[258] | 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 <stat/loggers.h> |
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[384] | 14 | #include <estim/kalman.h> |
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[349] | 15 | #include "simulator_zdenek/simulator.h" |
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[258] | 16 | #include "pmsm.h" |
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| 17 | |
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[366] | 18 | using namespace bdm; |
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| 19 | |
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[258] | 20 | //! Simulator of PMSM machine with predefined profile on omega |
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[357] | 21 | class pmsmDS : public DS |
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| 22 | { |
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[258] | 23 | |
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| 24 | protected: |
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[357] | 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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[258] | 38 | public: |
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[357] | 39 | //! Constructor with fixed sampling period |
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| 40 | pmsmDS () |
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| 41 | { |
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| 42 | Dt=125; |
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| 43 | Drv=RV ( "{o_ua o_ub o_ia o_ib t_ua t_ub o_om o_th Mz }" ); |
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| 44 | } |
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| 45 | 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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| 46 | { |
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| 47 | pmsmsim_set_parameters ( Rs0, Ls0, Fmag0, Bf0, p0, kp0, J0, Uc0, DT0, dt0 ); |
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| 48 | } |
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| 49 | //! parse options: "modelu" => opt_modu=true; |
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| 50 | void set_options ( string &opt ) |
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| 51 | { |
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| 52 | opt_modu = ( opt.find ( "modelu" ) !=string::npos ); |
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| 53 | } |
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| 54 | void getdata ( vec &dt ) |
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| 55 | { |
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| 56 | dt.set_subvector(0,vec ( KalmanObs,6 )); |
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| 57 | dt(6)=x[2]; |
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| 58 | dt(7)=x[3]; |
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| 59 | dt(8)=x[8]; |
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| 60 | } |
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| 61 | void write ( vec &ut ) {} |
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[258] | 62 | |
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[357] | 63 | void step() |
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| 64 | { |
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| 65 | static int ind=0; |
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| 66 | static double dW; // increase of W |
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| 67 | static double Ww; // W |
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| 68 | static double Mz; // W |
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| 69 | if ( t>=dt_prof*ind ) |
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| 70 | { |
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| 71 | ind++; |
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| 72 | // check omega profile and set dW |
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| 73 | if ( ind<profileWw.length() ) |
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| 74 | { |
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| 75 | //linear increase |
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| 76 | if ( profileWw.length() ==1 ) |
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| 77 | { |
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| 78 | Ww=profileWw ( 0 ); |
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| 79 | dW=0.0; |
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| 80 | } |
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| 81 | else |
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| 82 | { |
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| 83 | dW = profileWw ( ind )-profileWw ( ind-1 ); |
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| 84 | dW *=125e-6/dt_prof; |
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| 85 | } |
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| 86 | } |
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| 87 | else |
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| 88 | { |
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| 89 | dW = 0; |
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| 90 | } |
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| 91 | // Check Mz profile and set Mz |
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| 92 | if ( ind<profileMz.length() ) |
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| 93 | { |
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| 94 | //sudden increase |
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| 95 | Mz = profileMz(ind); |
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| 96 | } |
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| 97 | else |
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| 98 | { |
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| 99 | Mz = 0; |
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| 100 | } |
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| 101 | } |
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| 102 | Ww += dW; |
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| 103 | //Simulate Dt seconds! |
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| 104 | for ( int i=0; i<Dt; i++ ) |
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| 105 | { |
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| 106 | pmsmsim_step ( Ww , Mz); |
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| 107 | } |
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[326] | 108 | // for ( int i=0;i<Dt;i++ ) { pmsmsim_noreg_step ( Ww , Mz);} |
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[332] | 109 | |
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[357] | 110 | //discretization |
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| 111 | double ustep=1.2; |
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| 112 | KalmanObs [ 0 ] = ustep*itpp::round( KalmanObs [ 0 ]/ ustep) ; |
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| 113 | KalmanObs [ 1 ] = ustep*itpp::round(KalmanObs [ 1 ]/ ustep); |
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| 114 | double istep=0.085; |
