debug: JE default values with p arg

Author: franckgaga

src/controller/nonlinmpc.jl

@@ -204,7 +204,7 @@ function NonLinMPC(
     L_Hp = diagm(repeat(Lwt, Hp)),
     Cwt  = DEFAULT_CWT,
     Ewt  = DEFAULT_EWT,
-    JE::Function = (_,_,_) -> 0.0,
+    JE::Function = (_,_,_,_) -> 0.0,
     p = model.p,
     optim::JuMP.GenericModel = JuMP.Model(DEFAULT_NONLINMPC_OPTIMIZER, add_bridges=false),
     kwargs...
@@ -270,7 +270,7 @@ function NonLinMPC(
     L_Hp = diagm(repeat(Lwt, Hp)),
     Cwt  = DEFAULT_CWT,
     Ewt  = DEFAULT_EWT,
-    JE::JEFunc = (_,_,_) -> 0.0,
+    JE::JEFunc = (_,_,_,_) -> 0.0,
     p::P = estim.model.p,
     optim::JM = JuMP.Model(DEFAULT_NONLINMPC_OPTIMIZER, add_bridges=false),
 ) where {NT<:Real, SE<:StateEstimator{NT}, JM<:JuMP.GenericModel, JEFunc<:Function, P<:Any}

test/test_predictive_control.jl

@@ -493,7 +493,7 @@ end
     @test nmpc6.L_Hp ≈ Diagonal(diagm(repeat(Float64[0, 1], 15)))
     nmpc7 = NonLinMPC(nonlinmodel, Hp=15, Ewt=1e-3, JE=(UE,ŶE,D̂E,p) -> p*UE.*ŶE.*D̂E, p=2)
     @test nmpc7.E == 1e-3
-    @test nmpc7.JE([1,2],[3,4],[4,6],2) == 2*[1,2].*[3.4].*[4,6]
+    @test nmpc7.JE([1,2],[3,4],[4,6],2) == 2*[1,2].*[3,4].*[4,6]
     optim = JuMP.Model(optimizer_with_attributes(Ipopt.Optimizer, "nlp_scaling_max_gradient"=>1.0))
     nmpc8 = NonLinMPC(nonlinmodel, Hp=15, optim=optim)
     @test solver_name(nmpc8.optim) == "Ipopt"
@@ -537,8 +537,8 @@ end
     @test info[:Ŷ][end] ≈ r[1] atol=5e-2
     Hp = 1000
     R̂y = fill(r[1], Hp)
-    JE = (_ , ŶE, _ ) -> sum((ŶE[2:end] - R̂y).^2)
-    nmpc = NonLinMPC(linmodel, Mwt=[0], Nwt=[0], Cwt=Inf, Ewt=1, JE=JE, Hp=Hp, Hc=1)
+    JE = (_ , ŶE, _ , R̂y) -> sum((ŶE[2:end] - R̂y).^2)
+    nmpc = NonLinMPC(linmodel, Mwt=[0], Nwt=[0], Cwt=Inf, Ewt=1, JE=JE, p=R̂y, Hp=Hp, Hc=1)
     preparestate!(nmpc, [10])
     u = moveinput!(nmpc)
     @test u ≈ [1] atol=5e-2