bump version

Author: baggepinnen

Project.toml

@@ -1,7 +1,7 @@
 name = "RobustAndOptimalControl"
 uuid = "21fd56a4-db03-40ee-82ee-a87907bee541"
 authors = ["Fredrik Bagge Carlson", "Marcus Greiff"]
-version = "0.2.3"
+version = "0.2.4"
 
 [deps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"

src/glover_mcfarlane.jl

@@ -154,7 +154,7 @@ end
 
 
 """
-    `Wh` = hanus(W)
+    Wh = hanus(W)
 
 Return `Wh` on Hanus form. `Wh` has twice the number of inputs, where the second half of the inputs are "actual inputs", e.g., potentially saturated. This is used to endow `W` with anti-windup protection.
 `W` must have an invertable `D` matrix and be minimum phase.

src/plotting.jl

@@ -98,7 +98,7 @@ specificationplot(sens::T, γ::Number; kwargs...) where {T<:LTISystem} =
 
 @userplot MvNyquistplot
 """
-    fig = nyquistplot(sys, w;  unit_circle=false, hz = false, kwargs...)
+    fig = mvnyquistplot(sys, w;  unit_circle=false, hz = false, kwargs...)
 
 Create a Nyquist plot of the `LTISystem`. A frequency vector `w` must be
 provided.
@@ -108,16 +108,17 @@ If `hz=true`, the hover information will be displayed in Hertz, the input freque
 
 `kwargs` is sent as argument to plot.
 """
-nyquistplot
-@recipe function nyquistplot(p::MvNyquistplot;  unit_circle=false, hz=false)
+mvnyquistplot
+@recipe function mvnyquistplot(p::MvNyquistplot;  unit_circle=false, hz=false)
+    length(p.args) == 2 || throw(ArgumentError("You must provide a frequency vector."))
     sys, w = p.args
     nw = length(w)
     framestyle --> :zerolines
     θ = range(0, stop=2π, length=100)
     S, C = sin.(θ), cos.(θ)
-    L = freqresp(sys, w)
-    dets = map(axes(L, 1)) do i
-        det(I + L[i,:,:])
+    L = freqresp(sys, w).parent
+    dets = map(axes(L, 3)) do i
+        det(I + L[:,:,i])
     end
     dets = vec(dets)
     redata = real.(dets)

test/test_reduction.jl

@@ -156,14 +156,14 @@ end
 
 # Pcl, S, CS, T = hinfsignals(P, G, C)
 
-# Cr = controller_reduction(P,C,7, false)
+# Cr = RobustAndOptimalControl.controller_reduction(P,C,7, false)
 # Cr2 = baltrunc(C,n=7)[1]
 # Pclr, Sr, CSr, Tr = hinfsignals(P, G, Cr)
 # Pclr2, Sr2, CSr2, Tr2 = hinfsignals(P, G, Cr2)
 # bodeplot([Pcl, Pclr], plotphase=false, size=(1900,920))
 # bodeplot([C, Cr, Cr2])
 
-# hinfn = ControlSystems._infnorm_two_steps_ct(minreal(Pcl-Pclr), :hinf, 1e-9, 1000, 1e-6)[1]
+# hinfn = hinfnorm2(minreal(Pcl-Pclr))[1]
 # @test hinfn ≈ 14.88609988 rtol=1e-3
 # @test isstable(Pclr)