[62] | 1 | /* |
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| 2 | \file |
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| 3 | \brief Models for synchronous electric drive using IT++ and BDM |
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| 4 | \author Vaclav Smidl. |
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| 5 | |
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| 6 | ----------------------------------- |
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| 7 | BDM++ - C++ library for Bayesian Decision Making under Uncertainty |
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| 8 | |
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| 9 | Using IT++ for numerical operations |
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| 10 | ----------------------------------- |
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| 11 | */ |
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| 12 | |
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| 13 | #include <itpp/itbase.h> |
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| 14 | #include <estim/libKF.h> |
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| 15 | #include <estim/libPF.h> |
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| 16 | #include <stat/libFN.h> |
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| 17 | |
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| 18 | #include "pmsm.h" |
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| 19 | #include "simulator.h" |
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| 20 | |
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| 21 | #include "../simulator_zdenek/ekf_example/ekf_obj.h" |
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| 22 | #include "iopom.h" |
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| 23 | |
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| 24 | using namespace itpp; |
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| 25 | //!Extended Kalman filter with unknown \c Q |
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| 26 | |
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| 27 | void set_simulator_t(double &Ww) { |
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| 28 | |
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[63] | 29 | if (t>0.0002) x[8]=1.2; // 1A //0.2ZP |
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[62] | 30 | if (t>0.4) x[8]=10.8; // 9A |
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| 31 | if (t>0.6) x[8]=25.2; // 21A |
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| 32 | |
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| 33 | if (t>0.7) Ww=2.*M_PI*10.; |
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| 34 | if (t>1.0) x[8]=1.2; // 1A |
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| 35 | if (t>1.2) x[8]=10.8; // 9A |
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| 36 | if (t>1.4) x[8]=25.2; // 21A |
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| 37 | |
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| 38 | if (t>1.6) Ww=2.*M_PI*50.; |
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| 39 | if (t>1.9) x[8]=1.2; // 1A |
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| 40 | if (t>2.1) x[8]=10.8; // 9A |
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| 41 | if (t>2.3) x[8]=25.2; // 21A |
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| 42 | |
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| 43 | if (t>2.5) Ww=2.*M_PI*100; |
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| 44 | if (t>2.8) x[8]=1.2; // 1A |
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| 45 | if (t>3.0) x[8]=10.8; // 9A |
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| 46 | if (t>3.2) x[8]=25.2; // 21A |
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| 47 | |
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| 48 | if (t>3.4) Ww=2.*M_PI*150; |
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| 49 | if (t>3.7) x[8]=1.2; // 1A |
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| 50 | if (t>3.9) x[8]=10.8; // 9A |
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| 51 | if (t>4.1) x[8]=25.2; // 21A |
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| 52 | |
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| 53 | if (t>4.3) Ww=2.*M_PI*0; |
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| 54 | if (t>4.8) x[8]=-1.2; // 1A |
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| 55 | if (t>5.0) x[8]=-10.8; // 9A |
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| 56 | if (t>5.2) x[8]=-25.2; // 21A |
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| 57 | |
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| 58 | if (t>5.4) Ww=2.*M_PI*(-10.); |
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| 59 | if (t>5.7) x[8]=-1.2; // 1A |
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| 60 | if (t>5.9) x[8]=-10.8; // 9A |
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| 61 | if (t>6.1) x[8]=-25.2; // 21A |
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| 62 | |
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| 63 | if (t>6.3) Ww=2.*M_PI*(-50.); |
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| 64 | if (t>6.7) x[8]=-1.2; // 1A |
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| 65 | if (t>6.9) x[8]=-10.8; // 9A |
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| 66 | if (t>7.1) x[8]=-25.2; // 21A |
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| 67 | |
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| 68 | if (t>7.3) Ww=2.*M_PI*(-100.); |
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| 69 | if (t>7.7) x[8]=-1.2; // 1A |
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| 70 | if (t>7.9) x[8]=-10.8; // 9A |
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| 71 | if (t>8.1) x[8]=-25.2; // 21A |
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| 72 | if (t>8.3) x[8]=10.8; // 9A |
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| 73 | if (t>8.5) x[8]=25.2; // 21A |
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| 74 | |
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[63] | 75 | x[8]=0.0; |
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[62] | 76 | } |
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| 77 | |
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| 78 | int main() { |
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| 79 | // Kalman filter |
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| 80 | int Ndat = 90000; |
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| 81 | double h = 1e-6; |
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| 82 | int Nsimstep = 125; |
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[63] | 83 | int Npart = 100; |
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[62] | 84 | |
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| 85 | |
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| 86 | vec mu0= "0.0 0.0 0.0 0.0"; |
