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function [y,u,t,p,UU,t_open,t_ppp,t_est,its_ppp,its_est] = ppp_nlin_run (system_name,i_ppp,i_par,A_u,w_s,N_ol,extras)
function [y,u,t,p,UU,t_open,t_ppp,t_est,its_ppp,its_est] = ppp_nlin_run(system_name,i_ppp,i_par,A_u,w_s,N_ol,Q,extras)
## usage: [y,u,t,p,U,t_open,t_ppp,t_est,its_ppp,its_est] =
## ppp_nlin_run (system_name,i_ppp,i_par,A_u,w_s,N_ol[,extras])
##
## y,u,t System output, input and corresponding time p
## Estimated parameters U PPP weight vector t_open The
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## Real-time implementatipn of nonlinear PPP Copyright (C) 2001,2002
## by Peter J. Gawthrop
## Globals to pass details to simulation
global system_name_sim i_ppp_sim x_0_sim y_sim u_sim A_u_sim simpar_sim
## Defaults
if nargin<7
if nargin<8
extras.alpha = 0.1;
extras.criterion = 1e-5;
extras.emulate_timing = 0;
extras.max_iterations = 10;
extras.simulate = 1;
extras.v = 1e-5;
extras.verbose = 0;
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simpar_pred = simpar; # Initial prediction simulation params
T_ol_0 = simpar.last; # The initial specified interval
n_t = round(simpar.last/simpar.dt); # Corresponding length
x_0 = eval(sprintf("%s_state(par);", system_name));
x_0_model = x_0;
[n_x,n_y,n_u] = eval(sprintf("%s_def;", system_name));
if nargin<8
Q = ones(n_y,1);
endif
## Sensitivity system details -- defines moving horizon simulation
simpars = eval(sprintf("%s_simpar;", s_system_name));
pars = eval(sprintf("%s_numpar;", s_system_name));
x_0s = eval(sprintf("%s_state(pars);", s_system_name));
x_0_models = x_0s;
## Times
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## Optimise
tick = time;
[pars,Par,Error,Y,its] = \
ppp_optimise(s_system_name,x_0_models,pars,simpar_est,u_star_t,y_est,i_par,extras);
if extras.visual
figure(2);
figure(11);
title("Parameter optimisation");
II = [1:length(y_est)]; plot(II,y_est,"*", II,Y);
endif
est_time = time-tick;
t_est = [t_est;est_time];
its_est = [its_est; its-1];
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x_next = x_next(n_t+1,:)'; # Initial state for next time
x_nexts(1:2:(2*n_x)-1) = x_next; # And for internal sensitivity model
## Optimize for next interval
U_old = U; # Save previous value
U = expm(A_u*T_ol)*U; # Initialise from continuation trajectory
pars(i_ppp(:,1)) = U; # Put initial value of U into the parameter vector
[U, U_all, Error, Y, its] = ppp_nlin(system_name,x_nexts,pars,simpars,u_star_tau,w_s,i_ppp,extras);
[U, U_all, Error, Y, its] = ppp_nlin(system_name,x_nexts,pars,simpars,u_star_tau,w_s,i_ppp,Q,extras);
if extras.visual
figure(3);
figure(12);
title("PPP optimisation");
II = [1:length(w_s)]; plot(II,w_s,"*", II,Y);
figure(1);
endif
ppp_time = time-tick;
t_ppp = [t_ppp;ppp_time];
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