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| 115 | KalmanObs [ 2 ] = istep*itpp::round( KalmanObs [ 2 ]/ istep) ; |
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| 116 | KalmanObs [ 3 ] = istep*itpp::round(KalmanObs [ 3 ]/ istep); |
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[258] | 117 | |
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[357] | 118 | }; |
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[258] | 119 | |
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[357] | 120 | void log_add ( logger &L ) |
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| 121 | { |
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| 122 | L_x = L.add ( rx, "x" ); |
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| 123 | L_oy = L.add ( ry, "o" ); |
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| 124 | L_ou = L.add ( ru, "o" ); |
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| 125 | L_iu = L.add ( ru, "t" ); |
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| 126 | // log differences |
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| 127 | if ( opt_modu ) |
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| 128 | { |
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| 129 | L_optu = L.add ( ru, "model" ); |
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| 130 | } |
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| 131 | } |
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[280] | 132 | |
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[357] | 133 | void logit ( logger &L ) |
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| 134 | { |
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| 135 | L.logit ( L_x, vec ( x,4 ) ); |
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| 136 | L.logit ( L_oy, vec_2 ( KalmanObs[2],KalmanObs[3] ) ); |
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| 137 | L.logit ( L_ou, vec_2 ( KalmanObs[0],KalmanObs[1] ) ); |
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| 138 | L.logit ( L_iu, vec_2 ( KalmanObs[4],KalmanObs[5] ) ); |
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| 139 | if ( opt_modu ) |
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| 140 | { |
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| 141 | double sq3=sqrt ( 3.0 ); |
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| 142 | double ua,ub; |
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| 143 | double i1=x[0]; |
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| 144 | double i2=0.5* ( -i1+sq3*x[1] ); |
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| 145 | double i3=0.5* ( -i1-sq3*x[1] ); |
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| 146 | double u1=KalmanObs[0]; |
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| 147 | double u2=0.5* ( -u1+sq3*KalmanObs[1] ); |
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| 148 | double u3=0.5* ( -u1-sq3*KalmanObs[1] ); |
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[258] | 149 | |
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[357] | 150 | double du1=1.4* ( double ( i1>0.3 ) - double ( i1<-0.3 ) ) +0.2*i1; |
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| 151 | double du2=1.4* ( double ( i2>0.3 ) - double ( i2<-0.3 ) ) +0.2*i2; |
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| 152 | double du3=1.4* ( double ( i3>0.3 ) - double ( i3<-0.3 ) ) +0.2*i3; |
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| 153 | ua = ( 2.0* ( u1-du1 )- ( u2-du2 )- ( u3-du3 ) ) /3.0; |
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| 154 | ub = ( ( u2-du2 )- ( u3-du3 ) ) /sq3; |
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| 155 | L.logit ( L_optu , vec_2 ( ua,ub ) ); |
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| 156 | } |
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| 157 | |
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| 158 | } |
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| 159 | |
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| 160 | void set_profile ( double dt, const vec &Ww, const vec &Mz ) |
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| 161 | { |
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| 162 | dt_prof=dt; |
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| 163 | profileWw=Ww; |
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| 164 | profileMz=Mz; |
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| 165 | } |
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| 166 | |
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| 167 | void from_setting( const Setting &root ) |
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| 168 | { |
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[377] | 169 | UI::SettingResolver params_exp(root["params"]); |
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| 170 | const Setting& params=params_exp.result; |
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[357] | 171 | |
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[366] | 172 | set_parameters ( params["Rs"], params["Ls"], params["Fmag"], \ |
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| 173 | params["Bf"], params["p"], params["kp"], \ |
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| 174 | params["J"], params["Uc"], params["DT"], 1.0e-6 ); |
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| 175 | |
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[357] | 176 | // Default values of profiles for omega and Mz |
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| 177 | vec profW=vec("1.0"); |
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| 178 | vec profM=vec("0.0"); |
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| 179 | double tstep=1.0; |
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| 180 | root.lookupValue( "tstep", tstep ); |
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| 181 | UI::get( profW, root, "profileW" ); |
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| 182 | UI::get( profM, root, "profileM" ); |
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| 183 | set_profile (tstep , profW, profM); |
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| 184 | |
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| 185 | string opts; |
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| 186 | if ( root.lookupValue( "options", opts ) ) |
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| 187 | set_options(opts); |
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| 188 | } |
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| 189 | |
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| 190 | // TODO dodelat void to_setting( Setting &root ) const; |
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[258] | 191 | }; |
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[318] | 192 | |
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[357] | 193 | UIREGISTER ( pmsmDS ); |
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| 194 | |
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| 195 | |
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[318] | 196 | //! This class behaves like BM but it is evaluating EKF |
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[357] | 197 | class pmsmCRB : public EKFfull |
