debug julia 1.6

Author: franckgaga

src/controller/explicitmpc.jl

@@ -38,6 +38,7 @@ struct ExplicitMPC{SE<:StateEstimator} <: PredictiveController
         Cwt = Inf # no slack variable ϵ for ExplicitMPC
         Ewt = 0   # economic costs not supported for ExplicitMPC
         validate_weights(model, Hp, Hc, M_Hp, N_Hc, L_Hp, Cwt)
+        M_Hp, N_Hc, L_Hp = float(M_Hp), float(N_Hc), float(L_Hp) # debug julia 1.6
         R̂y, R̂u = zeros(ny*Hp), zeros(nu*Hp) # dummy vals (updated just before optimization)
         noR̂u = iszero(L_Hp)
         S, T = init_ΔUtoU(nu, Hp, Hc)

src/controller/linmpc.jl

@@ -40,6 +40,7 @@ struct LinMPC{SE<:StateEstimator} <: PredictiveController
         ŷ = copy(model.yop) # dummy vals (updated just before optimization)
         Ewt = 0   # economic costs not supported for LinMPC
         validate_weights(model, Hp, Hc, M_Hp, N_Hc, L_Hp, Cwt)
+        M_Hp, N_Hc, L_Hp = float(M_Hp), float(N_Hc), float(L_Hp) # debug julia 1.6
         R̂y, R̂u = zeros(ny*Hp), zeros(nu*Hp) # dummy vals (updated just before optimization)
         noR̂u = iszero(L_Hp)
         S, T = init_ΔUtoU(nu, Hp, Hc)

src/controller/nonlinmpc.jl

@@ -44,6 +44,7 @@ struct NonLinMPC{SE<:StateEstimator, JEfunc<:Function} <: PredictiveController
         nu, ny, nd = model.nu, model.ny, model.nd
         ŷ = copy(model.yop) # dummy vals (updated just before optimization)
         validate_weights(model, Hp, Hc, M_Hp, N_Hc, L_Hp, Cwt, Ewt)
+        M_Hp, N_Hc, L_Hp = float(M_Hp), float(N_Hc), float(L_Hp) # debug julia 1.6
         R̂y, R̂u = zeros(ny*Hp), zeros(nu*Hp) # dummy vals (updated just before optimization)
         noR̂u = iszero(L_Hp)
         S, T = init_ΔUtoU(nu, Hp, Hc)

test/test_predictive_control.jl

@@ -26,13 +26,12 @@ sys = [ tf(1.90,[18.0,1])   tf(1.90,[18.0,1])   tf(1.90,[18.0,1]);
     mpc9 = LinMPC(model, nint_u=[1, 1], nint_ym=[0, 0])
     @test mpc9.estim.nint_u  == [1, 1]
     @test mpc9.estim.nint_ym == [0, 0]
-
-    mpc10 = LinMPC(model, M_Hp=Diagonal(1.01:0.01:1.2))
-    @test mpc10.M_Hp ≈ Diagonal(1.01:0.01:1.2)
+    mpc10 = LinMPC(model, M_Hp=Diagonal(collect(1.01:0.01:1.2)))
+    @test mpc10.M_Hp ≈ Diagonal(collect(1.01:0.01:1.2))
     mpc11 = LinMPC(model, N_Hc=Diagonal([0.1,0.11,0.12,0.13]), Cwt=Inf)
     @test mpc11.Ñ_Hc ≈ Diagonal([0.1,0.11,0.12,0.13])
-    mcp12 = LinMPC(model, L_Hp=Diagonal(0.001:0.001:0.02))
-    @test mcp12.L_Hp ≈ Diagonal(0.001:0.001:0.02)
+    mcp12 = LinMPC(model, L_Hp=Diagonal(collect(0.001:0.001:0.02)))
+    @test mcp12.L_Hp ≈ Diagonal(collect(0.001:0.001:0.02))
 
     @test_throws ArgumentError LinMPC(model, Hp=0)
     @test_throws ArgumentError LinMPC(model, Hc=0)
@@ -243,12 +242,12 @@ end
     mpc9 = ExplicitMPC(model, nint_u=[1, 1], nint_ym=[0, 0])
     @test mpc9.estim.nint_u  == [1, 1]
     @test mpc9.estim.nint_ym == [0, 0]
-    mpc10 = ExplicitMPC(model, M_Hp=Diagonal(1.01:0.01:1.2))
-    @test mpc10.M_Hp ≈ Diagonal(1.01:0.01:1.2)
+    mpc10 = ExplicitMPC(model, M_Hp=Diagonal(collect(1.01:0.01:1.2)))
+    @test mpc10.M_Hp ≈ Diagonal(collect(1.01:0.01:1.2))
     mpc11 = ExplicitMPC(model, N_Hc=Diagonal([0.1,0.11,0.12,0.13]))
     @test mpc11.Ñ_Hc ≈ Diagonal([0.1,0.11,0.12,0.13])
-    mcp12 = ExplicitMPC(model, L_Hp=Diagonal(0.001:0.001:0.02))
-    @test mcp12.L_Hp ≈ Diagonal(0.001:0.001:0.02)
+    mcp12 = ExplicitMPC(model, L_Hp=Diagonal(collect(0.001:0.001:0.02)))
+    @test mcp12.L_Hp ≈ Diagonal(collect(0.001:0.001:0.02))
 end
 
 @testset "ExplicitMPC moves and getinfo" begin
@@ -362,12 +361,12 @@ end
     nmpc11 = NonLinMPC(nonlinmodel, Hp=15, nint_u=[1, 1], nint_ym=[0, 0])
     @test nmpc11.estim.nint_u  == [1, 1]
     @test nmpc11.estim.nint_ym == [0, 0]
-    nmpc12 = NonLinMPC(nonlinmodel, M_Hp=Diagonal(1.01:0.01:1.2))
-    @test nmpc12.M_Hp ≈ Diagonal(1.01:0.01:1.2)
+    nmpc12 = NonLinMPC(nonlinmodel, M_Hp=Diagonal(collect(1.01:0.01:1.2)))
+    @test nmpc12.M_Hp ≈ Diagonal(collect(1.01:0.01:1.2))
     nmpc13 = NonLinMPC(nonlinmodel, N_Hc=Diagonal([0.1,0.11,0.12,0.13]), Cwt=Inf)
     @test nmpc13.Ñ_Hc ≈ Diagonal([0.1,0.11,0.12,0.13])
-    nmcp14 = NonLinMPC(nonlinmodel, L_Hp=Diagonal(0.001:0.001:0.02))
-    @test nmcp14.L_Hp ≈ Diagonal(0.001:0.001:0.02)
+    nmcp14 = NonLinMPC(nonlinmodel, L_Hp=Diagonal(collect(0.001:0.001:0.02)))
+    @test nmcp14.L_Hp ≈ Diagonal(collect(0.001:0.001:0.02))
 
     @test_throws ArgumentError NonLinMPC(nonlinmodel, Hp=15, Ewt=[1, 1])
     # to uncomment when deprecated constructor is removed: