modified: CHANGELOG.md

	modified:   Project.toml
	modified:   src/AutomationLabsSystems.jl
	modified:   src/main/main_systems.jl

CHANGELOG.md

@@ -1,5 +1,10 @@
 # AutomationLabsSystems Changelog
 
+## v0.1.1
+
+* Add system linearization.
+* Add model evaluation from a system.
+* Improve tests.
 ## v0.1.0
 
 * Initial public release.

Project.toml

@@ -1,7 +1,7 @@
 name = "AutomationLabsSystems"
 uuid = "6d3dfdf0-e107-48c6-a6ff-eced1a5a9334"
 authors = ["Pierre BLAUD <pierre.blaud@ikmail.com> and contributors"]
-version = "0.1.0"
+version = "0.1.1"
 
 [deps]
 AutomationLabsIdentification = "48ff5a6f-d08b-4053-9585-6a9e3e078386"
@@ -11,6 +11,7 @@ LazySets = "b4f0291d-fe17-52bc-9479-3d1a343d9043"
 MLJ = "add582a8-e3ab-11e8-2d5e-e98b27df1bc7"
 MLJMultivariateStatsInterface = "1b6a4a23-ba22-4f51-9698-8599985d3728"
 MathematicalSystems = "d14a8603-c872-5ed3-9ece-53e0e82e39da"
+NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
 
 [compat]
 AutomationLabsIdentification = "0.2"
@@ -20,6 +21,7 @@ LazySets = "2"
 MLJ = "0.19"
 MLJMultivariateStatsInterface = "0.5"
 MathematicalSystems = "0.13"
+NNlib = "0.8"
 julia = "1"
 
 [extras]

src/AutomationLabsSystems.jl

@@ -15,10 +15,14 @@ import MLJMultivariateStatsInterface
 import LazySets
 import Flux
 import ForwardDiff
+import NNlib
 
 export proceed_system
 export proceed_system_linearization
 
+#export proceed_system_discretization 
+export proceed_system_model_evaluation
+
 # Load files
 include("types/types.jl")
 include("sub/design_models.jl")

src/main/main_systems.jl

@@ -151,7 +151,7 @@ function proceed_system_linearization( system::MathematicalSystems.ConstrainedBl
     return MathematicalSystems.@system x' = A_sys*x + B_sys*u x∈system.X u∈system.U 
 end
 
-function proceed_system_linearization( system::MathematicalSystems.ConstrainedBlackBoxControlDiscreteSystem,
+function proceed_system_linearization(system::MathematicalSystems.ConstrainedBlackBoxControlDiscreteSystem,
     state::Vector{Float64}, 
     input::Vector{Float64} )
 
@@ -164,5 +164,47 @@ function proceed_system_linearization( system::MathematicalSystems.ConstrainedBl
     return MathematicalSystems.@system x⁺ = A_sys*x + B_sys*u x∈system.X u∈system.U
 end
 
+function proceed_system_linearization(system::MathematicalSystems.ConstrainedLinearControlDiscreteSystem,
+    state::Vector{Float64}, 
+    input::Vector{Float64} )
+
+    return system
+end
+
+function proceed_system_linearization(system::MathematicalSystems.ConstrainedLinearControlContinuousSystem,
+    state::Vector{Float64}, 
+    input::Vector{Float64} )
+
+    return system
+end
+
 
 # to continuous system to discrete system
+
+
+# Extract model from a system from identification and user function
+function proceed_system_model_evaluation(system::MathematicalSystems.ConstrainedBlackBoxControlDiscreteSystem)
+
+    if typeof(system.f) == Flux.Chain{Tuple{Flux.Dense{typeof(identity), Matrix{Float32}, Bool}, Flux.Chain{NTuple{4, Flux.Dense{typeof(NNlib.relu), Matrix{Float32}, Vector{Float32}}}}, Flux.Dense{typeof(identity), Matrix{Float32}, Bool}}}
+        model_type = AutomationLabsIdentification.Fnn()
+
+    elseif typeof(system.f) == Flux.Chain{Tuple{AutomationLabsIdentification.DenseIcnn{typeof(identity), Matrix{Float32}, Bool}, Flux.Chain{Tuple{AutomationLabsIdentification.DenseIcnn{typeof(NNlib.relu), Matrix{Float32}, Vector{Float32}}, AutomationLabsIdentification.DenseIcnn{typeof(NNlib.relu), Matrix{Float32}, Vector{Float32}}}}, AutomationLabsIdentification.DenseIcnn{typeof(identity), Matrix{Float32}, Bool}}}
+        model_type = AutomationLabsIdentification.Icnn()
+
+    elseif typeof(system.f) == Flux.Chain{Tuple{Flux.Dense{typeof(identity), Matrix{Float32}, Bool}, Flux.Chain{Tuple{Flux.SkipConnection{Flux.Chain{Tuple{Flux.Dense{typeof(NNlib.relu), Matrix{Float32}, Vector{Float32}}}}, typeof(+)}}}, Flux.Dense{typeof(identity), Matrix{Float32}, Bool}}}
+        model_type = AutomationLabsIdentification.ResNet()
+
+    elseif typeof(system.f) == Flux.Chain{Tuple{Flux.Dense{typeof(identity), Matrix{Float32}, Bool}, Flux.Chain{Tuple{Flux.SkipConnection{Flux.Chain{Tuple{Flux.Dense{typeof(NNlib.relu), Matrix{Float32}, Vector{Float32}}}}, typeof(vcat)}}}, Flux.Dense{typeof(identity), Matrix{Float32}, Bool}}}
+        model_type = AutomationLabsIdentification.DenseNet()
+
+    elseif typeof(system.f) == Flux.Chain{Tuple{Flux.Dense{typeof(identity), Matrix{Float32}, Bool}, Flux.Chain{NTuple{4, Flux.SkipConnection{Flux.Parallel{typeof(+), Tuple{Flux.Dense{typeof(NNlib.relu), Matrix{Float32}, Vector{Float32}}, Flux.Chain{Tuple{Flux.Dense{typeof(NNlib.relu), Matrix{Float32}, Vector{Float32}}, Flux.Dense{typeof(NNlib.relu), Matrix{Float32}, Vector{Float32}}}}}}, typeof(+)}}}, Flux.Dense{typeof(identity), Matrix{Float32}, Bool}}}
+        model_type = AutomationLabsIdentification.PolyNet()
+
+    elseif typeof(system.f) == Function
+        model_type = typeof(system.f)
+
+    end
+
+
+    return model_type 
+end