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[63] | 87 | vec Qdiag ( "0.05 0.05 0.002 0.001" ); //zdenek: 0.01 0.01 0.0001 0.0001 |
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[62] | 88 | vec Rdiag ( "0.05 0.05" ); //var(diff(xth)) = "0.034 0.034" |
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| 89 | chmat Q ( Qdiag ); |
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| 90 | chmat R ( Rdiag ); |
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| 91 | |
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| 92 | RV rQ ( "100","{Q}","4","0" ); |
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| 93 | EKFfixed KFE ( rx, rQ); |
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| 94 | KFE.init_ekf ( Nsimstep*h); |
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| 95 | |
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| 96 | |
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| 97 | ///////////// Particles |
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| 98 | mgamma_fix evolQ ( rQ,rQ ); |
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| 99 | MPF<EKFfixed> M ( rx,rQ,evolQ,evolQ,Npart,KFE ); |
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| 100 | // initialize |
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[63] | 101 | evolQ.set_parameters ( 10.0 ,Qdiag, 1.0); //sigma = 1/10 mu |
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[62] | 102 | evolQ.condition ( Qdiag ); //Zdenek default |
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| 103 | epdf& pfinit=evolQ._epdf(); |
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| 104 | M.set_est ( pfinit ); |
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[63] | 105 | evolQ.set_parameters ( 500000.0, Qdiag, 0.9999 ); |
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[62] | 106 | |
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| 107 | |
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| 108 | epdf& KFEep = KFE._epdf(); |
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| 109 | epdf& Mep = M._epdf(); |
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| 110 | |
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| 111 | |
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| 112 | mat Xt=zeros ( Ndat ,9 ); //true state from simulator |
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[63] | 113 | mat Dt=zeros ( Ndat,4 ); //observation |
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[62] | 114 | mat XtE=zeros ( Ndat, 4 ); |
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| 115 | mat XtM=zeros ( Ndat,4+4 ); //Q + x |
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| 116 | |
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| 117 | // SET SIMULATOR |
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| 118 | pmsmsim_set_parameters ( 0.28,0.003465,0.1989,0.0,4,1.5,0.04, 200., 3e-6, h ); |
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| 119 | double Ww=0.0; |
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[63] | 120 | static int k_rampa=1; |
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| 121 | static long k_rampa_tmp=0; |
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| 122 | |
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[62] | 123 | vec dt ( 2 ); |
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| 124 | vec ut ( 2 ); |
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| 125 | |
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| 126 | for ( int tK=1;tK<Ndat;tK++ ) { |
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| 127 | //Number of steps of a simulator for one step of Kalman |
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| 128 | for ( int ii=0; ii<Nsimstep;ii++ ) { |
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| 129 | //simulator |
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[63] | 130 | Ww+=k_rampa*2.*M_PI*2e-4; //1000Hz/s |
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| 131 | if ( Ww>2.*M_PI*150. ) { |
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| 132 | Ww=2.*M_PI*150.; |
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| 133 | if ( k_rampa_tmp<500000 ) k_rampa_tmp++; |
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| 134 | else {k_rampa=-1;k_rampa_tmp=0;} |
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| 135 | }; |
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| 136 | if ( Ww<-2.*M_PI*150. ) Ww=-2.*M_PI*150.; /* */ |
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| 137 | // set_simulator_t(Ww); |
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[62] | 138 | pmsmsim_step ( Ww ); |
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| 139 | }; |
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| 140 | // collect data |
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| 141 | ut ( 0 ) = KalmanObs[0]; |
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| 142 | ut ( 1 ) = KalmanObs[1]; |
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| 143 | dt ( 0 ) = KalmanObs[2]; |
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| 144 | dt ( 1 ) = KalmanObs[3]; |
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| 145 | //estimator |
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| 146 | KFE.bayes ( concat ( dt,ut ) ); |
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| 147 | M.bayes ( concat ( dt,ut ) ); |
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| 148 | |
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| 149 | Xt.set_row ( tK,vec ( x,9 ) ); //vec from C-array |
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[63] | 150 | Dt.set_row ( tK, concat ( dt,ut)); |
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[62] | 151 | XtE.set_row ( tK,KFEep.mean() ); |
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| 152 | XtM.set_row ( tK,Mep.mean() ); |
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| 153 | } |
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| 154 | |
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| 155 | char tmpstr[200]; |
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| 156 | sprintf(tmpstr,"%s/%s","herez/","format"); |
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| 157 | ofstream form(tmpstr); |
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| 158 | form << "# Experimetal header file"<< endl; |
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| 159 | dirfile_write(form,"herez/",Xt,"X","{isa isb om th }" ); |
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| 160 | dirfile_write ( form,"herez",XtM,"XtM","{q1 q2 q3 q4 isa isb om th }" ); |
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| 161 | dirfile_write ( form,"herez",XtE,"XE","{isa isb om th }" ); |
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| 162 | dirfile_write ( form,"herez",Dt,"Dt","{isa isb ua ub }" ); |
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| 163 | |
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| 164 | return 0; |
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| 165 | } |
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