function [k_x,k_w,K_x,K_w,Us0,J_uu,J_ux,J_uw,J_xx,J_xw,J_ww,y_u,cond_uu] = ppp_lin(A,B,C,D,A_u,A_w,tau,Q,R,P,max_cond);
  ## usage:
  ## usage:   [k_x,k_w,K_x,K_w,Us0,J_uu,J_ux,J_uw,J_xx,J_xw,J_ww,y_u,cond_uu] = ppp_lin(A,B,C,D,A_u,A_w,tau,Q,R,P,max_cond)
  ## [k_x,k_w,K_x,K_w,Us0,J_uu,J_ux,J_uw,J_xx,J_xw,J_ww,y_u,cond_uu] =
  ##  ppp_lin(A,B,C,D,A_u,A_w,tau,Q,R,P,max_cond)

  ##
  ## Linear PPP (Predictive pole-placement) computation 
  ## INPUTS:
  ## A,B,C,D: system matrices
  ## A_u: composite system matrix for U* generation 
  ##      one square matrix (A_ui) row for each system input
  ##      each A_ui generates U*' for ith system input.
  ## OR
  ## A_u: square system matrix for U* generation 
  ##      same square matrix for each system input.
  ## A_w: composite system matrix for W* generation 
  ##      one square matrix (A_wi) row for each system output
  ##      each A_wi generates W*' for ith system output.
  ## t: row vector of times for optimisation (equispaced in time)
  ## tau: row vector of times for optimisation (equispaced in time)
  ## Q column vector of output weights (defaults to unity)
  ## OR
  ## Q matrix,  each row corresponds to time-varying weight compatible with t
  ## max_cond: Maximum condition number of J_uu (def 1/eps)
  ## OUTPUTS:
  ## k_x: State feedback gain
  ## k_w: setpoint gain
  ## ie u(t) = k_w w(t) - k_x x(t)
  ## K_x, K_w: open loop gains
  ## Us0: Value of U* at tau=0
  ## J_uu, J_ux, J_uw, J_xx,J_xw,J_ww: cost derivatives
  ## cond_uu : Condition number of J_uu
  ## Copyright (C) 1999, 2000 by Peter J. Gawthrop
  ## 	$Id$	

  ## Check some dimensions
  [n_x,n_u,n_y] = abcddim(A,B,C,D);
  if (n_x==-1)
    return
  endif

  
  ## Default Q (output weight)
  if nargin<8
    Q = ones(n_y,1);
  endif

  ## Default R (input weight)
  if nargin<9