Merge pull request #278 from JuliaControl/debug_constant_DI

debug: prepare AD with `rand` constant contexts

Author: franckgaga

src/controller/nonlinmpc.jl

@@ -761,7 +761,7 @@ function get_nonlincon_oracle(mpc::NonLinMPC, ::JuMP.GenericModel{JNT}) where JN
     Û0::Vector{JNT}, X̂0::Vector{JNT}  = zeros(JNT, nU),  zeros(JNT, nX̂)
     gc::Vector{JNT}, g::Vector{JNT}   = zeros(JNT, nc),  zeros(JNT, ng)
     gi::Vector{JNT}, geq::Vector{JNT} = zeros(JNT, ngi), zeros(JNT, neq)
-    λi::Vector{JNT}, λeq::Vector{JNT} = ones(JNT, ngi),  ones(JNT, neq)
+    λi::Vector{JNT}, λeq::Vector{JNT} = rand(JNT, ngi),  rand(JNT, neq)
     # -------------- inequality constraint: nonlinear oracle -----------------------------
     function gi!(gi, Z̃, ΔŨ, x̂0end, Ue, Ŷe, U0, Ŷ0, Û0, K0, X̂0, gc, geq, g)
         update_predictions!(ΔŨ, x̂0end, Ue, Ŷe, U0, Ŷ0, Û0, K0, X̂0, gc, g, geq, mpc, Z̃)

src/estimator/kalman.jl

@@ -1111,8 +1111,8 @@ function get_ekf_linfuncs(NT, model, i_ym, nint_u, nint_ym, jacobian)
     x̂0 = zeros(NT, nx̂)
     û0 = Cache(zeros(NT, nu))
     k0 = Cache(zeros(NT, nk))
-    cst_u0 = Constant(zeros(NT, nu))
-    cst_d0 = Constant(zeros(NT, nd))
+    cst_u0 = Constant(rand(NT, nu))
+    cst_d0 = Constant(rand(NT, nd))
     F̂prep = prepare_jacobian(
         f̂_ekf!, x̂0next, jacobian, x̂0, û0, k0, cst_u0, cst_d0; strict
     )

src/estimator/mhe/construct.jl

@@ -1478,7 +1478,7 @@ function get_nonlincon_oracle(
     k0::Vector{JNT}                  = zeros(JNT, nk)
     û0::Vector{JNT}, ŷ0::Vector{JNT} = zeros(JNT, nu), zeros(JNT, nŷ)
     g::Vector{JNT}, gi::Vector{JNT}  = zeros(JNT, ng), zeros(JNT, ngi)
-    λi::Vector{JNT}                  = ones(JNT, ngi)
+    λi::Vector{JNT}                  = rand(JNT, ngi)
     # -------------- inequality constraint: nonlinear oracle -------------------------
     function gi!(gi, Z̃, V̂, X̂0, û0, k0, ŷ0, g)
         update_prediction!(V̂, X̂0, û0, k0, ŷ0, g, estim, Z̃)

src/model/linearization.jl

@@ -29,9 +29,9 @@ function get_linearization_func(
     d = zeros(NT, nd)
     k = zeros(NT, nx*(solver.ni+1))
     cache_k = Cache(k)
-    cst_x = Constant(x)
-    cst_u = Constant(u)
-    cst_d = Constant(d)
+    cst_x = Constant(rand(NT, nx))
+    cst_u = Constant(rand(NT, nu))
+    cst_d = Constant(rand(NT, nd))
     A_prep  = prepare_jacobian(f_x!, xnext, backend, x, cache_k, cst_u, cst_d; strict)
     Bu_prep = prepare_jacobian(f_u!, xnext, backend, u, cache_k, cst_x, cst_d; strict)
     Bd_prep = prepare_jacobian(f_d!, xnext, backend, d, cache_k, cst_x, cst_u; strict)