ar_controller.hpp

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#ifndef PCARC_HPP
#define PCARC_HPP
 
#include <Eigen/Dense>
#include <mx/improc/eigenCube.hpp>
#include <mx/improc/eigenImage.hpp>
using namespace mx::improc;
 
#include "utils.hpp"
#include "recursive_least_squares.hpp"
 
namespace DDSPC
{
 
class PredictiveController{
    
   private:
        RecursiveLeastSquares* rls;
 
        uint buffer_size;
        uint measurement_head {0};
        uint command_head {0};
        Matrix measurement_buffer;
        Matrix command_buffer;
        
        Matrix* regularization_matrix;
        bool use_regularization_matrix_01 {true};
        bool do_switch_regularization_matrix {false};
        Matrix regularization_matrix_01;
        Matrix regularization_matrix_02;
 
 
        Matrix controller;
        Matrix integrator;
 
        int _num_modes;
        int _num_future;
        int _num_history;
        realT _gain;
        realT _delta_max;
        realT _regularization;
 
        int num_predictors;
        int num_features;
        int num_correlations;
 
   public:
        PredictiveController(int num_actuators, int num_history, int num_future, realT gain, realT gamma, realT initial_regularization, realT initial_covariance);
      ~PredictiveController();
 
        void set_regularization(realT new_regularization);
        inline Matrix get_prediction_matrix(){
            return rls->prediction_matrix;
        };
        
        void reset();
 
        Matrix get_measurement_future();
        Matrix get_measurement_past();
 
        Matrix get_command_future(int skip_cmds);
        Matrix get_command_past();
 
        Matrix get_current_command_past(int num_steps);
        Matrix get_current_measurement_past(int num_steps);
 
        void get_current_past();
        
        Matrix calculate_command(Matrix new_measurement, Matrix exploration_noise);
        void update_system();
        void update_controller();
};
 
}
 
#endif