added: mpc weight modification tests

Author: franckgaga

docs/src/public/generic_func.md

@@ -37,7 +37,7 @@ initstate!
 setstate!
 ```
 
-## Set Plant Model
+## Set Model and Weights
 
 ```@docs
 setmodel!

src/estimator/execute.jl

@@ -246,7 +246,7 @@ Set `model` and covariance matrices of `estim` [`StateEstimator`](@ref).
 
 Allows model adaptation of estimators based on [`LinModel`](@ref) at runtime. Modification 
 of [`NonLinModel`](@ref) is not supported. New covariance matrices can be specified with the
-keyword arguments (see [`SteadyKalmanFilter`](ref) documentation for the nomenclature). Not 
+keyword arguments (see [`SteadyKalmanFilter`](@ref) documentation for the nomenclature). Not 
 supported by [`Luenberger`](@ref) and [`SteadyKalmanFilter`](@ref), use the time-varying
 [`KalmanFilter`](@ref) instead.  The [`MovingHorizonEstimator`](@ref) model is kept constant
 over the estimation horizon ``H_e``. The matrix dimensions and sample time must stay the

test/test_predictive_control.jl

@@ -286,6 +286,10 @@ end
     r = [40]
     u = moveinput!(mpc, r)
     @test u ≈ [13] atol=1e-2
+    setmodel!(mpc, M_Hp=diagm(1:1000), Ñ_Hc=diagm([0.1;1e6]), L_Hp=diagm(1.1:1000.1))
+    @test mpc.M_Hp ≈ diagm(1:1000)
+    @test mpc.Ñ_Hc ≈ diagm([0.1;1e6])
+    @test mpc.L_Hp ≈ diagm(1.1:1000.1)
 end
 
 @testset "ExplicitMPC construction" begin
@@ -413,6 +417,10 @@ end
     r = [40]
     u = moveinput!(mpc, r)
     @test u ≈ [13] atol=1e-2
+    setmodel!(mpc, M_Hp=diagm(1:1000), Ñ_Hc=[0.1], L_Hp=diagm(1.1:1000.1))
+    @test mpc.M_Hp ≈ diagm(1:1000)
+    @test mpc.Ñ_Hc ≈ [0.1]
+    @test mpc.L_Hp ≈ diagm(1.1:1000.1)
 end
 
 @testset "NonLinMPC construction" begin
@@ -712,5 +720,18 @@ end
     r = [40]
     u = moveinput!(mpc, r)
     @test u ≈ [13] atol=1e-2
+    setmodel!(mpc, M_Hp=diagm(1:1000), Ñ_Hc=diagm([0.1;1e6]), L_Hp=diagm(1.1:1000.1))
+    @test mpc.M_Hp ≈ diagm(1:1000)
+    @test mpc.Ñ_Hc ≈ diagm([0.1;1e6])
+    @test mpc.L_Hp ≈ diagm(1.1:1000.1)
+    f(x,u,d) = estim.model.A*x + estim.model.Bu*u + estim.model.Bd*d
+    h(x,d)   = estim.model.C*x + estim.model.Du*d
+    nonlinmodel = NonLinModel(f, h, 10.0, 1, 1, 1)
+    nmpc = NonLinMPC(nonlinmodel, Hp=1000, Hc=1)
+    setmodel!(nmpc, M_Hp=diagm(1:1000), Ñ_Hc=diagm([0.1;1e6]), L_Hp=diagm(1.1:1000.1))
+    @test nmpc.M_Hp ≈ diagm(1:1000)
+    @test nmpc.Ñ_Hc ≈ diagm([0.1;1e6])
+    @test nmpc.L_Hp ≈ diagm(1.1:1000.1)
+    @test_throws ErrorException setmodel!(nmpc, deepcopy(nonlinmodel))
 end
 

test/test_state_estim.jl

@@ -546,6 +546,7 @@ end
     setmodel!(ukf2, Q̂=[1e-3], R̂=[1e-6])
     @test ukf2.Q̂ ≈ [1e-3]
     @test ukf2.R̂ ≈ [1e-6]
+    @test_throws ErrorException setmodel!(ukf2, deepcopy(nonlinmodel))
 end
 
 @testset "ExtendedKalmanFilter construction" begin
@@ -668,6 +669,7 @@ end
     setmodel!(ekf2, Q̂=[1e-3], R̂=[1e-6])
     @test ekf2.Q̂ ≈ [1e-3]
     @test ekf2.R̂ ≈ [1e-6]
+    @test_throws ErrorException setmodel!(ekf2, deepcopy(nonlinmodel))
 end
 
 @testset "MovingHorizonEstimator construction" begin
@@ -1055,4 +1057,5 @@ end
     setmodel!(mhe2, Q̂=[1e-3], R̂=[1e-6])
     @test mhe2.Q̂ ≈ [1e-3]
     @test mhe2.R̂ ≈ [1e-6]
+    @test_throws ErrorException setmodel!(mhe2, deepcopy(nonlinmodel))
 end