handle complex uncertain tzeros

Author: baggepinnen

src/mcm_nugap.jl

@@ -33,7 +33,7 @@ Reduce the number of particles in an uncertain system `G` by removing all partic
 
 Note: If `G` has a stochastic interpretation, i.e., the coefficients come from some distribution, this interpretation will be lost after reduction, mean values and standard deviations will not be preserved. The reduced system should instead be interpreted as preserving worst-case uncertainty.
 
-If the `gap = nugap(G)` has already been precomputed, it can be supplied as an argument to avoid potentially costly recomputaiton.
+If the `gap = nugap(G)` has already been precomputed, it can be supplied as an argument to avoid potentially costly recomputation.
 """
 function nu_reduction(G, g=0.1; gap = nugap(G))
     nind = argmin(gap.particles)

src/uncertainty_interface.jl

@@ -510,6 +510,21 @@ end
 
 ControlSystemsBase._bounds_and_features(sys::StateSpace{<:Any, <:AbstractParticles}, plot::Val) = ControlSystemsBase._bounds_and_features(sys_from_particles(sys, 1), plot)
 
+function ControlSystemsBase.tzeros(A::AbstractMatrix{T}, B::AbstractMatrix{T}, C::AbstractMatrix{T}, D::AbstractMatrix{T}) where T <: Complex{<:AbstractParticles}
+    partzeros = map(1:nparticles(A[1].re)) do i
+        tzeros(vecindex(A, i), vecindex(B, i), vecindex(C, i), vecindex(D, i))
+    end
+    PT = typeof(A[1].re)
+    num_zeros = length(partzeros[1])
+    out = zeros(T, num_zeros)
+    for i in 1:num_zeros
+        for j = 1:nparticles(A[1].re)
+            out[i].re.particles[j] = partzeros[j][i].re
+        end
+    end
+    out
+end
+
 # function any0det(D::Matrix{<:Complex{<:AbstractParticles}})
 #     D0 = similar(D, ComplexF64)
 #     maxre = maxim = -1