system determinant

docs/src/index.md

@@ -84,7 +84,8 @@ The following is a list of packages from the wider Julia ecosystem that may be o
 - [DescriptorSystems.jl](https://github.com/andreasvarga/DescriptorSystems.jl) contains types that represent statespace systems on descriptor form, i.e., with a mass matrix. These systems can represent linear DAE systems and non-proper systems.
 - [LowLevelParticleFilters.jl](https://github.com/baggepinnen/LowLevelParticleFilters.jl) is a library for state estimation using particle filters and Kalman filters of different flavors.
 - [ModelingToolkit.jl](https://mtk.sciml.ai/stable/) is an acausal modeling tool, similar in spirit to Modelica. A video showing ControlSystems and ModelingToolkit together is [available here](https://youtu.be/favQKOyyx4o). [ControlSystemsMTK.jl](https://juliacontrol.github.io/ControlSystemsMTK.jl/dev/) exists to ease the use of these two packages together.
-- [JuliaSimControl.jl](https://help.juliahub.com/juliasimcontrol/dev/) is a product that builds upon the JuliaControl ecosystem and ModelingToolkit, providing additional nonlinear and robust control methods.
+- [DyadControlSystems.jl](https://help.juliahub.com/dyadcontrol/dev/) is a product that builds upon the JuliaControl ecosystem and ModelingToolkit, providing additional nonlinear and robust control methods.
+- [LinearMPC.jl](https://darnstrom.github.io/LinearMPC.jl/stable/) A package for linear quadratic MPC that supports generation of embeddable C-code for real-time applications.
 - [FaultDetectionTools.jl](https://github.com/andreasvarga/FaultDetectionTools.jl) contains utilities and observers for online fault detection.
 - [ReachabilityAnalysis.jl](https://juliareach.github.io/ReachabilityAnalysis.jl/dev/generated_examples/Building/) is a package for reachability analysis. This can be used to verify stability and safety properties of linear and nonlinear systems.
 - [MatrixEquations.jl](https://github.com/andreasvarga/MatrixEquations.jl) contains solvers for many different matrix equations common in control. ControlSystems.jl makes use of this package for solving Riccati and Lyapunov equations.

lib/ControlSystemsBase/src/matrix_comps.jl

@@ -1019,4 +1019,13 @@ end
 
 function observer_filter(sys::AbstractStateSpace{Continuous}, K::AbstractMatrix; kwargs...)
     observer_predictor(sys, K; kwargs...)
-end
+end
+
+function LinearAlgebra.det(sys::LTISystem)
+    sys = deepcopy(sys)
+    arrayofsys = getindex.(Ref(sys), 1:sys.ny, (1:sys.nu)')
+    if sys isa AbstractStateSpace
+        @. arrayofsys = sminreal(arrayofsys)
+    end
+    LinearAlgebra.det_bareiss!(arrayofsys)
+end

lib/ControlSystemsBase/src/types/StateSpace.jl

@@ -265,6 +265,10 @@ Base.zero(sys::AbstractStateSpace) = basetype(sys)(zero(sys.D), sys.timeevol)
 Base.zero(::Type{StateSpace{Continuous, F}}) where {F} = ss([zero(F)], Continuous())
 Base.zero(::Type{StateSpace{D, F}}) where {D<:Discrete, F} = ss([zero(F)], undef_sampletime(D))
 
+# one is a multiplicative identity, which can be set to the one of the element type. This is different from oneunit which should be of the same type.
+Base.one(::Type{StateSpace{TE, T}}) where {TE, T} = Base.one(T)
+
+
 function +(s1::ST, s2::ST) where {ST <: AbstractStateSpace}
     #Ensure systems have same dimensions
     if size(s1) != size(s2)

lib/ControlSystemsBase/test/test_matrix_comps.jl

@@ -11,6 +11,12 @@ sysr, G = balreal(sys)
 @test gram(sysr, :o) ≈ diagm(G)
 @test sort(poles(sysr), by=real) ≈ sort(poles(sys), by=real)
 
+@testset "det" begin
+    detsys = det(sys)
+    w = 0.1
+    @test freqresp(detsys, w)[1] ≈ det(freqresp(sys, w))
+end
+
 sysb,T = ControlSystemsBase.balance_statespace(sys)
 @test similarity_transform(sysb, T) ≈ sys
 Ab,Bb,Cb,T = ControlSystemsBase.balance_statespace(A,B,C)