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()