Index: mttroot/mtt/lib/control/PPP/ppp_lin_run.m
==================================================================
--- mttroot/mtt/lib/control/PPP/ppp_lin_run.m
+++ mttroot/mtt/lib/control/PPP/ppp_lin_run.m
@@ -56,10 +56,14 @@
   endif
   
   if !struct_contains(p_c,"T")
     p_c.T = 10;			# Last time point.
   endif
+
+  if !struct_contains(p_c,"Iterations")
+    p_c.Iterations = 5;		# Number of interations, total =T*Iterations
+  endif
 
   if !struct_contains(p_c,"augment")
     p_c.augment = 0;		# Augment basis funs with constant
   endif
   
@@ -177,20 +181,20 @@
     t_max = 1/min(abs(cl_poles))
     t_min = 1/max(abs(cl_poles))
   endif
 
   ## Initial control U
-  U = zeros(p_c.n_U,1);	
+  U = zeros(p_c.n_U,1)	
 
 
   ## Short sample interval
   dt = p_c.delta_ol/p_c.N;
 
   ## Observer design
   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
+  Sigma = p_o.sigma*eye(n_y)	# Measurement noise variance
   
   if strcmp(p_o.method, "intermittent")
     Ad = expm(A*p_c.delta_ol);		# Discrete-time transition matrix
     if (ControlType==2)		# 
       [L, M, P, obs_poles] = dlqe(Ad,G,C,sigma_x,Sigma);
@@ -234,11 +238,12 @@
   y_e = [];
   t_e = [];
   e_e = [];
   tick = time;
   i=0;
-  for j=1:4
+
+  for j=1:p_c.Iterations
     for k=1:I
       tim=time;			# Timing
       i++;
       if Simulate		# Exact simulation 
 	t_sim = [1:p_c.N]*dt;	# Simulation time points
@@ -295,11 +300,10 @@
       else
 	t = [t;t_i];
 	y = [y;y_i'];
 	u = [u;u_i'];
       endif
-      
 
       if strcmp(p_o.method, "intermittent")
 	y_e = [y_e; y_new'];
 	e_e = [e_e; e_est'];
 	t_e = [t_e; t_i];