root/pmsm/pmsmDS.h @ 278

/*!
  \file
  \brief DataSource for experiments with realistic simulator of the PMSM model
  \author Vaclav Smidl.

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

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

#include <stat/loggers.h>
#include "simulator.h"
#include "pmsm.h"

//! Simulator of PMSM machine with predefined profile on omega
class pmsmDS : public DS {

protected:
        //! indeces of logged variables
        int L_x, L_ou, L_oy, L_iu, L_optu;
        //! Setpoints of omega in timespans given by dt_prof
        vec profileWw;
        //! time-step for profiles
        double dt_prof;
        //! Number of miliseconds per discrete time step
        int Dt;
        //! options for logging, string in which each character has a meaning:
        //! \c u - log predictions of 'true' voltage
        string opt;
public:
        //! Constructor with fixed sampling period
        pmsmDS (string opt0="" ) : Dt ( 125 ), opt(opt0) {}
        void set_parameters ( double Rs0, double Ls0, double Fmag0, double Bf0, double p0, double kp0, double J0, double Uc0, double DT0, double dt0 ) {
                pmsmsim_set_parameters ( Rs0, Ls0, Fmag0, Bf0, p0, kp0, J0, Uc0, DT0, dt0 );
        }
        void getdata ( vec &dt ) {dt=vec ( KalmanObs,6 );}
        void write ( vec &ut ) {}

        void step() {
                static int ind=0;
                static double dW; // increase of W
                static double Ww; // W
                if ( t>=dt_prof*ind ) {
                        ind++;
                        if ( ind<profileWw.length() ) {
                                //linear increase
                                if ( profileWw.length() ==1 ) {
                                        Ww=profileWw ( 0 ); dW=0.0;}
                                else {
                                        dW = profileWw ( ind )-profileWw ( ind-1 );
                                        dW *=125e-6/dt_prof;
                                }
                        }
                        else {
                                dW = 0;
                        }
                }
                Ww += dW;
                //Simulate Dt seconds!
                for ( int i=0;i<Dt;i++ ) {      pmsmsim_step ( Ww );}
        };

        void log_add ( logger &L ) {
                L_x = L.add ( rx, "x" );
                L_oy = L.add ( ry, "obs" );
                L_ou = L.add ( ru, "obs" );
                L_iu = L.add ( ru, "true" );
                // log differences
                if (opt.find("u")==string::npos){
                        L_optu = L.add(ru, "model");
                }
        }

        void logit ( logger &L ) {
                L.logit ( L_x, vec ( x,4 )      );
                L.logit ( L_oy, vec_2 ( KalmanObs[2],KalmanObs[3] ) );
                L.logit ( L_ou, vec_2 ( KalmanObs[0],KalmanObs[1] ) );
                L.logit ( L_iu, vec_2 ( KalmanObs[4],KalmanObs[5] ) );
                if (opt.find("u")==string::npos){
                        double sq3=sqrt(3.0);
                        double ua,ub;
                        double i1=x[0];
                        double i2=0.5*(-i1+sq3*x[1]);
                        double i3=0.5*(-i1-sq3*x[1]);
                        double u1=KalmanObs[0];
                        double u2=0.5*(-u1+sq3*KalmanObs[1]);
                        double u3=0.5*(-u1-sq3*KalmanObs[1]);
                        
                        double du1=0.7*(double(i1>0.1) - double(i1<-0.1))+0.05*i1;
                        double du2=0.7*(double(i2>0.1) - double(i2<-0.1))+0.05*i2;
                        double du3=0.7*(double(i3>0.1) - double(i3<-0.1))+0.05*i3;
                        ua = (2.0*(u1-du1)-(u2-du2)-(u3-du3))/3.0;
                        ub = ((u2-du2)-(u3-du3))/sq3;
                        L.logit( L_optu , vec_2 (ua,ub));
                }
                }

        void set_profile ( double dt, const vec &Ww ) {dt_prof=dt; profileWw=Ww;}
};