[42] | 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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[262] | 13 | |
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[42] | 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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[218] | 20 | #include "sim_profiles.h" |
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[42] | 21 | |
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[254] | 22 | using namespace bdm; |
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[48] | 23 | //!Extended Kalman filter with unknown \c Q |
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| 24 | class EKF_unQ : public EKFCh , public BMcond { |
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[42] | 25 | public: |
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[48] | 26 | //! Default constructor |
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| 27 | void condition ( const vec &Q0 ) { |
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| 28 | Q.setD ( Q0,0 ); |
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| 29 | //from EKF |
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| 30 | preA.set_submatrix ( dimy+dimx,dimy,Q._Ch() ); |
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[54] | 31 | }; |
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[48] | 32 | }; |
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[42] | 33 | |
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| 34 | |
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| 35 | int main() { |
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| 36 | // Kalman filter |
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[218] | 37 | int Ndat = 9000; |
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[42] | 38 | double h = 1e-6; |
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[48] | 39 | int Nsimstep = 125; |
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[218] | 40 | int Npart = 200; |
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[54] | 41 | |
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[42] | 42 | // internal model |
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| 43 | IMpmsm fxu; |
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[218] | 44 | // Rs Ls dt Fmag(Ypm) kp p J Bf(Mz) |
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| 45 | fxu.set_parameters ( 0.28, 0.003465, Nsimstep*h, 0.1989, 1.5 ,4.0, 0.04, 0.0 ); |
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[42] | 46 | // observation model |
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| 47 | OMpmsm hxu; |
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| 48 | |
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| 49 | vec mu0= "0.0 0.0 0.0 0.0"; |
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[218] | 50 | vec Qdiag ( "0.001 0.001 1e-6 1e-10" ); //zdenek: 0.01 0.01 0.0001 0.0001 |
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| 51 | vec Rdiag ( "1e-10 1e-10" ); //var(diff(xth)) = "0.034 0.034" |
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[42] | 52 | chmat Q ( Qdiag ); |
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| 53 | chmat R ( Rdiag ); |
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[279] | 54 | EKFCh KFE ; |
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[48] | 55 | KFE.set_parameters ( &fxu,&hxu,Q,R ); |
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[54] | 56 | KFE.set_est ( mu0, chmat ( 1*ones ( 4 ) ) ); |
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[42] | 57 | |
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[162] | 58 | RV rQ ( "{Q }","2" ); |
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[279] | 59 | EKF_unQ KFEp; |
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[48] | 60 | KFEp.set_parameters ( &fxu,&hxu,Q,R ); |
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[218] | 61 | KFEp.set_est ( mu0, chmat ( zeros ( 4 ) ) ); |
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[42] | 62 | |
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[279] | 63 | mgamma evolQ ; |
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| 64 | MPF<EKF_unQ> M (&evolQ,&evolQ,Npart,KFEp ); |
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[48] | 65 | // initialize |
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[279] | 66 | evolQ.set_parameters ( 10.0, "0.01 0.01" ); //sigma = 1/10 mu |
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[54] | 67 | evolQ.condition ( "0.01 0.01" ); //Zdenek default |
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[279] | 68 | epdf& pfinit=evolQ._epdf(); |
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[48] | 69 | M.set_est ( pfinit ); |
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[279] | 70 | evolQ.set_parameters ( 10.0, "0.01 0.01"); |
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[42] | 71 | |
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[48] | 72 | // |
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[42] | 73 | |
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[271] | 74 | const epdf& KFEep = KFE.posterior(); |
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| 75 | const epdf& Mep = M.posterior(); |
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[42] | 76 | |
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[54] | 77 | mat Xt=zeros ( Ndat ,9 ); //true state from simulator |
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| 78 | mat Dt=zeros ( Ndat,4+2 ); //observation |
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| 79 | mat XtE=zeros ( Ndat, 4 ); |
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[218] | 80 | mat XtM=zeros ( Ndat,2+4 ); //Q + x |
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[42] | 81 | |
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| 82 | // SET SIMULATOR |
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| 83 | pmsmsim_set_parameters ( 0.28,0.003465,0.1989,0.0,4,1.5,0.04, 200., 3e-6, h ); |
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| 84 | double Ww=0.0; |
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| 85 | static int k_rampa=1; |
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| 86 | static long k_rampa_tmp=0; |
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| 87 | vec dt ( 2 ); |
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| 88 | vec ut ( 2 ); |
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[218] | 89 | vec vecW="0.1 0.2 0.4 0.9 0.4 0.2 0.0 -0.4 -0.9 -1.6 -0.4 0.0 0.0"; |
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[42] | 90 | |
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| 91 | for ( int tK=1;tK<Ndat;tK++ ) { |
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| 92 | //Number of steps of a simulator for one step of Kalman |
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| 93 | for ( int ii=0; ii<Nsimstep;ii++ ) { |
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| 94 | //simulator |
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[218] | 95 | sim_profile_vec01t(Ww,vecW); |
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[42] | 96 | pmsmsim_step ( Ww ); |
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| 97 | }; |
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| 98 | // collect data |
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[218] | 99 | ut ( 0 ) = 0.0;//KalmanObs[0]; |
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| 100 | ut ( 1 ) = 0.0;//KalmanObs[1]; |
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[42] | 101 | dt ( 0 ) = KalmanObs[2]; |
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| 102 | dt ( 1 ) = KalmanObs[3]; |
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[48] | 103 | |
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[42] | 104 | //estimator |
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| 105 | KFE.bayes ( concat ( dt,ut ) ); |
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[48] | 106 | M.bayes ( concat ( dt,ut ) ); |
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[42] | 107 | |
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[54] | 108 | Xt.set_row ( tK,vec ( x,9 ) ); //vec from C-array |
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| 109 | Dt.set_row ( tK, concat ( dt,ut,vec_1(sqrt(pow(ut(0),2)+pow(ut(1),2))), vec_1(sqrt(pow(dt(0),2)+pow(dt(1),2))) ) ); |
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| 110 | XtE.set_row ( tK,KFEep.mean() ); |
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| 111 | XtM.set_row ( tK,Mep.mean() ); |
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[42] | 112 | } |
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| 113 | |
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| 114 | it_file fou ( "pmsm_sim.it" ); |
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| 115 | |
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| 116 | fou << Name ( "xth" ) << Xt; |
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| 117 | fou << Name ( "Dt" ) << Dt; |
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| 118 | fou << Name ( "xthE" ) << XtE; |
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[48] | 119 | fou << Name ( "xthM" ) << XtM; |
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[42] | 120 | //Exit program: |
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[54] | 121 | |
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[42] | 122 | return 0; |
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[54] | 123 | } |
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