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Merge pull request #311 from JuliaControl/improve_precompile
added: slightly improve the speed of precompilation
2 parents 1be4655 + f62d591 commit faba5ee

1 file changed

Lines changed: 101 additions & 97 deletions

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‎src/precompile.jl‎

Lines changed: 101 additions & 97 deletions
Original file line numberDiff line numberDiff line change
@@ -1,64 +1,13 @@
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# Putting some things in `@setup_workload` instead of `@compile_workload` can reduce the
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# size of the precompile file and potentially make loading faster.
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@setup_workload begin
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15
sys = [
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tf(1.90, [1800, 1]) tf(1.90, [1800, 1]);
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tf(-0.74,[800, 1]) tf(0.74, [800, 1])
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]
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Ts = 400.0
6-
model = setop!(LinModel(sys, Ts), uop=[10, 10], yop=[50, 30])
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y = model()
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mpc_im = setconstraint!(LinMPC(InternalModel(model)), ymin=[45, -Inf])
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initstate!(mpc_im, model.uop, y)
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preparestate!(mpc_im, [55, 30])
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mpc_im.estim()
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u = mpc_im([55, 30])
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sim!(mpc_im, 2)
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transcription = MultipleShooting()
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mpc_kf = setconstraint!(LinMPC(KalmanFilter(model); transcription), ymin=[45, -Inf])
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initstate!(mpc_kf, model.uop, model())
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preparestate!(mpc_kf, [55, 30])
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mpc_kf.estim()
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u = mpc_kf([55, 30])
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sim!(mpc_kf, 2, [55, 30])
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mpc_skf = setconstraint!(LinMPC(SteadyKalmanFilter(model)), ymin=[45, -Inf])
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initstate!(mpc_skf, model.uop, model())
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preparestate!(mpc_skf, [55, 30])
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mpc_skf.estim()
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u = mpc_skf([55, 30])
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sim!(mpc_skf, 2, [55, 30])
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mpc_mhe = setconstraint!(LinMPC(MovingHorizonEstimator(model, He=2)), ymin=[45, -Inf])
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setconstraint!(mpc_mhe.estim, x̂min=[-50,-50,-50,-50], x̂max=[50,50,50,50])
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initstate!(mpc_mhe, model.uop, model())
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preparestate!(mpc_mhe, [55, 30])
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mpc_mhe.estim()
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u = mpc_mhe([55, 30])
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sim!(mpc_mhe, 2, [55, 30])
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39-
mpc_man = setconstraint!(LinMPC(ManualEstimator(model)), ymin=[45, -Inf])
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initstate!(mpc_man, model.uop, model())
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setstate!(mpc_man, ones(4))
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u = mpc_man([55, 30])
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nmpc_skf = setconstraint!(NonLinMPC(SteadyKalmanFilter(model), Cwt=Inf), ymin=[45, -Inf])
45-
initstate!(nmpc_skf, model.uop, model())
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preparestate!(nmpc_skf, [55, 30])
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nmpc_skf.estim()
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u = nmpc_skf([55, 30])
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sim!(nmpc_skf, 2, [55, 30])
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51-
res = sim!(model, 2)
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res_man = SimResult(model, res.U_data, res.Y_data; X_data=res.X_data)
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exmpc = ExplicitMPC(model)
56-
initstate!(exmpc, model.uop, model())
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preparestate!(exmpc, [55, 30])
58-
exmpc.estim()
59-
u = exmpc([55, 30])
60-
sim!(exmpc, 2, [55, 30])
61-
10+
sys2 = minreal(ss(sys))
6211
function f!(xnext, x, u, _ , p)
6312
A, B, _ = p
6413
mul!(xnext, A , x)
@@ -70,51 +19,106 @@ function h!(y, x, _ , p)
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mul!(y, C, x)
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return nothing
7221
end
73-
74-
sys2 = minreal(ss(sys))
75-
nlmodel = setop!(
76-
NonLinModel(f!, h!, Ts, 2, 2, 2, solver=RungeKutta(4), p=(sys2.A, sys2.B, sys2.C)),
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uop=[10, 10], yop=[50, 30]
78-
)
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y = nlmodel()
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81-
transcription = MultipleShooting(f_threads=true)
82-
nmpc_ukf = setconstraint!(NonLinMPC(
83-
UnscentedKalmanFilter(nlmodel); Hp=10, transcription, Cwt=1e3), ymin=[45, -Inf]
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)
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initstate!(nmpc_ukf, nlmodel.uop, y)
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preparestate!(nmpc_ukf, [55, 30])
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u = nmpc_ukf([55, 30])
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sim!(nmpc_ukf, 2, [55, 30])
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nmpc_ekf = setconstraint!(NonLinMPC(ExtendedKalmanFilter(model), Cwt=Inf), ymin=[45, -Inf])
91-
initstate!(nmpc_ekf, model.uop, model())
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preparestate!(nmpc_ekf, [55, 30])
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u = nmpc_ekf([55, 30])
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sim!(nmpc_ekf, 2, [55, 30])
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96-
transcription = TrapezoidalCollocation()
97-
nmpc_mhe = setconstraint!(NonLinMPC(
98-
MovingHorizonEstimator(nlmodel, He=2); transcription, Hp=10, Cwt=Inf), ymin=[45, -Inf]
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)
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setconstraint!(nmpc_mhe.estim, x̂min=[-50,-50,-50,-50], x̂max=[50,50,50,50])
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initstate!(nmpc_mhe, nlmodel.uop, y)
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preparestate!(nmpc_mhe, [55, 30])
103-
u = nmpc_mhe([55, 30])
104-
sim!(nmpc_mhe, 2, [55, 30])
22+
p = (sys2.A, sys2.B, sys2.C)
10523

