test: LinMPC construction with custom linear constraints

Author: franckgaga

src/controller/construct.jl

@@ -108,18 +108,18 @@ function validate_weights(model, Hp, Hc, M_Hp, N_Hc, L_Hp, C=Inf, E=nothing)
     Hp < 1  && throw(ArgumentError("Prediction horizon Hp should be ≥ 1"))
     Hc < 1  && throw(ArgumentError("Control horizon Hc should be ≥ 1"))
     Hc > Hp && throw(ArgumentError("Control horizon Hc should be ≤ prediction horizon Hp"))
-    size(M_Hp) ≠ (nM,nM) && throw(ArgumentError("M_Hp size $(size(M_Hp)) ≠ (ny*Hp, ny*Hp) ($nM,$nM)"))
-    size(N_Hc) ≠ (nN,nN) && throw(ArgumentError("N_Hc size $(size(N_Hc)) ≠ (nu*Hc, nu*Hc) ($nN,$nN)"))
-    size(L_Hp) ≠ (nL,nL) && throw(ArgumentError("L_Hp size $(size(L_Hp)) ≠ (nu*Hp, nu*Hp) ($nL,$nL)"))
+    size(M_Hp) ≠ (nM,nM) && throw(DimensionMismatch("M_Hp size $(size(M_Hp)) ≠ (ny*Hp, ny*Hp) ($nM,$nM)"))
+    size(N_Hc) ≠ (nN,nN) && throw(DimensionMismatch("N_Hc size $(size(N_Hc)) ≠ (nu*Hc, nu*Hc) ($nN,$nN)"))
+    size(L_Hp) ≠ (nL,nL) && throw(DimensionMismatch("L_Hp size $(size(L_Hp)) ≠ (nu*Hp, nu*Hp) ($nL,$nL)"))
     (isdiag(M_Hp) && any(diag(M_Hp) .< 0)) && throw(ArgumentError("Mwt values should be nonnegative"))
     (isdiag(N_Hc) && any(diag(N_Hc) .< 0)) && throw(ArgumentError("Nwt values should be nonnegative"))
     (isdiag(L_Hp) && any(diag(L_Hp) .< 0)) && throw(ArgumentError("Lwt values should be nonnegative"))
     !ishermitian(M_Hp) && throw(ArgumentError("M_Hp should be hermitian"))
     !ishermitian(N_Hc) && throw(ArgumentError("N_Hc should be hermitian"))
     !ishermitian(L_Hp) && throw(ArgumentError("L_Hp should be hermitian"))
-    size(C) ≠ ()    && throw(ArgumentError("Cwt should be a real scalar"))
+    size(C) ≠ ()    && throw(DimensionMismatch("Cwt should be a real scalar"))
     C < 0           && throw(ArgumentError("Cwt weight should be ≥ 0"))
-    !isnothing(E) && size(E) ≠ () && throw(ArgumentError("Ewt should be a real scalar"))
+    !isnothing(E) && size(E) ≠ () && throw(DimensionMismatch("Ewt should be a real scalar"))
 end
 
 "Include all the data for the constraints of [`PredictiveController`](@ref)"

test/3_test_predictive_control.jl

@@ -53,6 +53,23 @@
     mpc16 = LinMPC(model, Hc=[1,2,3,6,6,6], Hp=10, Cwt=Inf)
     @test mpc16.Hc == 4 # the last 2 elements of Hc are ignored
     @test size(mpc16.P̃u) == (10*mpc1.estim.model.nu, 4*mpc1.estim.model.nu)
+    
+    Wy = ones(3, ny)
+    mpc17 = LinMPC(model; Wy)
+    @test mpc17.con.W̄y ≈ ModelPredictiveControl.repeatdiag(Wy, mpc17.Hp+1)
+    @test mpc17.con.W̄u ≈ zeros(model.nu*(mpc17.Hp+1), model.nu*(mpc17.Hp+1))
+    @test mpc17.con.W̄d ≈ zeros(model.nd*(mpc17.Hp+1), model.nd*(mpc17.Hp+1))
+    @test mpc17.con.W̄r ≈ zeros(model.ny*(mpc17.Hp+1), model.ny*(mpc17.Hp+1))
+    
+    Wy = ones(2, model.ny)
+    Wu = 2*ones(2, model.nu)
+    Wd = 3*ones(2, model.nd)
+    Wr = 0.5*ones(2, model.ny)
+    mpc18 = LinMPC(model; Wy, Wu, Wd, Wr)
+    @test mpc18.con.W̄y ≈ ModelPredictiveControl.repeatdiag(Wy, mpc18.Hp+1)
+    @test mpc18.con.W̄u ≈ ModelPredictiveControl.repeatdiag(Wu, mpc18.Hp+1)
+    @test mpc18.con.W̄d ≈ ModelPredictiveControl.repeatdiag(Wd, mpc18.Hp+1)
+    @test mpc18.con.W̄r ≈ ModelPredictiveControl.repeatdiag(Wr, mpc18.Hp+1)
 
     @test_logs(
         (:warn, 
@@ -62,14 +79,19 @@
     )
     @test_throws ArgumentError LinMPC(model, Hc=0)
     @test_throws ArgumentError LinMPC(model, Hp=1, Hc=2)
-    @test_throws ArgumentError LinMPC(model, Mwt=[1])
-    @test_throws ArgumentError LinMPC(model, Mwt=[1])
-    @test_throws ArgumentError LinMPC(model, Lwt=[1])
-    @test_throws ArgumentError LinMPC(model, Cwt=[1])
+    @test_throws DimensionMismatch LinMPC(model, Mwt=[1])
+    @test_throws DimensionMismatch LinMPC(model, Mwt=[1])
+    @test_throws DimensionMismatch LinMPC(model, Lwt=[1])
+    @test_throws DimensionMismatch LinMPC(model, Cwt=[1])
     @test_throws ArgumentError LinMPC(model, Mwt=[-1,1])
     @test_throws ArgumentError LinMPC(model, Nwt=[-1,1])
     @test_throws ArgumentError LinMPC(model, Lwt=[-1,1])
     @test_throws ArgumentError LinMPC(model, Cwt=-1)
+    @test_throws DimensionMismatch LinMPC(model, Wy=ones(2, ny+1))
+    @test_throws DimensionMismatch LinMPC(model, Wu=ones(2, nu-1))
+    @test_throws DimensionMismatch LinMPC(model, Wd=ones(2, nd+1))
+    @test_throws DimensionMismatch LinMPC(model, Wr=ones(2, ny-1))
+    @test_throws DimensionMismatch LinMPC(model, Wy=ones(2, ny), Wu=ones(3, nu))
 end
 
 @testitem "LinMPC moves and getinfo" setup=[SetupMPCtests] begin