| 1 | /*! |
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| 2 | \file |
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| 3 | \brief DataSource for experiments with realistic simulator of the PMSM model |
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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 <base/loggers.h> |
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| 14 | #include <estim/kalman.h> |
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| 15 | #include "simulator_zdenek/simulator.h" |
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| 16 | #include "pmsm.h" |
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| 17 | |
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| 18 | using namespace bdm; |
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| 19 | |
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| 20 | //! Simulator of PMSM machine with predefined profile on omega |
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| 21 | class pmsmDS : public DS |
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| 22 | { |
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| 23 | |
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| 24 | protected: |
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| 25 | //! indeces of logged variables |
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| 26 | int L_x, L_ou, L_oy, L_iu, L_optu; |
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| 27 | //! Setpoints of omega in timespans given by dt_prof |
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| 28 | vec profileWw; |
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| 29 | //! Setpoints of Mz in timespans given by dt_prof |
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| 30 | vec profileMz; |
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| 31 | //! time-step for profiles |
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| 32 | double dt_prof; |
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| 33 | //! Number of miliseconds per discrete time step |
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| 34 | int Dt; |
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| 35 | //! options for logging, - log predictions of 'true' voltage |
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| 36 | bool opt_modu; |
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| 37 | //! options for logging, - |
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| 38 | public: |
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| 39 | //! Constructor with fixed sampling period |
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| 40 | pmsmDS () : DS() |
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| 41 | { |
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| 42 | Dt=125; |
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| 43 | Yrv=RV ( "{o_ua o_ub o_ia o_ib t_ua t_ub o_om o_th Mz }" ); |
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| 44 | ytsize = Yrv._dsize(); |
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| 45 | Drv = Yrv; |
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| 46 | } |
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| 47 | void set_parameters ( double Rs0, double Ls0, double Fmag0, double Bf0, double p0, double kp0, double J0, double Uc0, double DT0, double dt0 ) |
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| 48 | { |
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| 49 | pmsmsim_set_parameters ( Rs0, Ls0, Fmag0, Bf0, p0, kp0, J0, Uc0, DT0, dt0 ); |
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| 50 | } |
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| 51 | //! parse options: "modelu" => opt_modu=true; |
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| 52 | void set_options ( string &opt ) |
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| 53 | { |
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| 54 | opt_modu = ( opt.find ( "modelu" ) !=string::npos ); |
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| 55 | } |
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| 56 | void getdata ( vec &dt ) const |
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| 57 | { |
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| 58 | dt.set_subvector(0,vec ( KalmanObs,6 )); |
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| 59 | dt(6)=x[2]; |
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| 60 | dt(7)=x[3]; |
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| 61 | dt(8)=x[8]; |
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| 62 | } |
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| 63 | void write ( vec &ut ) {} |
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| 64 | |
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| 65 | void step() |
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| 66 | { |
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| 67 | static int ind=0; |
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| 68 | static double dW; // increase of W |
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| 69 | static double Ww; // W |
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| 70 | static double Mz; // W |
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| 71 | if ( t>=dt_prof*ind ) |
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| 72 | { |
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| 73 | ind++; |
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| 74 | // check omega profile and set dW |
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| 75 | if ( ind <2 && profileWw.length() ==1 ) |
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| 76 | { |
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| 77 | Ww=profileWw ( 0 ); |
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| 78 | dW=0.0; |
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| 79 | } |
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| 80 | if ( ind<profileWw.length() ) |
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| 81 | { |
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| 82 | dW = profileWw ( ind )-profileWw ( ind-1 ); |
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| 83 | dW *=125e-6/dt_prof; |
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| 84 | } |
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| 85 | else |
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| 86 | { |
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| 87 | dW = 0; |
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| 88 | } |
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| 89 | // Check Mz profile and set Mz |
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| 90 | if ( ind<profileMz.length() ) |
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| 91 | { |
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| 92 | //sudden increase |
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| 93 | Mz = profileMz(ind); |
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| 94 | } |
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| 95 | else |
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| 96 | { |
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| 97 | Mz = 0; |
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| 98 | } |
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| 99 | } |
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| 100 | Ww += dW; |
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| 101 | //Simulate Dt seconds! |