10624
function JE( _ , Ŷe, _ , R̂y)
10725
Ŷ = @views Ŷe[3:end]
10826
Ȳ = R̂y - Ŷ
10927
return dot(Ȳ, Ȳ)
11028
end
11129
R̂y = repeat([55; 30], 10)
112-
empc = setconstraint!(
113-
NonLinMPC(nlmodel, Mwt=[0, 0], Hp=10, Cwt=Inf, Ewt=1, JE=JE, p=R̂y), ymin=[45, -Inf]
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)
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preparestate!(empc, [55, 30])
116-
u = empc()
117-
sim!(empc, 2)
118-
119-
linearizemodel = linearize(nlmodel)
120-
setmodel!(mpc_kf, linearizemodel)
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31+
# all calls in this block will be precompiled, regardless of whether
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# they belong to your package or not (on Julia 1.8 and higher)
33+
@compile_workload begin
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35+
model = setop!(LinModel(sys, Ts), uop=[10, 10], yop=[50, 30])
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y = model()
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38+
mpc_im = setconstraint!(LinMPC(InternalModel(model)), ymin=[45, -Inf])
39+
initstate!(mpc_im, model.uop, y)
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preparestate!(mpc_im, [55, 30])
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mpc_im.estim()
42+
u = mpc_im([55, 30])
43+
sim!(mpc_im, 2)
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45+
mpc_skf = setconstraint!(LinMPC(SteadyKalmanFilter(model)), ymin=[45, -Inf])
46+
initstate!(mpc_skf, model.uop, model())
47+
preparestate!(mpc_skf, [55, 30])
48+
mpc_skf.estim()
49+
u = mpc_skf([55, 30])
50+
sim!(mpc_skf, 2, [55, 30])
51+
52+
transcription = MultipleShooting()
53+
mpc_kf = setconstraint!(LinMPC(KalmanFilter(model); transcription), ymin=[45, -Inf])
54+
initstate!(mpc_kf, model.uop, model())
55+
preparestate!(mpc_kf, [55, 30])
56+
mpc_kf.estim()
57+
u = mpc_kf([55, 30])
58+
sim!(mpc_kf, 2, [55, 30])
59+
60+
mhe = MovingHorizonEstimator(model, He=2, direct=true)
61+
mhe = setconstraint!(mhe, x̂min=[-50,-50,-50,-50], x̂max=[50,50,50,50])
62+
initstate!(mhe, model.uop, model())
63+
preparestate!(mhe, [55, 30])
64+
mhe()
65+
66+
mpc_man = setconstraint!(LinMPC(ManualEstimator(model)), ymin=[45, -Inf])
67+
initstate!(mpc_man, model.uop, model())
68+
setstate!(mpc_man, ones(4))
69+
mpc_man([55, 30])
70+
71+
nmpc_skf = setconstraint!(NonLinMPC(SteadyKalmanFilter(model), Cwt=Inf), ymin=[45, -Inf])
72+
initstate!(nmpc_skf, model.uop, model())
73+
preparestate!(nmpc_skf, [55, 30])
74+
nmpc_skf.estim()
75+
nmpc_skf([55, 30])
76+
77+
res = sim!(model, 2)
78+
res_man = SimResult(model, res.U_data, res.Y_data; X_data=res.X_data)
79+
80+
exmpc = ExplicitMPC(model)
81+
initstate!(exmpc, model.uop, model())
82+
preparestate!(exmpc, [55, 30])
83+
exmpc.estim()
84+
exmpc([55, 30])
85+
86+
nlmodel = NonLinModel(f!, h!, Ts, 2, 2, 2; solver=RungeKutta(4), p)
87+
nlmodel = setop!(nlmodel, uop=[10, 10], yop=[50, 30])
88+
y = nlmodel()
89+
90+
transcription = MultipleShooting(f_threads=true)
91+
nmpc_ukf = setconstraint!(NonLinMPC(
92+
UnscentedKalmanFilter(nlmodel); Hp=10, transcription, Cwt=1e3), ymin=[45, -Inf]
93+
)
94+
initstate!(nmpc_ukf, nlmodel.uop, y)
95+
preparestate!(nmpc_ukf, [55, 30])
96+
nmpc_ukf([55, 30])
97+
sim!(nmpc_ukf, 2, [55, 30])
98+
99+
nmpc_ekf = setconstraint!(NonLinMPC(ExtendedKalmanFilter(model), Cwt=Inf), ymin=[45, -Inf])
100+
initstate!(nmpc_ekf, model.uop, model())
101+
preparestate!(nmpc_ekf, [55, 30])
102+
nmpc_ekf([55, 30])
103+
104+
transcription = TrapezoidalCollocation()
105+
nmpc_mhe = setconstraint!(NonLinMPC(
106+
MovingHorizonEstimator(nlmodel, He=2); transcription, Hp=10, Cwt=Inf), ymin=[45, -Inf]
107+
)
108+
setconstraint!(nmpc_mhe.estim, x̂min=[-50,-50,-50,-50], x̂max=[50,50,50,50])
109+
initstate!(nmpc_mhe, nlmodel.uop, y)
110+
preparestate!(nmpc_mhe, [55, 30])
111+
nmpc_mhe([55, 30])
112+
113+
empc = setconstraint!(
114+
NonLinMPC(nlmodel, Mwt=[0, 0], Hp=10, Cwt=Inf, Ewt=1, JE=JE, p=R̂y), ymin=[45, -Inf]
115+
)
116+
preparestate!(empc, [55, 30])
117+
empc()
118+
119+
linearizemodel = linearize(nlmodel)
120+
setmodel!(mpc_kf, linearizemodel)
121+
122+
end
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end # @setup_workload

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