Overview
Comment:ppp_int_obs now returns corrected as well as predicted output
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SHA3-256: 64167f57e7385ed5e4c5c4bb7a2084d883886323325619a45f47bfd4185ba87d
User & Date: gawthrop@users.sourceforge.net on 2003-10-16 07:30:24
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Context
2003-10-20
17:10:30
Added initial revision of ntt:
new transformation tools for using bond graphs with Matlab.
Copyright 2003 Dr. Dominic J. Diston.
check-in: dcfb465bef user: geraint@users.sourceforge.net tags: origin/master, trunk
2003-10-16
07:30:24
ppp_int_obs now returns corrected as well as predicted output check-in: 64167f57e7 user: gawthrop@users.sourceforge.net tags: origin/master, trunk
2003-10-15
16:21:20
Simulation and real now compatible! check-in: 265bc11f8e user: gawthrop@users.sourceforge.net tags: origin/master, trunk
Changes

Modified mttroot/mtt/lib/control/PPP/ppp_int_obs.m from [982a22072f] to [9bfdfe49cb].

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function [x_p,y_p,error] = ppp_int_obs (x,y,U,A,B,C,D,A_u,delta,L)
function [x_p,y_p,y_new,error] = ppp_int_obs (x,y,U,A,B,C,D,A_u,delta,L)

  ## usage: x_new = ppp_int_obs (x,y,U,A,B,C,D,A_u,delta,L)
  ##
  ## Intermittent observer for PPP
  ##
  ## x,y Current estimated state and measured output
  ## U PPP control weights
  ## A,B,C,D System matrices
  ## A_u PPP basis matrix
  ## delta time step
  ## L Observer gain
  ## x_p, y_p predicted estimated state and output
  ## y_new corrected estimated current output
  ## error corresponding error

  ## Copyright (C) 2003 by Peter J. Gawthrop

  ## Sanity check
  [n_x,n_u,n_y] = abcddim(A,B,C,D);

  if nargin<10
    L = zeros(n_x,n_y);
  endif
  
  ## Corrector (on current value of output)
  error = (C*x-y);
  x_new = x - L*error;
  y_new = C*x_new;

  ## Predictor (predicts Delta_OL ahead)
  [y_p,us,x_p] = ppp_ystar (A,B,C,D,x_new,A_u,U,delta);

endfunction

Modified mttroot/mtt/lib/control/PPP/ppp_lin_run.m from [66d5fae7bd] to [96369350d9].

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	t_i = ti(1);
      else			# The real thing
	[t_i,y_i,u_i] = ppp_put_get(U); # Generic interface to real-time
      endif

      ## Observer
      if strcmp(p_o.method, "intermittent")
	[x_est y_est e_est] = ppp_int_obs \
	[x_est y_est y_new, e_est] = ppp_int_obs \
	    (x_est,y_i,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 y_est y_new e_est] = ppp_int_obs \
	      (x_est,yi(:,k),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];
	  y_e = [y_e; y_new'];
	  e_e = [e_e; e_est'];
	endfor
      endif
      
      ##Control
      U = K_w*w - K_x*x_est;

      ## Save data
      if Simulate
	t = [t;ti'];
	y = [y;yi'];
	u = [u;ui'];
      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_est'];
	y_e = [y_e; y_new'];
	e_e = [e_e; e_est'];
	t_e = [t_e; t_i];
      endif

      delta_comp = time-tim;
      usleep(floor(1e6*(p_c.delta_ol-delta_comp-0.01)));
    endfor			# Main loop


MTT: Model Transformation Tools
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