root/pmsm/sim_var_arx.cpp @ 170

/*!
  \file
  \brief Models for synchronous electric drive using IT++ and BDM
  \author Vaclav Smidl.

  -----------------------------------
  BDM++ - C++ library for Bayesian Decision Making under Uncertainty

  Using IT++ for numerical operations
  -----------------------------------
*/

#include <itpp/itbase.h>
#include <estim/arx.h>

#include <stat/loggers.h>

using namespace itpp;

vec getPsi_a ( int t, mat &D, mat &Du , mat &X );
vec getPsi_b ( int t, mat &D, mat &Du , mat &X );

int main() {
        // Kalman filter
        int Ndat = 90000;
        mat D;
        mat Du;
        mat X;

        dirfilelog L ( "exp/sim_var_arx",1000 );

        it_file itf ( "sim_var.it" );
        itf >> Name ( "D" ) >> D;
        itf >> Name ( "Du" ) >> Du;
        itf >> Name ( "X" ) >> X;

        Array<std::string> Names = "{ia ib om dom r }";
        int rglen = Names.length();
        //Regressor
        RV rgr ( Names );
        mat V0 = 0.0001*eye ( rglen ); V0 ( 0,0 ) =200;
        double nu0 = rglen+1;

        //Autoregressive model
        ARX Ar_a ( rgr,V0,nu0 ,0.95 );
        ARX Ar_b ( rgr,V0,nu0 ,0.95 );
        const epdf& pA= Ar_a._epdf();
        const epdf& pB= Ar_b._epdf();

        RV rta ( "{th_a }",vec_1 ( rglen ) );
        RV rtb ( "{th_b }",vec_1 ( rglen ) );
        int tha_log = L.add ( rta,"" );
        int thb_log = L.add ( rtb,"" );
        L.init();

        vec Psi ( rglen );
        vec Save ( 13 );
        for ( int t=2; t<Ndat; t++ ) {
                Psi =getPsi_a ( t, D,Du ,X );
                Ar_a.bayes ( Psi );
                Psi =getPsi_b ( t, D,Du ,X );
                Ar_b.bayes ( Psi );

                Save = pA.mean();
                L.logit ( tha_log, Save );
                Save = pB.mean();
                L.logit ( thb_log, Save );
                L.step();
        }
        L.finalize();

        ivec bestind = Ar_a.structure_est ( egiw ( rgr,V0,nu0 ) );
        ivec bestind2 = Ar_b.structure_est ( egiw ( rgr,V0,nu0 ) );
        cout << bestind <<endl;
        cout << bestind2 <<endl;

        return 0;
}

vec getPsi_a ( int t, mat &D, mat &Du, mat &X ) {
        vec Psi ( 5 );
        Psi ( 0 ) = D ( t,0 )-Du ( t,0 ); // a=0

        Psi ( 1 ) = D ( t,2 );
        Psi ( 2 ) = D(t,2)-D(t-1,2 );
        Psi ( 3 ) = D(t,0)-D(t-1,0 );
        Psi ( 4 ) = X ( t,2 ) - X ( t-1,2 );

        return Psi;
}

vec getPsi_b ( int t, mat &D, mat &Du, mat &X ) {
        vec Psi ( 5 );
        Psi ( 0 ) = D ( t,1 )-Du ( t,1 ); //b=1

        Psi ( 1 ) = D(t,3);
        Psi ( 2 ) = D(t,3)-D(t-1,3 );
        Psi ( 3 ) = D ( t,1 )-D(t-1,1);
        Psi ( 4 ) = X ( t,2 ) - X ( t-1,2 );

        return Psi;
}