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| 102 | for ( int i=0; i<Dt; i++ ) |
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| 103 | { |
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| 104 | pmsmsim_step ( Ww , Mz); |
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| 105 | } |
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| 106 | // for ( int i=0;i<Dt;i++ ) { pmsmsim_noreg_step ( Ww , Mz);} |
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| 107 | |
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| 108 | //discretization |
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| 109 | double ustep=1.2; |
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| 110 | KalmanObs [ 0 ] = ustep*itpp::round( KalmanObs [ 0 ]/ ustep) ; |
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| 111 | KalmanObs [ 1 ] = ustep*itpp::round(KalmanObs [ 1 ]/ ustep); |
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| 112 | double istep=0.085; |
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| 113 | KalmanObs [ 2 ] = istep*itpp::round( KalmanObs [ 2 ]/ istep) ; |
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| 114 | KalmanObs [ 3 ] = istep*itpp::round(KalmanObs [ 3 ]/ istep); |
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| 115 | |
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| 116 | }; |
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| 117 | |
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| 118 | void log_register ( logger &L ) |
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| 119 | { |
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| 120 | L_x = L.add ( rx, "x" ); |
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| 121 | L_oy = L.add ( ry, "o" ); |
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| 122 | L_ou = L.add ( ru, "o" ); |
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| 123 | L_iu = L.add ( ru, "t" ); |
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| 124 | // log differences |
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| 125 | if ( opt_modu ) |
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| 126 | { |
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| 127 | L_optu = L.add ( ru, "model" ); |
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| 128 | } |
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| 129 | } |
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| 130 | |
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| 131 | void log_write ( logger &L ) |
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| 132 | { |
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| 133 | L.logit ( L_x, vec ( x,4 ) ); |
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| 134 | L.logit ( L_oy, vec_2 ( KalmanObs[2],KalmanObs[3] ) ); |
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| 135 | L.logit ( L_ou, vec_2 ( KalmanObs[0],KalmanObs[1] ) ); |
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| 136 | L.logit ( L_iu, vec_2 ( KalmanObs[4],KalmanObs[5] ) ); |
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| 137 | if ( opt_modu ) |
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| 138 | { |
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| 139 | double sq3=sqrt ( 3.0 ); |
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| 140 | double ua,ub; |
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| 141 | double i1=x[0]; |
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| 142 | double i2=0.5* ( -i1+sq3*x[1] ); |
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| 143 | double i3=0.5* ( -i1-sq3*x[1] ); |
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| 144 | double u1=KalmanObs[0]; |
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| 145 | double u2=0.5* ( -u1+sq3*KalmanObs[1] ); |
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| 146 | double u3=0.5* ( -u1-sq3*KalmanObs[1] ); |
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| 147 | |
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| 148 | double du1=1.4* ( double ( i1>0.3 ) - double ( i1<-0.3 ) ) +0.2*i1; |
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| 149 | double du2=1.4* ( double ( i2>0.3 ) - double ( i2<-0.3 ) ) +0.2*i2; |
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| 150 | double du3=1.4* ( double ( i3>0.3 ) - double ( i3<-0.3 ) ) +0.2*i3; |
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| 151 | ua = ( 2.0* ( u1-du1 )- ( u2-du2 )- ( u3-du3 ) ) /3.0; |
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| 152 | ub = ( ( u2-du2 )- ( u3-du3 ) ) /sq3; |
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| 153 | L.logit ( L_optu , vec_2 ( ua,ub ) ); |
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| 154 | } |
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| 155 | |
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| 156 | } |
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| 157 | |
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| 158 | void set_profile ( double dt, const vec &Ww, const vec &Mz ) |
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| 159 | { |
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| 160 | dt_prof=dt; |
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| 161 | profileWw=Ww; |
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| 162 | profileMz=Mz; |
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| 163 | } |
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| 164 | |
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| 165 | void from_setting( const Setting &root ) |
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| 166 | { |
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| 167 | const SettingResolver& params_l(root["params"]); |
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| 168 | const Setting ¶ms = params_l.result; |
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| 169 | set_parameters ( params["Rs"], params["Ls"], params["Fmag"], \ |
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| 170 | params["Bf"], params["p"], params["kp"], \ |
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| 171 | params["J"], params["Uc"], params["DT"], 1.0e-6 ); |
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| 172 | |
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| 173 | // Default values of profiles for omega and Mz |
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| 174 | vec profW=vec("1.0"); |
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| 175 | vec profM=vec("0.0"); |
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| 176 | double tstep=1.0; |
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| 177 | root.lookupValue( "tstep", tstep ); |
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| 178 | UI::get( profW, root, "profileW" ); |
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| 179 | UI::get( profM, root, "profileM" ); |
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| 180 | set_profile (tstep , profW, profM); |
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| 181 | |
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| 182 | string opts; |
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| 183 | if ( root.lookupValue( "options", opts ) ) |
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| 184 | set_options(opts); |
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| 185 | } |
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| 186 | |
