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## Names
s_system_name = sprintf("s%s", system_name);
## System details -- defines simulation within ol interval
par = eval(sprintf("%s_numpar;", system_name));
simpar = eval(sprintf("%s_simpar;", system_name))
x_0 = eval(sprintf("%s_state(par);", system_name))
simpar = eval(sprintf("%s_simpar;", system_name));
x_0 = eval(sprintf("%s_state(par);", system_name));
[n_x,n_y,n_u] = eval(sprintf("%s_def;", system_name));
## Sensitivity system details -- defines moving horizon simulation
simpars = eval(sprintf("%s_simpar;", s_system_name))
simpars = eval(sprintf("%s_simpar;", s_system_name));
sympars = eval(sprintf("%s_sympar;", s_system_name));
pars = eval(sprintf("%s_numpar;", s_system_name));
## Times
## -- within opt horizon
n_Tau = round(simpars.last/simpars.dt)
dtau = simpars.dt
n_Tau = round(simpars.last/simpars.dt);
dtau = simpars.dt;
Tau = [0:n_Tau-1]'*dtau;
[n_tau,n_w] = size(w_s);
tau = Tau(n_Tau-n_tau+1:n_Tau);
w = w_s(length(w_s)); # Final value of setpoint
## -- within ol interval
n_t = round(simpar.last/simpar.dt)
n_t = round(simpar.last/simpar.dt);
dt = simpar.dt;
t_ol = [0:n_t-1]'*dt;
T_ol = n_t*dt;
## Weight and moving-horizon setpoint
# weight = [zeros(n_y,n_Tau-n_tau), ones(n_y,n_tau)];
# w_s = w*ones(n_tau,1);
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pars(i_ppp(:,1)) = U; # Put final value of U into the parameter vector
else
Error = [];
endif
opt_time = time-tick;
printf("Optimisation %i took %i iterations and %2.2f sec\n", i, \
length(Error), opt_time);
##title(sprintf("Moving horizon trajectories: Interval %i",i));
##grid;
##plot(tau,Y)
## (Assumes that first gain parameter is one)
##U = [u_ol zeros(n_t,n_u-1)]; # Generate the vector input
[y_ol,y_s,x_ol] = eval(sprintf("%s_ssim(x_0s, pars, simpar, u_star_t);", s_system_name));
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