"T": [(i, ) for i in range(1, ntrays + 1)],
"Mv": [(i, ) for i in range(2, ntrays)],
"Mv1": [((), )],
"Mvn": [((), )]
}
x_vars = {
"x": [(i, ) for i in range(1, ntrays + 1)],
"M": [(i, ) for i in range(1, ntrays + 1)]
}
nfet = 10
tfe = [i for i in range(1, nfet + 1)]
c = NmpcGen(d_mod=DistDiehlNegrete,
u=u,
states=states,
ref_state=ref_state,
u_bounds=u_bounds)
c.load_iguess_ss()
c.solve_ss()
c.load_d_s(c.d1)
c.solve_d(c.d1)
c.update_state_real() # update the current state
c.find_target_ss()
c.create_nmpc()
c.update_targets_nmpc()
c.compute_QR_nmpc(n=-1)
c.new_weights_olnmpc(10000, 1e+06)
from pyomo.environ import *
from nmpc_mhe.dync.NMPCGen import NmpcGen
from nmpc_mhe.mods.bfb.bfb_abs7momdt_nmpc import bfb_dae
from snap_shot import snap
from pyomo.core.base import value
states = [
"Ngb", "Hgb", "Ngc", "Hgc", "Nsc", "Hsc", "Nge", "Hge", "Nse", "Hse", "mom"
]
u = ["u1"]
u_bounds = {"u1": (162.183495794 * 0.5, 162.183495794 * 1.6)}
ref_state = {("c_capture", ((), )): 0.52}
c = NmpcGen(d_mod=bfb_dae,
u=u,
states=states,
ref_state=ref_state,
u_bounds=u_bounds)
c.ss.dref = snap
c.load_iguess_ss()
c.solve_ss()
c.load_d_s(c.d1)
c.solve_d(c.d1)
c.update_state_real() # update the current state
c.find_target_ss()
c.create_nmpc()
c.update_targets_nmpc()
c.compute_QR_nmpc(n=-1)
c.new_weights_olnmpc(1000, 1e+06)
from nmpc_mhe.dync.NMPCGen import NmpcGen
from nmpc_mhe.mods.bfb.bfb_abs7momdt_ht2 import bfb_dae
from snap_shot import snap
import sys
from numpy.random import normal as npm
from pyutilib.common._exceptions import ApplicationError
states = [
"Ngb", "Hgb", "Ngc", "Hgc", "Nsc", "Hsc", "Nge", "Hge", "Nse", "Hse", "mom"
]
u = ["u1"]
u_bounds = {"u1": (162.183495794 * 0.0005, 162.183495794 * 10000)}
ref_state = {("c_capture", ((), )): 0.63}
c = NmpcGen(d_mod=bfb_dae,
u=u,
states=states,
ref_state=ref_state,
u_bounds=u_bounds,
nfe_t=5,
_t=100)
c.ss.dref = snap
c.load_iguess_ss()
# sys.exit()
# c.ss.lydot.display()
# sys.exit()
c.solve_ss()
c.solve_d(c.ss)
c.ss.write_nl()
# sys.exit()
c.load_d_s(c.d1)