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| 187 | // TODO dodelat void to_setting( Setting &root ) const; |
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| 188 | }; |
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| 189 | |
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| 190 | UIREGISTER ( pmsmDS ); |
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| 191 | |
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| 192 | |
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| 193 | //! This class behaves like BM but it is evaluating EKF |
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| 194 | class pmsmCRB : public EKFfull |
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| 195 | { |
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| 196 | protected: |
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| 197 | vec interr; |
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| 198 | vec old_true; |
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| 199 | vec secder; |
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| 200 | int L_CRB; |
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| 201 | int L_err; |
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| 202 | int L_sec; |
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| 203 | public: |
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| 204 | //! constructor |
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| 205 | pmsmCRB():EKFfull() |
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| 206 | { |
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| 207 | old_true=zeros(6); |
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| 208 | } |
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| 209 | |
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| 210 | void bayes(const vec &dt) |
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| 211 | { |
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| 212 | static vec umin(2); |
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| 213 | vec u(2); |
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| 214 | vec &mu = est._mu(); |
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| 215 | //assume we know state exactly: |
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| 216 | vec true_state=vec(x,4); // read from pmsm |
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| 217 | mu=true_state; |
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| 218 | |
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| 219 | //integration error |
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| 220 | old_true(4)=KalmanObs[4]; |
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| 221 | old_true(5)=KalmanObs[5];// add U |
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| 222 | u(0) = KalmanObs[0]; // use the required value for derivatives |
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| 223 | u(1) = KalmanObs[1]; |
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| 224 | interr = (true_state - pfxu->eval(old_true)); |
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| 225 | |
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| 226 | //second derivative |
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| 227 | IMpmsm2o* pf = dynamic_cast<IMpmsm2o*>(pfxu.get()); |
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| 228 | if (pf) |
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| 229 | { |
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| 230 | secder=pf->eval2o(u-umin); |
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| 231 | } |
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| 232 | |
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| 233 | umin =u; |
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| 234 | EKFfull::bayes(dt); |
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| 235 | old_true.set_subvector(0,true_state); |
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| 236 | } |
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| 237 | |
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| 238 | void log_add(logger &L, const string &name="" ) |
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| 239 | { |
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| 240 | L_CRB=L.add(rx,"crb"); |
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| 241 | L_err=L.add(rx,"err"); |
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| 242 | L_sec=L.add(rx,"d2"); |
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| 243 | } |
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| 244 | void logit(logger &L) |
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| 245 | { |
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| 246 | L.logit(L_err, interr); |
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| 247 | L.logit(L_CRB,diag(_R())); |
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| 248 | L.logit(L_sec,secder); |
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| 249 | } |
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| 250 | |
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| 251 | void from_setting( const Setting &root ) |
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| 252 | { |
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| 253 | shared_ptr<diffbifn> IM = UI::build<diffbifn>(root, "IM"); |
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| 254 | shared_ptr<diffbifn> OM = UI::build<diffbifn>(root, "OM"); |
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| 255 | |
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| 256 | //parameters |
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| 257 | |
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| 258 | //statistics |
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| 259 | int dim=IM->dimension(); |
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| 260 | |
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| 261 | vec mu0; |
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| 262 | if(root.exists("mu0")) |
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| 263 | UI::get( mu0, root, "mu0"); |
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| 264 | else |
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| 265 | mu0=zeros(dim); |
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| 266 | |
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| 267 | mat P0; |
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| 268 | if(root.exists( "dP0" )) |
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| 269 | { |
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| 270 | vec dP0; |
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| 271 | UI::get(dP0,root, "dP0"); |
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| 272 | P0=diag(dP0); |
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| 273 | } |
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| 274 | else if (root.exists("P0")) |
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| 275 | UI::get(P0,root, "P0"); |
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| 276 | else |
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| 277 | P0=eye(dim); |
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| 278 | |
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| 279 | set_statistics(mu0,P0); |
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| 280 | |
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| 281 | vec dQ; |
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| 282 | UI::get( dQ, root, "dQ"); |
