function [y,u,t,y_e,t_e,e_e] = ppp_lin_run (Name,Simulate,ControlType,w,x_0,p_c,p_o)
## usage: [y,u,t,y_e,t_e,e_e] = ppp_lin_run (Name,Simulate,ControlType,w,x_0,p_c,p_o);
##
##
## Linear closed-loop PPP of lego system (and simulation)
##
## Name: Name of system (in mtt terms)
## Simulate = 0: real thing
## Simulate = 1: simulate
## Control = 0: step test
## Control = 1: PPP open-loop
## Control = 2: PPP closed-loop
## w is the (constant) setpoint
## par_control and par_observer are structures containing parameters
## for the observer and controller
##Defaults
if nargin<1 # Default name to dir name
names = split(pwd,"/");
[n_name,m_name] = size(names);
Name = deblank(names(n_name,:));
endif
## System
sys = mtt2sys(Name); # Create system
[A,B,C,D] = sys2ss(sys); # SS form
[n_x, n_u, n_y] = abcddim(A,B,C,D); # Dimensions
if nargin<2
Simulate = 1;
endif
if nargin<3
ControlType = 2;
endif
if nargin<4
w = ones(n_y,1);;
endif
if nargin<5
x_0 = zeros(n_x,1);
endif
if nargin<6
p_c.N = 5;
endif
if nargin<7
p_o.sigma = 1e-1;
endif
if !struct_contains(p_c,"delta_ol")
p_c.delta_ol = 0.5; # OL sample interval
endif
if !struct_contains(p_c,"T")
p_c.T = 5.0; # Last time point.
endif
if !struct_contains(p_c,"Method")
p_c.Method = "lq";
endif
if struct_contains(p_c,"Method")
if strcmp(p_c.Method,"lq")
p_c.Q = eye(n_y);
p_c.R = (0.5^2)*eye(n_u);
p_c.N_u = n_x;
elseif strcmp(p_c.Method,"original");
if !struct_contains(p_c,"A_w")
p_c.A_w = 0;
endif
if !struct_contains(p_c,"A_u")
p_c.N_u = n_x;
a_u = 1.0;
p_c.A_u = laguerre_matrix(p_c.N_u,a_u)
endif
else
error(sprintf("Method %s not recognised", p_c.Method));
endif
endif
if !struct_contains(p_o,"x_0")
p_o.x_0 = zeros(n_x,1);
endif
## Check w.
[n_w,m_w] = size(w);
if ( (n_w<>n_y) || (m_w<>1) )
error(sprintf("ppp_lin_run: w must a column vector with %i elements",n_y));
endif
## Initialise
x_est = p_o.x_0;
## Initilise simulation state
x = x_0;
if ControlType==0 # Step input
I = 1; # 1 large sample
p_c.delta_ol = p_c.T # I
K_w = zeros(p_c.N_u,n_y);
K_w(1,1) = 1;
K_w(2,1) = -1;
K_x = zeros(p_c.N_u,n_x);
U = K_w*w; # Initial control U
else
I = ceil(p_c.T/p_c.delta_ol) # Number of large samples
if strcmp(p_c.Method, "original")
tau = [10:0.1:11]*(2/a_u); # Time horizons
[k_x,k_w,K_x,K_w] = ppp_lin(A,B,C,D,p_c.A_u,p_c.A_w,tau); # Design
elseif strcmp(p_c.Method, "lq") # LQ design
tau = [0:0.001:1.0]*5; # Time horizons
[k_x,k_w,K_x,K_w,Us0,J_uu,J_ux,J_uw,J_xx,J_xw,J_ww,y_u,p_c.A_u] \
= ppp_lin_quad (A,B,C,D,tau,p_c.Q,p_c.R);
else
error(sprintf("Method %s not recognised", p_c.Method));
endif
##Sanity check A_u
[p_c.N_u,M_u] = size(p_c.A_u);
if (p_c.N_u<>M_u)
error("A_u must be square");
endif
U = K_w*w; # Initial control U
## Checks
[ol_zeros, ol_poles] = sys2zp(sys)
cl_poles = eig(A - B*k_x)
endif
## Observer design
Ad = expm(A*p_c.delta_ol); # Discrete-time transition matrix
if (ControlType==2) #
G = eye(n_x); # State noise gain
sigma_x = eye(n_x); # State noise variance
Sigma = p_o.sigma*eye(n_y); # Measurement noise variance
[L, M, P, obs_poles] = dlqe(Ad,G,C,sigma_x,Sigma);
else
L = zeros(n_x,n_y);
obs_poles = eig(Ad);
endif
## Display the poles
obs_poles
## Short sample interval
dt = p_c.delta_ol/p_c.N;
## Write the include file for the real-time function
disp("Writing Ustar.h");
ppp_ustar2h(ppp_ustar (p_c.A_u, n_u, [0:dt:p_c.delta_ol], 0,0));
## Control loop
y = [];
u = [];
t = [];
y_e = [];
t_e = [];
e_e = [];
tick = time;
for i=1:I
i
if Simulate # Exact simulation
t_sim = [0:p_c.N]*dt; # Simulation time points
[yi,ui,xsi] = ppp_ystar(A,B,C,D,x,p_c.A_u,U,t_sim); # Simulate
x = xsi(:,p_c.N+1); # Current state
y_now = yi(:,p_c.N+1); # Current output
else # The real thing
to_rt(U'); # Send U
data = from_rt(p_c.N); # Receive data
[yi,ui] = convert_data(data); # And convert from integer format
y_now = yi(:,p_c.N); # Current output
endif
## Observer
[x_est y_est e_est] = ppp_int_obs (x_est,y_now,U,A,B,C,D,p_c.A_u,p_c.delta_ol,L);
##Control
U = K_w*w - K_x*x_est;
## Save data
ti = [(i-1)*p_c.N:i*p_c.N-1]*dt;
t = [t;ti'];
y = [y;yi(:,1:p_c.N)'];
u = [u;ui(:,1:p_c.N)'];
y_e = [y_e; y_est'];
t_e = [t_e; (i*p_c.N)*dt];
e_e = [e_e; e_est];
endfor # Main loop
sample_interval = (time-tick)/(I*p_c.N)
## Put data on file (so can use for identification)
filename = sprintf("%s_ident_data.dat",Name);
eval(sprintf("save -ascii %s t y u",filename));
## Plot
gset nokey
title("");
boxed=0;
monochrome=1;
grid;
xlabel("t");
ylabel("y");
figure(1);plot(t,y, t_e,y_e,"+");
ylabel("u");
figure(2);plot(t,u);
ylabel("e");
figure(3);plot(t_e,e_e);
endfunction