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    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
  ## Use double length to allow for overuns
  disp("Writing Ustar.h");
  overrun = 2;
  ppp_ustar2h(ppp_ustar (p_c.A_u, n_u, [0:dt:overrun*p_c.delta_ol], 0,0)); 









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    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
  
  if !struct_contains(p_o,"method")
    p_o.method = "continuous";
##    p_o.method = "intermittent";
  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("Control 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

  ## 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
  
  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);
    else
      L = zeros(n_x,n_y);
      obs_poles = eig(Ad);
    endif
  elseif strcmp(p_o.method, "continuous")
    Ad = expm(A*dt);		# Discrete-time transition matrix
    A_ud = expm(p_c.A_u*dt);	# Discrete-time input transition
    if (ControlType==2)		# 
      [L, M, P, obs_poles] = dlqe(Ad,G,C,sigma_x,Sigma);
    else
      L = zeros(n_x,n_y);
      obs_poles = eig(Ad);
    endif
  else
    error(sprintf("Observer method ""%s"" unknown", p_o.method));
  endif
  
  ## Display the poles
  obs_poles




  ## Write the include file for the real-time function
  ## Use double length to allow for overuns
  disp("Writing Ustar.h");
  overrun = 2;
  ppp_ustar2h(ppp_ustar (p_c.A_u, n_u, [0:dt:overrun*p_c.delta_ol], 0,0)); 


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      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];
    sample_time = (time-tim)/p_c.N
    dt
  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));








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      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
    if strcmp(p_o.method, "intermittent")
      [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);
    elseif strcmp(p_o.method, "continuous")
      Ui = U;			# U at sub intervals
       for k = 1:p_c.N
      [x_est y_est e_est] = ppp_int_obs \
	  (x_est,yi(:,k+1),Ui,A,B,C,D,p_c.A_u,dt,L);
      Ui = A_ud*Ui;
      y_e = [y_e; y_est'];
      e_e = [e_e; e_est];
      endfor
    endif
    
    ##Control
    ##U = K_w*w - K_x*x_est;
    U = expm(p_c.A_u*(p_c.delta_ol))*U
    ## 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)'];
    sample_time = (time-tim)/p_c.N

    if strcmp(p_o.method, "intermittent")
      y_e = [y_e; y_est'];
      e_e = [e_e; e_est];
      t_e = [t_e; (i*p_c.N)*dt];
    endif
    

    dt
  endfor			# Main loop

  if strcmp(p_o.method, "continuous")
    t_e = t;
  endif
  
  
  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));


MTT: Model Transformation Tools
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