added: linearize and setmodel! to precompilation

Author: franckgaga

src/model/linearization.jl

@@ -29,8 +29,8 @@ function get_linearization_func(NT, f!, h!, nu, nx, ny, nd, p)
     A_prep  = prepare_jacobian(f_x!, xnext, backend, x, cst_u, cst_d; strict)
     Bu_prep = prepare_jacobian(f_u!, xnext, backend, u, cst_x, cst_d; strict)
     Bd_prep = prepare_jacobian(f_d!, xnext, backend, d, cst_x, cst_u; strict)
-    C_prep  = prepare_jacobian(h_x!, y,     backend, x, cst_d    ; strict)
-    Dd_prep = prepare_jacobian(h_d!, y,     backend, d, cst_x    ; strict)
+    C_prep  = prepare_jacobian(h_x!, y,     backend, x, cst_d       ; strict)
+    Dd_prep = prepare_jacobian(h_d!, y,     backend, d, cst_x       ; strict)
     function linfunc!(xnext, y, A, Bu, C, Bd, Dd, x, u, d, cst_x, cst_u, cst_d)
         # all the arguments before `x` are mutated in this function
         jacobian!(f_x!, xnext, A,  A_prep,  backend, x, cst_u, cst_d)

src/precompile.jl

@@ -11,59 +11,59 @@ initstate!(mpc_im, model.uop, y)
 preparestate!(mpc_im, [55, 30])
 mpc_im.estim()
 u = mpc_im([55, 30])
-sim!(mpc_im, 3)
+sim!(mpc_im, 2)
 
 mpc_kf = setconstraint!(LinMPC(KalmanFilter(model)), ymin=[45, -Inf])
 initstate!(mpc_kf, model.uop, model())
 preparestate!(mpc_kf, [55, 30])
 mpc_kf.estim()
 u = mpc_kf([55, 30])
-sim!(mpc_kf, 3, [55, 30])
+sim!(mpc_kf, 2, [55, 30])
 
 mpc_lo = setconstraint!(LinMPC(Luenberger(model)), ymin=[45, -Inf])
 initstate!(mpc_lo, model.uop, model())
 preparestate!(mpc_lo, [55, 30])
 mpc_lo.estim()
 u = mpc_lo([55, 30])
-sim!(mpc_lo, 3, [55, 30])
+sim!(mpc_lo, 2, [55, 30])
 
 mpc_ukf = setconstraint!(LinMPC(UnscentedKalmanFilter(model)), ymin=[45, -Inf])
 initstate!(mpc_ukf, model.uop, model())
 preparestate!(mpc_ukf, [55, 30])
 mpc_ukf.estim()
 u = mpc_ukf([55, 3])
-sim!(mpc_ukf, 3, [55, 30])
+sim!(mpc_ukf, 2, [55, 30])
 
 mpc_ekf = setconstraint!(LinMPC(ExtendedKalmanFilter(model)), ymin=[45, -Inf])
 initstate!(mpc_ekf, model.uop, model())
 preparestate!(mpc_ekf, [55, 30])
 mpc_ekf.estim()
 u = mpc_ekf([55, 30])
-sim!(mpc_ekf, 3, [55, 30])
+sim!(mpc_ekf, 2, [55, 30])
 
 mpc_skf = setconstraint!(LinMPC(SteadyKalmanFilter(model)), ymin=[45, -Inf])
 initstate!(mpc_skf, model.uop, model())
 preparestate!(mpc_skf, [55, 30])
 mpc_skf.estim()
 u = mpc_skf([55, 30])
-sim!(mpc_skf, 3, [55, 30])
+sim!(mpc_skf, 2, [55, 30])
 
 mpc_mhe = setconstraint!(LinMPC(MovingHorizonEstimator(model, He=2)), ymin=[45, -Inf])
 setconstraint!(mpc_mhe.estim, x̂min=[-50,-50,-50,-50], x̂max=[50,50,50,50])
 initstate!(mpc_mhe, model.uop, model())
 preparestate!(mpc_mhe, [55, 30])
 mpc_mhe.estim()
 u = mpc_mhe([55, 30])
-sim!(mpc_mhe, 3, [55, 30])
+sim!(mpc_mhe, 2, [55, 30])
 
 nmpc_skf = setconstraint!(NonLinMPC(SteadyKalmanFilter(model), Cwt=Inf), ymin=[45, -Inf])
 initstate!(nmpc_skf, model.uop, model())
 preparestate!(nmpc_skf, [55, 30])
 nmpc_skf.estim()
 u = nmpc_skf([55, 30])
-sim!(nmpc_skf, 3, [55, 30])
+sim!(nmpc_skf, 2, [55, 30])
 
-res = sim!(model, 3)
+res = sim!(model, 2)
 
 res_man = SimResult(model, res.U_data, res.Y_data; X_data=res.X_data)
 
@@ -72,7 +72,7 @@ initstate!(exmpc, model.uop, model())
 preparestate!(exmpc, [55, 30])
 exmpc.estim()
 u = exmpc([55, 30])
-sim!(exmpc, 3, [55, 30])
+sim!(exmpc, 2, [55, 30])
 
 f(x,u,_,model) = model.A*x + model.Bu*u
 h(x,_,model) = model.C*x
@@ -87,21 +87,21 @@ initstate!(nmpc_im, nlmodel.uop, y)
 preparestate!(nmpc_im, [55, 30])
 nmpc_im.estim()
 u = nmpc_im([55, 30])
-sim!(nmpc_im, 3, [55, 30])
+sim!(nmpc_im, 2, [55, 30])
 
 nmpc_ukf = setconstraint!(
     NonLinMPC(UnscentedKalmanFilter(nlmodel), Hp=10, Cwt=1e3), ymin=[45, -Inf]
 )
 initstate!(nmpc_ukf, nlmodel.uop, y)
 preparestate!(nmpc_ukf, [55, 30])
 u = nmpc_ukf([55, 30])
-sim!(nmpc_ukf, 3, [55, 30])
+sim!(nmpc_ukf, 2, [55, 30])
 
 nmpc_ekf = setconstraint!(NonLinMPC(ExtendedKalmanFilter(model), Cwt=Inf), ymin=[45, -Inf])
 initstate!(nmpc_ekf, model.uop, model())
 preparestate!(nmpc_ekf, [55, 30])
 u = nmpc_ekf([55, 30])
-sim!(nmpc_ekf, 3, [55, 30])
+sim!(nmpc_ekf, 2, [55, 30])
 
 nmpc_mhe = setconstraint!(
     NonLinMPC(MovingHorizonEstimator(nlmodel, He=2), Hp=10, Cwt=Inf), ymin=[45, -Inf]
@@ -110,7 +110,7 @@ setconstraint!(nmpc_mhe.estim, x̂min=[-50,-50,-50,-50], x̂max=[50,50,50,50])
 initstate!(nmpc_mhe, nlmodel.uop, y)
 preparestate!(nmpc_mhe, [55, 30])
 u = nmpc_mhe([55, 30])
-sim!(nmpc_mhe, 3, [55, 30])
+sim!(nmpc_mhe, 2, [55, 30])
 
 function JE( _ , Ŷe, _ , R̂y)
     Ŷ = Ŷe[3:end]
@@ -123,4 +123,7 @@ empc = setconstraint!(
 )
 preparestate!(empc, [55, 30])
 u = empc()
-sim!(empc, 3)
+sim!(empc, 2)
+
+linearizemodel = linearize(nlmodel)
+setmodel!(mpc_kf, linearizemodel)