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| 198 | { |
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| 199 | protected: |
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| 200 | vec interr; |
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| 201 | vec old_true; |
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| 202 | vec secder; |
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| 203 | int L_CRB; |
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| 204 | int L_err; |
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| 205 | int L_sec; |
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| 206 | public: |
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| 207 | //! constructor |
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| 208 | pmsmCRB():EKFfull() |
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| 209 | { |
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| 210 | old_true=zeros(6); |
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| 211 | } |
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[318] | 212 | |
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[357] | 213 | void bayes(const vec &dt) |
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| 214 | { |
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| 215 | static vec umin(2); |
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| 216 | vec u(2); |
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| 217 | //assume we know state exactly: |
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| 218 | vec true_state=vec(x,4); // read from pmsm |
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| 219 | E.set_mu(true_state); |
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| 220 | mu=true_state; |
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| 221 | |
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| 222 | //integration error |
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| 223 | old_true(4)=KalmanObs[4]; |
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| 224 | old_true(5)=KalmanObs[5];// add U |
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| 225 | u(0) = KalmanObs[0]; // use the required value for derivatives |
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| 226 | u(1) = KalmanObs[1]; |
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| 227 | interr = (true_state - pfxu->eval(old_true)); |
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| 228 | |
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| 229 | //second derivative |
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| 230 | IMpmsm2o* pf = dynamic_cast<IMpmsm2o*>(pfxu); |
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| 231 | if (pf) |
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| 232 | { |
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| 233 | secder=pf->eval2o(u-umin); |
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| 234 | } |
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| 235 | |
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| 236 | umin =u; |
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| 237 | EKFfull::bayes(dt); |
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| 238 | old_true.set_subvector(0,true_state); |
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| 239 | } |
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| 240 | |
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| 241 | void log_add(logger &L, const string &name="" ) |
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| 242 | { |
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| 243 | L_CRB=L.add(rx,"crb"); |
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| 244 | L_err=L.add(rx,"err"); |
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| 245 | L_sec=L.add(rx,"d2"); |
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| 246 | } |
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| 247 | void logit(logger &L) |
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| 248 | { |
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| 249 | L.logit(L_err, interr); |
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| 250 | L.logit(L_CRB,diag(_R())); |
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| 251 | L.logit(L_sec,secder); |
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| 252 | } |
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| 253 | |
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| 254 | void from_setting( const Setting &root ) |
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| 255 | { |
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| 256 | diffbifn* IM = UI::build<diffbifn>(root, "IM"); |
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| 257 | diffbifn* OM = UI::build<diffbifn>(root, "OM"); |
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| 258 | |
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| 259 | //parameters |
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| 260 | |
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| 261 | //statistics |
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| 262 | int dim=IM->dimension(); |
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[359] | 263 | |
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[357] | 264 | vec mu0; |
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[359] | 265 | if(root.exists("mu0")) |
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| 266 | UI::get( mu0, root, "mu0"); |
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| 267 | else |
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[357] | 268 | mu0=zeros(dim); |
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[359] | 269 | |
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[357] | 270 | mat P0; |
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[359] | 271 | if(root.exists( "dP0" )) |
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| 272 | { |
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| 273 | vec dP0; |
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| 274 | UI::get(dP0,root, "dP0"); |
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[357] | 275 | P0=diag(dP0); |
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[359] | 276 | } |
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| 277 | else if (root.exists("P0")) |
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| 278 | UI::get(P0,root, "P0"); |
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| 279 | else |
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[357] | 280 | P0=eye(dim); |
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| 281 | |
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| 282 | set_statistics(mu0,P0); |
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| 283 | |
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| 284 | vec dQ; |
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| 285 | UI::get( dQ, root, "dQ"); |
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| 286 | vec dR; |
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| 287 | UI::get( dR, root, "dR"); |
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| 288 | set_parameters(IM, OM, diag(dQ) , diag(dR)); |
