function * `time_delay::Float64`: the associated time delay """ struct TransferFunction diff --git a/src/viz.jl b/src/viz.jl index ff5e869..ed6b143 100644 --- a/src/viz.jl +++ b/src/viz.jl @@ -34,8 +34,9 @@ xlims!(ax, 0, 15) # Example ``` g = 4 / (4 * s ^ 2 + 0.8 * s + 1) -u = 1 / s -data = simulate(g * u, (0.0, 50.0)) +U = 1 / s +Y = g * U +data = simulate(Y, 50.0) fig = viz_response(data) ``` """ @@ -186,8 +187,9 @@ returns the two axes of the plot for further tuning via `matplotlib` commands. adjust the range of frequencies that the Bode plot presents with `log10_ω_min` and `log10_ω_max`. -returns a `CairoMakie.jl` `Figure` object for further modification. increase the resolution of the Bode plot with `nb_pts`. + +returns a `CairoMakie.jl` `Figure` object for further modification. """ function bode_plot(g::TransferFunction; log10_ω_min::Float64=-3.0, log10_ω_max::Float64=3.0, nb_pts::Int=300, savename::Union{Nothing, String}=nothing) From 11fe9ff7e5f35c77fbed0743fd152d44f6bdc802 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sun, 2 Jan 2022 13:29:37 -0800 Subject: [PATCH 16/19] add markdown and interactive utils for tests --- Project.toml | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/Project.toml b/Project.toml index 8481eca..73025d0 100644 --- a/Project.toml +++ b/Project.toml @@ -7,6 +7,7 @@ version = "0.3.0" DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa" DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59" +InteractiveUtils Polynomials = "f27b6e38-b328-58d1-80ce-0feddd5e7a45" Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7" Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665" @@ -29,7 +30,9 @@ Colors = "^0.12.8" Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4" Polynomials = "f27b6e38-b328-58d1-80ce-0feddd5e7a45" DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" +Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a" +InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240" Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40" [targets] -test = ["Test", "Documenter", "Polynomials"] +test = ["Test", "Documenter", "Polynomials", "Markdown", "InteractiveUtils"] From df7582e69f22560e15f68694bfd768b37f613cf5 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sun, 2 Jan 2022 13:35:07 -0800 Subject: [PATCH 17/19] bug in project toml --- .github/workflows/ci_testing.yml | 3 +++ Project.toml | 1 - 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/.github/workflows/ci_testing.yml b/.github/workflows/ci_testing.yml index 52b5505..5e3e7a3 100644 --- a/.github/workflows/ci_testing.yml +++ b/.github/workflows/ci_testing.yml @@ -32,6 +32,9 @@ jobs: env: GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} + + - name: set up documenter + run: julia --project -e 'import Pkg; Pkg.add("Documenter")' - name: build and deploy docs run: julia --project --color=yes ./docs/make.jl diff --git a/Project.toml b/Project.toml index 73025d0..716f0dc 100644 --- a/Project.toml +++ b/Project.toml @@ -7,7 +7,6 @@ version = "0.3.0" DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa" DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59" -InteractiveUtils Polynomials = "f27b6e38-b328-58d1-80ce-0feddd5e7a45" Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7" Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665" From 60f54fcc291f79f44369b6fd81eecc0cd751f4a0 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sun, 2 Jan 2022 13:52:21 -0800 Subject: [PATCH 18/19] add pkg to project toml --- Project.toml | 1 + 1 file changed, 1 insertion(+) diff --git a/Project.toml b/Project.toml index 716f0dc..2f7ce4f 100644 --- a/Project.toml +++ b/Project.toml @@ -32,6 +32,7 @@ DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0" Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a" InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240" Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40" +Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f" [targets] test = ["Test", "Documenter", "Polynomials", "Markdown", "InteractiveUtils"] From 5eceb909fac7397228b351c1c050dd5ac05d6bb7 Mon Sep 17 00:00:00 2001 From: SimonEnsemble Date: Sun, 2 Jan 2022 14:28:37 -0800 Subject: [PATCH 19/19] add Pkg to targets project --- Project.toml | 2 +- src/show.jl | 11 +++++++++++ 2 files changed, 12 insertions(+), 1 deletion(-) diff --git a/Project.toml b/Project.toml index 2f7ce4f..8894c89 100644 --- a/Project.toml +++ b/Project.toml @@ -35,4 +35,4 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40" Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f" [targets] -test = ["Test", "Documenter", "Polynomials", "Markdown", "InteractiveUtils"] +test = ["Test", "Documenter", "Polynomials", "Markdown", "InteractiveUtils", "Pkg"] diff --git a/src/show.jl b/src/show.jl index fdf6882..bcda8cb 100644 --- a/src/show.jl +++ b/src/show.jl @@ -51,6 +51,17 @@ function Base.show(io::IO, tf::TransferFunction) return nothing end +function Base.show(io::IO, g::ClosedLoopTransferFunction) + println(io, "closed-loop transfer function. + top + ------- + 1 + g_ol") + println(io, "\n top = ") + show(io, g.top) + println(io, "\n\n g_ol = ") + show(io, g.g_ol) +end + function Base.show(io::IO, pc::PController) println(io, "P controller") println(io, "\tcontroller gain Kc = ", pc.Kc)

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