Add parametric systems

Project.toml

@@ -9,6 +9,7 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 MultivariatePolynomials = "102ac46a-7ee4-5c85-9060-abc95bfdeaa3"
 RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
+Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
 [compat]
@@ -18,5 +19,6 @@ LinearAlgebra = "<0.0.1, 1.4"
 MacroTools = "0.5"
 MultivariatePolynomials = "0.3, 0.4, 0.5"
 RecipesBase = "0.6, 0.7, 0.8, 1.0, 1.1, 1.2"
+Requires = "1.3.1"
 SparseArrays = "<0.0.1, 1.4"
 julia = "1.5"

docs/Project.toml

@@ -6,4 +6,4 @@ LazySets = "b4f0291d-fe17-52bc-9479-3d1a343d9043"
 [compat]
 Documenter = "1"
 DocumenterCitations = "1.3"
-LazySets = "2, 3, 4"
+LazySets = "5"

docs/src/lib/methods.md

@@ -55,6 +55,7 @@ isblackbox(::AbstractSystem)
 isnoisy(::AbstractSystem)
 iscontrolled(::AbstractSystem)
 isconstrained(::AbstractSystem)
+isparametric(::AbstractSystem)
 state_matrix(::AbstractSystem)
 input_matrix(::AbstractSystem)
 noise_matrix(::AbstractSystem)

docs/src/lib/types.md

@@ -57,6 +57,8 @@ SecondOrderConstrainedAffineControlContinuousSystem
 SecondOrderConstrainedLinearControlContinuousSystem
 SecondOrderContinuousSystem
 SecondOrderConstrainedContinuousSystem
+LinearParametricContinuousSystem
+LinearControlParametricContinuousSystem
 ```
 
 ## Discrete Systems
@@ -94,6 +96,8 @@ SecondOrderConstrainedAffineControlDiscreteSystem
 SecondOrderConstrainedLinearControlDiscreteSystem
 SecondOrderDiscreteSystem
 SecondOrderConstrainedDiscreteSystem
+LinearParametricDiscreteSystem
+LinearControlParametricDiscreteSystem
 ```
 
 #### Discretization Algorithms

docs/src/man/systems.md

@@ -99,6 +99,8 @@ However in this table we only included continuous system types for brevity.
 |SOACS|[`SecondOrderAffineContinuousSystem`](@ref)|
 |SOCACCS|[`SecondOrderConstrainedAffineControlContinuousSystem`](@ref)|
 |SOCLCCS|[`SecondOrderConstrainedLinearControlContinuousSystem`](@ref)|
+|LPCS|[`LinearParametricContinuousSystem`](@ref)|
+|LCPCS|[`LinearControlParametricContinuousSystem`](@ref)|
 
 The following table summarizes the equation represented by each system type
 (the names are given in abbreviated form). Again, discrete systems are not included. The column *Input constraints* is `yes` if the structure can model input or noise constraints (or both).
@@ -137,3 +139,5 @@ The following table summarizes the equation represented by each system type
 |``Mx'' + Cx' + Kx = Bu, x ∈ X, u ∈ U``|yes|yes|SOCLCCS|
 |``Mx'' + Cx' + f_i(x) = f_e``|no|no|SOCS|
 |``Mx'' + Cx' + f_i(x) = f_e``, x ∈ X, u ∈ U``|yes|yes|SOCCS|
+|``x' = A(θ)x, θ ∈ Θ``| no|no|LPCS|
+|``x' = A(θ)x + B(θ)u, θ ∈ Θ``| no|no|LPCS|

src/MathematicalSystems.jl

@@ -1,5 +1,6 @@
 module MathematicalSystems
 
+using Requires
 using LinearAlgebra, SparseArrays
 using LinearAlgebra: checksquare
 import RecipesBase
@@ -55,7 +56,8 @@ export islinear,
        isblackbox,
        isnoisy,
        iscontrolled,
-       isconstrained
+       isconstrained,
+       isparametric
 
 #====================================
 Concrete Types for Continuous Systems

src/abstract.jl

@@ -213,6 +213,18 @@ can also be applied to `typeof(s)`.
 """
 function isconstrained(::AbstractSystem) end
 
+"""
+    isparametric(s::AbstractSystem)
+
+Determines if the system `s` contains one or more symbolic parameters in its
+dynamics (for example, matrix entries that can take values from a
+specified set).
+
+The result of this function only depends on the
+system type, not the value, and can also be applied to `typeof(s)`.
+"""
+function isparametric(::AbstractSystem) end
+
 """
     AbstractMap
 

src/macros.jl

@@ -127,7 +127,7 @@ Return the system type whose field names match those in `fields`.
 ### Input
 
 - `AT`     -- abstract system type, which can be either `AbstractContinuousSystem`
-              or `AbstractDiscreSystem`
+              or `AbstractDiscreteSystem`
 - `fields` -- tuple of field names
 
 ### Output