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| 289 | |
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| 290 | //connect |
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| 291 | RV* drv = UI::build<RV>(root, "drv"); |
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| 292 | set_drv(*drv); |
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| 293 | RV* rv = UI::build<RV>(root, "rv"); |
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| 294 | set_rv(*rv); |
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| 295 | } |
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| 296 | |
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| 297 | // TODO dodelat void to_setting( Setting &root ) const; |
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[332] | 298 | }; |
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[342] | 299 | |
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[357] | 300 | UIREGISTER ( pmsmCRB ); |
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| 301 | |
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| 302 | |
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[342] | 303 | //! This class behaves like BM but it is evaluating EKF |
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[357] | 304 | class pmsmCRBMz : public EKFfull |
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| 305 | { |
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| 306 | protected: |
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| 307 | int L_CRB; |
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| 308 | public: |
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| 309 | //! constructor |
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| 310 | pmsmCRBMz():EKFfull() {} |
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[342] | 311 | |
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[357] | 312 | void bayes(const vec &dt) |
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| 313 | { |
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[342] | 314 | //assume we know state exactly: |
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[357] | 315 | vec true_state(5); |
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| 316 | true_state.set_subvector(0,vec(x,4)); // read from pmsm |
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| 317 | true_state(4)=x[8]; |
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| 318 | |
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| 319 | E.set_mu(true_state); |
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| 320 | mu = true_state; |
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| 321 | //hack for ut |
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| 322 | EKFfull::bayes(dt); |
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| 323 | } |
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| 324 | |
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| 325 | void log_add(logger &L, const string &name="" ) |
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| 326 | { |
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| 327 | L_CRB=L.add(concat(rx,RV("Mz",1,0)),"crbz"); |
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| 328 | } |
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| 329 | void logit(logger &L) |
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| 330 | { |
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| 331 | L.logit(L_CRB,diag(_R())); |
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| 332 | } |
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| 333 | |
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| 334 | void from_setting( const Setting &root ) |
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| 335 | { |
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| 336 | diffbifn* IM = UI::build<diffbifn>(root,"IM"); |
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| 337 | diffbifn* OM = UI::build<diffbifn>(root,"OM"); |
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| 338 | |
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| 339 | //statistics |
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| 340 | int dim=IM->dimension(); |
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| 341 | vec mu0; |
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[359] | 342 | if( root.exists( "mu0")) |
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| 343 | UI::get(mu0, root, "mu0"); |
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| 344 | else |
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[357] | 345 | mu0=zeros(dim); |
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| 346 | |
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[359] | 347 | mat P0; |
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| 348 | |
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| 349 | if(root.exists("dP0")) |
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| 350 | { |
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| 351 | vec dP0; |
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| 352 | UI::get(dP0, root, "dP0"); |
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| 353 | P0=diag(dP0); |
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| 354 | } |
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| 355 | else if(root.exists("P0")) |
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| 356 | UI::get( P0, root, "P0" ); |
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| 357 | else |
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| 358 | P0=eye(dim); |
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| 359 | |
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[357] | 360 | set_statistics(mu0,P0); |
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| 361 | |
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| 362 | vec dQ; |
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| 363 | UI::get(dQ, root, "dQ"); |
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| 364 | vec dR; |
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| 365 | UI::get(dR, root, "dR"); |
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| 366 | set_parameters(IM, OM, diag(dQ), diag(dR)); |
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| 367 | |
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| 368 | //connect |
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| 369 | RV* drv = UI::build<RV>(root, "drv"); |
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| 370 | set_drv(*drv); |
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| 371 | RV* rv = UI::build<RV>(root, "rv"); |
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| 372 | set_rv(*rv); |
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| 373 | } |
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| 374 | |
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| 375 | // TODO dodelat void to_setting( Setting &root ) const; |
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[342] | 376 | }; |
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[357] | 377 | |
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| 378 | UIREGISTER ( pmsmCRBMz ); |
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