Merge pull request #72 from JuliaControl/mhe_notation_dev_var

cleanup MHE append 0 to deviation vector variables

Author: franckgaga

src/estimator/mhe/construct.jl

@@ -1115,38 +1115,38 @@ function get_optim_functions(
     nx̂, nym, nŷ, nu, He = estim.nx̂, estim.nym, model.ny, model.nu, estim.He
     nV̂, nX̂, ng, nZ̃ = He*nym, He*nx̂, length(con.i_g), length(estim.Z̃)
     Nc = nZ̃ + 3
-    Z̃_cache::DiffCache{Vector{JNT}, Vector{JNT}} = DiffCache(zeros(JNT, nZ̃), Nc)
-    V̂_cache::DiffCache{Vector{JNT}, Vector{JNT}} = DiffCache(zeros(JNT, nV̂), Nc)
-    g_cache::DiffCache{Vector{JNT}, Vector{JNT}} = DiffCache(zeros(JNT, ng), Nc)
-    X̂_cache::DiffCache{Vector{JNT}, Vector{JNT}} = DiffCache(zeros(JNT, nX̂), Nc)
-    x̄_cache::DiffCache{Vector{JNT}, Vector{JNT}} = DiffCache(zeros(JNT, nx̂), Nc)
-    û_cache::DiffCache{Vector{JNT}, Vector{JNT}} = DiffCache(zeros(JNT, nu), Nc)
-    ŷ_cache::DiffCache{Vector{JNT}, Vector{JNT}} = DiffCache(zeros(JNT, nŷ), Nc)
+    Z̃_cache::DiffCache{Vector{JNT}, Vector{JNT}}  = DiffCache(zeros(JNT, nZ̃), Nc)
+    V̂_cache::DiffCache{Vector{JNT}, Vector{JNT}}  = DiffCache(zeros(JNT, nV̂), Nc)
+    g_cache::DiffCache{Vector{JNT}, Vector{JNT}}  = DiffCache(zeros(JNT, ng), Nc)
+    X̂0_cache::DiffCache{Vector{JNT}, Vector{JNT}} = DiffCache(zeros(JNT, nX̂), Nc)
+    x̄_cache::DiffCache{Vector{JNT}, Vector{JNT}}  = DiffCache(zeros(JNT, nx̂), Nc)
+    û0_cache::DiffCache{Vector{JNT}, Vector{JNT}} = DiffCache(zeros(JNT, nu), Nc)
+    ŷ0_cache::DiffCache{Vector{JNT}, Vector{JNT}} = DiffCache(zeros(JNT, nŷ), Nc)
     function Jfunc(Z̃tup::T...)::T where {T <: Real}
         Z̃1 = Z̃tup[begin]
         Z̃, g = get_tmp(Z̃_cache, Z̃1), get_tmp(g_cache, Z̃1)
         for i in eachindex(Z̃tup)
             Z̃[i] = Z̃tup[i] # Z̃ .= Z̃tup seems to produce a type instability
         end
-        V̂, X̂ = get_tmp(V̂_cache, Z̃1), get_tmp(X̂_cache, Z̃1)
-        û, ŷ = get_tmp(û_cache, Z̃1), get_tmp(ŷ_cache, Z̃1)
-        V̂, X̂ = predict!(V̂, X̂, û, ŷ, estim, model, Z̃)
+        V̂,  X̂0 = get_tmp(V̂_cache, Z̃1),  get_tmp(X̂0_cache, Z̃1)
+        û0, ŷ0 = get_tmp(û0_cache, Z̃1), get_tmp(ŷ0_cache, Z̃1)
+        V̂,  X̂0 = predict!(V̂, X̂0, û0, ŷ0, estim, model, Z̃)
         g = get_tmp(g_cache, Z̃1)
-        g = con_nonlinprog!(g, estim, model, X̂, V̂, Z̃)
+        g = con_nonlinprog!(g, estim, model, X̂0, V̂, Z̃)
         x̄ = get_tmp(x̄_cache, Z̃1)
         return obj_nonlinprog!(x̄, estim, model, V̂, Z̃)::T
     end
     function gfunc_i(i, Z̃tup::NTuple{N, T})::T where {N, T <:Real}
         Z̃1 = Z̃tup[begin]
         Z̃, g = get_tmp(Z̃_cache, Z̃1), get_tmp(g_cache, Z̃1)
         if any(new !== old for (new, old) in zip(Z̃tup, Z̃)) # new Z̃tup, update predictions:
-            V̂, X̂ = get_tmp(V̂_cache, Z̃1), get_tmp(X̂_cache, Z̃1)
-            û, ŷ = get_tmp(û_cache, Z̃1), get_tmp(ŷ_cache, Z̃1)
+            V̂,  X̂0 = get_tmp(V̂_cache, Z̃1),  get_tmp(X̂0_cache, Z̃1)
+            û0, ŷ0 = get_tmp(û0_cache, Z̃1), get_tmp(ŷ0_cache, Z̃1)
             for i in eachindex(Z̃tup)
                 Z̃[i] = Z̃tup[i] # Z̃ .= Z̃tup seems to produce a type instability
             end
-            V̂, X̂ = predict!(V̂, X̂, û, ŷ, estim, model, Z̃)
-            g = con_nonlinprog!(g, estim, model, X̂, V̂, Z̃)
+            V̂, X̂0 = predict!(V̂, X̂0, û0, ŷ0, estim, model, Z̃)
+            g = con_nonlinprog!(g, estim, model, X̂0, V̂, Z̃)
         end
         return g[i]
     end