Changeset 723 for applications/dual

Timestamp:

11/15/09 23:02:02 (15 years ago)

Author:

smidl

Message:

Big commit of LQG stuff

Location:

applications/dual

Files:

• experiment/itermc.m (modified) (1 diff)
• src/arx1_ctrl.h (modified) (3 diffs)
• src/iterativemc.cpp (modified) (4 diffs)

applications/dual/experiment/itermc.m

@@ -25 +25 @@
     c.controller = C1;
     Mmc=iterativemc(c);
-    losses(i) = sum((Mmc.y-yr*ones(size(Mmc.y))).^2);
+    losses(i) = sum((Mmc.S_y-yr*ones(size(Mmc.S_y))).^2);
     
     c.controller = C2;
     Mmc=iterativemc(c);
-    losses2(i) = sum((Mmc.y-yr*ones(size(Mmc.y))).^2);
+    looo= sum((Mmc.S_y-yr*ones(size(Mmc.S_y))).^2)
+%     keyboard
+    losses2(i) = looo;
 end
 [min(losses) median(losses) max(losses)]

applications/dual/src/arx1_ctrl.h

@@ -21 +21 @@
                 void set_b (const double b0){b=b0;}
                 //! data in ctrlaction are only past outputs yt
-                vec ctrlaction(const vec &yt){
+                vec ctrlaction(const vec &yt)const{
                         vec ut(1);
                         if (abs(b)<1e-2) {
@@ -63 +63 @@
         public:
                 //! expected input is yt
-                virtual void adapt(const vec &yt){
+                virtual void adapt(const vec &dt){
                         //prepare data for ARX
-                        Psi(0) = yt(0)-ytm;
-                        Psi(1) = utm;
                         // do estimation
-                        est.bayes(Psi);
+                        est.bayes(vec_1(dt(0)-ytm),vec_1(dt(1)));
+                        ytm = dt(0);
                         // save estimate b = E(b);
                         b = est.posterior().mean()(0); // first
                 }
                 //! same as exact control, but stores ut as utm
-                vec ctrlaction(const vec &yt){
-                        vec ut=exact_ctrl::ctrlaction(yt);
+                vec ctrlaction(const vec &dt)const{
+                        vec ut(1);
+                        mat P = est.posterior().variance();
+                        ut(0) =(yr - dt(0))/(b + (b<0 ? P(0,0) : -P(0,0)));;
                         // remember last ut for estimation
-                        utm=ut(0);
-                        ytm=yt(0);
                         return ut;
                 }
@@ -92 +91 @@
                         V0(1,0) = b0;
                         V0(0,1) = b0;
-                        V0(1,1) = P0;
+                        V0(1,1) = P0/6;
                         
-                        est.set_statistics(1,V0);
+                        est.set_statistics(1,V0,6);
                         est.set_constant(false);
+                        est.validate();
                         validate();
                 }
                 void validate(){
                         Psi = zeros(2);
-                        LIDs = zeros_i(1);
                 }
-                virtual void log_add ( logger &L, const string &name = "" ) {
-                        LIDs ( 0 ) = L.add ( RV("bhat",1) );
+                void log_register( logger& L, const string& prefix ){
+                        est.set_log_level(1);
+                        est.log_register(L,"");
+                };
+                void log_write() const{
+                        est.log_write();
                 }
-                virtual void logit ( logger &L ) {
-                        L.logit ( LIDs ( 0 ), b );
-                }
-                
 };
 UIREGISTER(ce_ctrl);

applications/dual/src/iterativemc.cpp

@@ -47 +47 @@
         double b;
         double sigma;
-        double ytm;
+        double ytm=0.0;
         double yr;
         int Ndat;
@@ -91 +91 @@
         RV y("y",1); // name random variable
         RV u("u",1); // name random variable
-        int L_yt=L->add(y);
-        int L_ut=L->add(u);
-        C->log_add(*L);
+        int L_yt=L->add(y,"S");
+        int L_ut=L->add(u,"S");
+        C->log_register(*L,"C");
         L->init();
         
         vec psi(2);       // regressor
-        double ut;        // input
+        double ut=0.0;        // input
         vec yt;
         
@@ -103 +103 @@
                 //yt has now meaning of yt-1
                 //design controller
-                C->adapt(vec_1(ytm));
-                ut = C->ctrlaction(vec_1(ytm))(0);   // the best controller there is
+                C->adapt(vec_2(ytm,ut));
+                ut = C->ctrlaction(vec_2(ytm,ut))(0);   // the best controller there is
                 
                 //prepare regressor
@@ -116 +116 @@
                 L->logit(L_yt, yt);
                 L->logit(L_ut, vec_1(ut));
-                C->logit(*L);
+                C->log_write();
                 L->step();
         }