Merge pull request #228 from JuliaControl/tune_bench

bench: increasing `samples` to reduce SD when needed

Author: franckgaga

benchmark/2_bench_state_estim.jl

@@ -149,7 +149,7 @@ mhe_lin_pred    = MovingHorizonEstimator(linmodel, He=10, direct=false)
 mhe_nonlin_curr = MovingHorizonEstimator(nonlinmodel, He=10, direct=true)
 mhe_nonlin_pred = MovingHorizonEstimator(nonlinmodel, He=10, direct=false)
 
-samples, evals, seconds = 5000, 1, 60
+samples, evals, seconds = 10000, 1, 60
 UNIT_ESTIM["MovingHorizonEstimator"]["preparestate!"]["LinModel"]["Current form"] =
     @benchmarkable(
         preparestate!($mhe_lin_curr, $y, $d),
@@ -260,7 +260,7 @@ mhe_cstr_ipopt_pred = MovingHorizonEstimator(model; He, nint_u, σQint_u, optim,
 mhe_cstr_ipopt_pred = setconstraint!(mhe_cstr_ipopt_pred; v̂min, v̂max)
 JuMP.unset_time_limit_sec(mhe_cstr_ipopt_pred.optim)
 
-samples, evals = 5000, 1
+samples, evals = 10000, 1
 CASE_ESTIM["CSTR"]["MovingHorizonEstimator"]["OSQP"]["Current form"] =
     @benchmarkable(test_mhe($mhe_cstr_osqp_curr, $plant); 
         samples=samples, evals=evals
@@ -332,7 +332,7 @@ mhe_pendulum_madnlp_pred = setconstraint!(mhe_pendulum_madnlp_pred; v̂min, v̂m
 JuMP.unset_time_limit_sec(mhe_pendulum_madnlp_pred.optim)
 JuMP.set_attribute(mhe_pendulum_madnlp_pred.optim, "tol", 1e-7)
 
-samples, evals, seconds = 10, 1, 15*60
+samples, evals, seconds = 25, 1, 15*60
 CASE_ESTIM["Pendulum"]["MovingHorizonEstimator"]["Ipopt"]["Current form"] =
     @benchmarkable(
         sim!($mhe_pendulum_ipopt_curr, $N, $u; plant=$plant, x_0=$x_0, x̂_0=$x̂_0),

benchmark/3_bench_predictive_control.jl

@@ -12,7 +12,7 @@ linmpc_ms = LinMPC(
     Mwt=[1, 1], Nwt=[0.1, 0.1], Lwt=[0.1, 0.1], Hp=10
 )
 
-samples, evals, seconds = 5000, 1, 60
+samples, evals, seconds = 10000, 1, 60
 UNIT_MPC["LinMPC"]["moveinput!"]["SingleShooting"] = 
     @benchmarkable(
         moveinput!($linmpc_ss, $y, $d),
@@ -51,7 +51,7 @@ nmpc_nonlin_ms = NonLinMPC(
     Mwt=[1, 1], Nwt=[0.1, 0.1], Lwt=[0.1, 0.1], Hp=10    
 )
 
-samples, evals, seconds = 5000, 1, 60
+samples, evals, seconds = 10000, 1, 60
 UNIT_MPC["NonLinMPC"]["moveinput!"]["LinModel"]["SingleShooting"] =
     @benchmarkable(
         moveinput!($nmpc_lin_ss, $y, $d),
@@ -446,7 +446,7 @@ mpc3_ipopt_ms = LinMPC(kf; Hp, Hc, Mwt, Nwt, Cwt, optim, transcription)
 mpc3_ipopt_ms = setconstraint!(mpc3_ipopt_ms; umin, umax)
 JuMP.unset_time_limit_sec(mpc3_ipopt_ms.optim)
 
-samples, evals = 5000, 1
+samples, evals = 10000, 1
 CASE_MPC["Pendulum"]["LinMPC"]["Successive linearization"]["OSQP"]["SingleShooting"] = 
     @benchmarkable(
         sim2!($mpc3_osqp_ss, $model, $N, $ry, $plant, $x_0, $x̂_0, $y_step),