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| 283 | vec dR; |
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| 284 | UI::get( dR, root, "dR"); |
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| 285 | set_parameters(IM, OM, diag(dQ) , diag(dR)); |
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| 286 | |
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| 287 | //connect |
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| 288 | shared_ptr<RV> drv = UI::build<RV>(root, "drv"); |
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| 289 | set_yrv(*drv); |
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| 290 | shared_ptr<RV> rv = UI::build<RV>(root, "rv"); |
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| 291 | set_rv(*rv); |
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| 292 | } |
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| 293 | |
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| 294 | // TODO dodelat void to_setting( Setting &root ) const; |
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| 295 | }; |
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| 296 | |
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| 297 | UIREGISTER ( pmsmCRB ); |
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| 298 | |
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| 299 | |
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| 300 | //! This class behaves like BM but it is evaluating EKF |
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| 301 | class pmsmCRBMz : public EKFfull |
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| 302 | { |
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| 303 | protected: |
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| 304 | int L_CRB; |
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| 305 | public: |
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| 306 | //! constructor |
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| 307 | pmsmCRBMz():EKFfull() {} |
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| 308 | |
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| 309 | void bayes(const vec &dt) |
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| 310 | { |
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| 311 | //assume we know state exactly: |
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| 312 | vec true_state(5); |
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| 313 | true_state.set_subvector(0,vec(x,4)); // read from pmsm |
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| 314 | true_state(4)=x[8]; |
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| 315 | |
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| 316 | vec &mu = est._mu(); |
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| 317 | mu = true_state; |
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| 318 | //hack for ut |
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| 319 | EKFfull::bayes(dt); |
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| 320 | } |
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| 321 | |
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| 322 | void log_add(logger &L, const string &name="" ) |
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| 323 | { |
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| 324 | L_CRB=L.add(concat(rx,RV("Mz",1,0)),"crbz"); |
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| 325 | } |
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| 326 | void logit(logger &L) |
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| 327 | { |
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| 328 | L.logit(L_CRB,diag(_R())); |
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| 329 | } |
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| 330 | |
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| 331 | void from_setting( const Setting &root ) |
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| 332 | { |
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| 333 | shared_ptr<diffbifn> IM = UI::build<diffbifn>(root,"IM"); |
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| 334 | shared_ptr<diffbifn> OM = UI::build<diffbifn>(root,"OM"); |
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| 335 | |
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| 336 | //statistics |
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| 337 | int dim=IM->dimension(); |
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| 338 | vec mu0; |
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| 339 | if( root.exists( "mu0")) |
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| 340 | UI::get(mu0, root, "mu0"); |
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| 341 | else |
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| 342 | mu0=zeros(dim); |
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| 343 | |
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| 344 | mat P0; |
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| 345 | |
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| 346 | if(root.exists("dP0")) |
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| 347 | { |
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| 348 | vec dP0; |
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| 349 | UI::get(dP0, root, "dP0"); |
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| 350 | P0=diag(dP0); |
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| 351 | } |
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| 352 | else if(root.exists("P0")) |
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| 353 | UI::get( P0, root, "P0" ); |
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| 354 | else |
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| 355 | P0=eye(dim); |
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| 356 | |
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| 357 | set_statistics(mu0,P0); |
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| 358 | |
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| 359 | vec dQ; |
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| 360 | UI::get(dQ, root, "dQ"); |
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| 361 | vec dR; |
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| 362 | UI::get(dR, root, "dR"); |
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| 363 | set_parameters(IM, OM, diag(dQ), diag(dR)); |
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| 364 | |
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| 365 | //connect |
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| 366 | shared_ptr<RV> drv = UI::build<RV>(root, "drv"); |
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| 367 | set_yrv(*drv); |
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| 368 | shared_ptr<RV> rv = UI::build<RV>(root, "rv"); |
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| 369 | set_rv(*rv); |
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| 370 | } |
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| 371 | |
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| 372 | // TODO dodelat void to_setting( Setting &root ) const; |
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| 373 | }; |
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| 374 | |
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| 375 | UIREGISTER ( pmsmCRBMz ); |
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