Overview
Comment:Made output of U and parameters consistent.
Downloads: Tarball | ZIP archive
Timelines: family | ancestors | descendants | both | origin/master | trunk
Files: files | file ages | folders
SHA3-256: 6c8bf9597f13aacb92755337679748a64c60cb5790a124d8471983564f36b3e9
User & Date: gawthrop@users.sourceforge.net on 2002-05-23 17:27:06.000
Other Links: branch diff | manifest | tags
Context
2002-05-24
11:04:10
Removed unnecessary message about *.log file not existing when -D option is used. check-in: 16d5375ac8 user: geraint@users.sourceforge.net tags: origin/master, trunk
2002-05-23
17:27:06
Made output of U and parameters consistent. check-in: 6c8bf9597f user: gawthrop@users.sourceforge.net tags: origin/master, trunk
17:26:07
Cosmetic tweaks to graphs check-in: 4d5e314d90 user: gawthrop@users.sourceforge.net tags: origin/master, trunk
Changes
Side-by-Side Diff Ignore Whitespace Patch
Modified mttroot/mtt/lib/control/PPP/ppp_nlin_run.m from [df20d4cf0c] to [76fba90674].
︙
56
57
58
59
60
61
62
63

64
65
66
67
68
69
70
71
72


73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106



107
108
109
110
111
112
113

56
57
58
59
60
61
62

63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91

92
93

94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116








-
+









+
+

















-


-













+
+
+








  simpar_model = simpar;	# Initial internal model simulation params
  simpar_pred = simpar;		# Initial prediction simulation params
  T_ol_0 = simpar.last;		# The initial specified interval
  n_t = round(simpar.last/simpar.dt); # Corresponding length
  x_0 = eval(sprintf("%s_state(par);", system_name));
  x_0_model = x_0;
  [n_x,n_y,n_u] = eval(sprintf("%s_def;", system_name));

  [n_par,m_par] = size(i_par);
  if nargin<8
    Q = ones(n_y,1);
  endif
 
  ## Sensitivity system details -- defines moving horizon simulation
  simpars = eval(sprintf("%s_simpar;", s_system_name));
  pars = eval(sprintf("%s_numpar;", s_system_name));
  x_0s = eval(sprintf("%s_state(pars);", s_system_name));
  x_0_models = x_0s;

  p = []; # Initialise saved parameters

  ## Times
  ## -- within opt horizon
  n_Tau = round(simpars.last/simpars.dt);
  dtau = simpars.dt;
  Tau = [0:n_Tau-1]'*dtau;
  [n_tau,n_w] = size(w_s);
  tau = Tau(n_Tau-n_tau+1:n_Tau);
  w = w_s(n_tau,:);		# Final value of setpoint


  ## Main simulation loop
  y = [];
  x = [];
  u = [];
  t = [];

  p = [];

  t_last = 0;
  UU = [];
  UU_l =[];
  UU_c =[];
  
  t_ppp = [];
  t_est = [];
  its_ppp = [];
  its_est = [];
  t_open = [];
  x_nexts = zeros(2*n_x,1);

  ## Initial U is zero
  [n_U,junk] = size(A_u);
  U = zeros(n_U,1);

  ## Initialise saved U
  UU = [];

  ## Create input basis functions
  u_star_tau = ppp_ustar(A_u,1,Tau',0,0,n_u-n_U);
	
  ## Reverse time to get "previous" U
  U_old = U;
︙
121
122
123
124
125
126
127








128
129
130
131
132
133
134

124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145








+
+
+
+
+
+
+
+








    A_u_sim = A_u;
    simpar_sim = simpar;
    T_total = simpar.last;
  endif
  
  for i = 0:N_ol		# Main loop 
    printf("%i",i);
    UU = [UU; U'];		# Save control U
    
    if n_par>0
      par_est = pars(i_par(:,1));
      p = [p; par_est'];		# Save up the estimated parameters
    endif
    

    if (extras.simulate==1)
      [y_ol,u_ol] = ppp_RT_sim(U); # Simulate
    else
      [y_ol,u_ol] = ppp_RT(U);	# Real thing
    endif

    t_start = time;		# Initialise time
︙
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159

154
155
156
157
158
159
160



161
162
163
164
165
166
167








-
-
-








      t_open = [t_open;T_ol];

      ## Generate input to actual system
      u_star_t = ppp_ustar(A_u,1,t_ol',0,0,n_u-n_U);

      ## Tune parameters/states
      if (estimating_parameters==1)
	## Save up the estimated parameters
	par_est = pars(i_par(:,1));
	p = [p; par_est'];

	## Set up according to interval length
	if (T_ol>T_ol_0) ## Truncate data
	  simpar_est.last = T_ol_0;
	  y_est = y_ol(1:n_t+1,:);
	else
	  simpar_est.last = T_ol;
︙
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255

249
250
251
252
253
254
255

256
257
258
259
260
261
262








-









      pars(i_ppp(:,1)) = U;	# Put final value of U into the parameter vector

      ## Save up data
      y_ol = y_ol(1:n_ol,:);
      y = [y; y_ol];
      u = [u; u_ol];
      UU = [UU; U'];
      t = [t; t_ol+t_last*ones(n_ol,1) ];
      t_last = t_last + T_ol;

    endif


    if (extras.simulate==1) # Do the actual simulation
︙
MTT: Model Transformation Tools
[ GitHub | SourceHut | Sourceforge | Fossil RSS ]