| 1 | #ifndef ARX_CTRL_H |
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| 2 | #define ARX_CTRL_H |
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| 3 | |
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| 4 | #include <design/ctrlbase.h> |
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| 5 | using namespace bdm; |
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| 6 | |
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| 7 | /*! exact controller for system \f$ y_{t+1} = y_{t} + b u_{t} + \sigma e_t \f$ |
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| 8 | |
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| 9 | From \f$ E\{y_{ref}\} = E\{ y_{t} + b u_{t} \} \f$, the optimal control action is: |
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| 10 | \f[ u_t = (y_{ref} - y_{t})/b \f] |
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| 11 | |
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| 12 | */ |
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| 13 | |
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| 14 | class exact_ctrl: public Controller { |
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| 15 | protected: |
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| 16 | //! target value of y |
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| 17 | double yr; |
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| 18 | //! parameter b (or its estimate) |
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| 19 | double b; |
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| 20 | public: |
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| 21 | void set_b (const double b0){b=b0;} |
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| 22 | //! data in ctrlaction are only past outputs yt |
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| 23 | vec ctrlaction(const vec &yt)const{ |
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| 24 | vec ut(1); |
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| 25 | if (abs(b)<1e-2) { |
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| 26 | ut= 0.1*randn(); |
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| 27 | } else { |
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| 28 | ut = (yr-yt)/b; |
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| 29 | } |
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| 30 | return ut; |
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| 31 | } |
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| 32 | void from_setting(const Setting &set){ |
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| 33 | Controller::from_setting(set); |
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| 34 | UI::get(yr,set,"yr",UI::compulsory); |
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| 35 | UI::get(b,set,"b",UI::compulsory); |
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| 36 | validate(); |
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| 37 | } |
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| 38 | void validate() { } |
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| 39 | }; |
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| 40 | UIREGISTER(exact_ctrl); |
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| 41 | |
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| 42 | /*! adaptive CE controller for \f$ y_{t+1} = y_{t} + b u_{t} + \sigma e_t \f$ |
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| 43 | |
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| 44 | From \f$ E\{y_{ref}\} = E\{ y_{t} + b u_{t} \} \f$, the optimal control action is: |
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| 45 | \f[ u_t = (y_{ref} - y_{t})/b \f] |
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| 46 | |
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| 47 | Using certainty equivalent approach, i.e. \f$ b= E(b|y_t, u_t, \ldots )\f$, which is |
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| 48 | estimated using ARX model. This class is not truly appropriate since it estimates also \f$ \sigma \f$ |
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| 49 | |
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| 50 | |
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| 51 | */ |
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| 52 | |
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| 53 | class ce_ctrl: public exact_ctrl { |
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| 54 | protected: |
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| 55 | //! estimator |
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| 56 | ARX est; |
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| 57 | //! vector of "dyad" for estimation |
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| 58 | vec Psi; |
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| 59 | //! remember last action - for estimation |
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| 60 | double utm; |
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| 61 | //! remember last input - for estimation |
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| 62 | double ytm; |
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| 63 | public: |
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| 64 | //! expected input is yt |
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| 65 | virtual void adapt(const vec &dt){ |
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| 66 | //prepare data for ARX |
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| 67 | // do estimation |
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| 68 | est.bayes(vec_1(dt(0)-ytm),vec_1(dt(1))); |
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| 69 | ytm = dt(0); |
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| 70 | // save estimate b = E(b); |
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| 71 | b = est.posterior().mean()(0); // first |
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| 72 | } |
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| 73 | //! same as exact control, but stores ut as utm |
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| 74 | vec ctrlaction(const vec &dt)const{ |
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| 75 | vec ut(1); |
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| 76 | mat P = est.posterior().variance(); |
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| 77 | ut(0) =(yr - dt(0))/(b + (b<0 ? P(0,0) : -P(0,0)));; |
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| 78 | // remember last ut for estimation |
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| 79 | return ut; |
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| 80 | } |
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| 81 | void from_setting(const Setting &set){ |
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| 82 | Controller::from_setting(set); |
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| 83 | UI::get(yr,set,"yr",UI::compulsory); |
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| 84 | double b0; |
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| 85 | UI::get(b0,set,"b0",UI::compulsory); |
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| 86 | double P0; |
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| 87 | UI::get(P0,set,"P0",UI::compulsory); |
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| 88 | |
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| 89 | mat V0(2,2); |
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| 90 | V0(0,0) = 0.1; |
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| 91 | V0(1,0) = b0; |
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| 92 | V0(0,1) = b0; |
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| 93 | V0(1,1) = P0/6; |
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| 94 | |
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| 95 | est.set_statistics(1,V0,6); |
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| 96 | est.set_constant(false); |
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| 97 | est.validate(); |
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| 98 | validate(); |
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| 99 | } |
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| 100 | void validate(){ |
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| 101 | Psi = zeros(2); |
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| 102 | } |
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| 103 | void log_register( logger& L, const string& prefix ){ |
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| 104 | est.set_log_level(1); |
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| 105 | est.log_register(L,""); |
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| 106 | }; |
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| 107 | void log_write() const{ |
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| 108 | est.log_write(); |
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| 109 | } |
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| 110 | }; |
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| 111 | UIREGISTER(ce_ctrl); |
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| 112 | |
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| 113 | #endif //ARX_CTRL |
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