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)
c.d1.create_bounds()
c.create_predictor()
c.predictor_step(c.d1, "real")
q_cov = {}
for j in range(1, ntrays + 1):
q_cov[("x", (j, ))] = 1e-05
q_cov[("M", (j, ))] = 1
c.make_noisy(q_cov)
for i in range(1, 1000):
c.solve_d(c.d1, stop_if_nopt=True, o_tee=True)
# Dot_sens
with open("debug1.txt", "w") as f:
c.d1.w_pnoisy.display(ostream=f)
c.randomize_noize(q_cov)
# c.solve_k_aug_nmpc()
# c.olnmpc.write_nl()
i = 1
k = 1
while k != 0:
if i == 1:
k = c.solve_d(c.olnmpc, max_cpu_time=60 * i)
else:
k = c.solve_d(c.olnmpc, max_cpu_time=60 * i, warm_start=True)
c.olnmpc.ipopt_zL_in.update(c.olnmpc.ipopt_zL_out)
c.olnmpc.ipopt_zU_in.update(c.olnmpc.ipopt_zU_out)
i += 1
c.initialize_olnmpc(c.d1)
c.olnmpc.display(filename="somefile1.txt")
c.solve_d(c.olnmpc, max_cpu_time=60 * 60)
c.update_u(src=c.olnmpc)
c.cycle_ics()
c.plant_input_gen(c.d1, src_kind="dict")
c.solve_d(c.d1)
c.update_state_real()
c.initialize_olnmpc(c.olnmpc, fe=5)
c.solve_d(c.olnmpc, max_cpu_time=60 * 60)
c.create_predictor()
c.predictor_step(c.d1)
c.update_state_predicted()
c.update_u(src=c.olnmpc)
c.update_soi_sp_nmpc()
# c.print_r_nmpc()