Index: mttroot/mtt/lib/control/PPP/ppp_optimise.m
==================================================================
--- mttroot/mtt/lib/control/PPP/ppp_optimise.m
+++ mttroot/mtt/lib/control/PPP/ppp_optimise.m
@@ -27,10 +27,13 @@
   ###############################################################
   ## Version control history
   ###############################################################
   ## $Id$
   ## $Log$
+  ## Revision 1.10  2002/05/13 16:01:09  gawthrop
+  ## Addes Q weighting matrix
+  ##
   ## Revision 1.9  2002/05/08 10:14:21  gawthrop
   ## Idetification now OK (Moved data range in ppp_optimise by one sample interval)
   ##
   ## Revision 1.8  2002/04/23 17:50:39  gawthrop
   ## error --> err to avoid name clash with built in function
@@ -124,20 +127,25 @@
 
     if (N_y!=n_y)
       mess = sprintf("n_y (%i) in data not same as n_y (%i) in model", n_y,N_y);
       error(mess);
     endif
+
+    if ( (N_data-n_data)<1 )
+      error(sprintf("y_0 (%i) must be shorter than y (%i)", n_data, N_data));
+    endif
     
     ## Use the last part of the simulation to compare with data
+    ## And shift back by one data point
     y = y(N_data-n_data:N_data-1,:);
     y_par = y_par(N_data-n_data:N_data-1,:);
 
     ##Evaluate error, cost derivative J and cost second derivative JJ
     err = 0; 
     J = zeros(n_th,1);
     JJ = zeros(n_th,n_th);
-    
+   
     for i = 1:n_y
       E = y(:,i) - y_0(:,i);	#  Error in ith output
       err = err + Q(i)*(E'*E);	# Sum the squared error over outputs
       y_par_i = y_par(:,i:n_y:n_y*n_th); # sensitivity function (ith output)
       J  = J + Q(i)*y_par_i'*E;	# Jacobian