| 1 | /* | 
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| 2 | * approx_esc_1d.cpp | 
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| 3 | * | 
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| 4 | *  Created on: Jul 30, 2012 | 
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| 5 | *      Author: Berk Calli | 
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| 6 | *      Organization: Delft Biorobotics Lab., Delft University of Technology | 
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| 7 | *              Contact info: b.calli@tudelft.nl, web: www.dbl.tudelft.nl | 
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| 8 | * | 
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| 9 | * Class for one dimensional approximation based extremum seeking control | 
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| 10 | * | 
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| 11 | * * References: | 
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| 12 | * - C. Zhang and R. Ordonez, âRobust and adaptive design of numerical optimization-based extremum seeking control,â Automatica, vol. 45, pp. 634â646, 2009. | 
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| 13 | * - B. Calli, W. Caarls, P. Jonker and M. Wisse, "Comparison of Extremum Seeking Control Algorithms for Robotic Applications," IROS 2012. | 
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| 14 | */ | 
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| 15 |  | 
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| 16 | #include "esc_approx/approx_esc_1d.h" | 
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| 17 |  | 
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| 18 | ApproxESC1D::ApproxESC1D(){ | 
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| 19 | data_size_ = 0; | 
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| 20 | poly_degree_ = 0; | 
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| 21 | k_grad_ = 0; | 
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| 22 | init_vel_ = 0; | 
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| 23 | sampling_ = 0; | 
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| 24 | ptr_ = 0; | 
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| 25 | initialized_ = false; | 
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| 26 | } | 
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| 27 |  | 
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| 28 | ApproxESC1D::ApproxESC1D(int data_size,int poly_degree, double k_grad, double init_vel, int sampling){ | 
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| 29 | init(data_size,poly_degree,k_grad,init_vel,sampling); | 
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| 30 | } | 
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| 31 |  | 
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| 32 | void ApproxESC1D::init(int data_size,int poly_degree, double k_grad, double init_vel, int sampling){ | 
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| 33 | data_size_ = data_size; | 
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| 34 | poly_degree_ = poly_degree; | 
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| 35 | k_grad_ = k_grad; | 
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| 36 | init_vel_ = init_vel; | 
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| 37 | sampling_ = sampling; | 
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| 38 | states_.resize(data_size); | 
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| 39 | obj_vals_.resize(data_size); | 
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| 40 | sample_ = 0; | 
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| 41 | ptr_ = 0; | 
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| 42 | initialized_ = true; | 
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| 43 | } | 
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| 44 |  | 
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| 45 | std::vector<double> ApproxESC1D::step(std::vector<double> state, double obj_val){ | 
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| 46 | if(initialized_){ | 
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| 47 | if(sample_ % sampling_ == 0){ | 
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| 48 |  | 
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| 49 | states_(ptr_) = state[0]; | 
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| 50 | obj_vals_(ptr_) = obj_val; | 
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| 51 |  | 
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| 52 | Eigen::MatrixXf V(data_size_,poly_degree_+1); | 
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| 53 | V = Eigen::MatrixXf::Zero(data_size_, poly_degree_+1); | 
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| 54 |  | 
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| 55 | for (int i = 0; i<data_size_; i++) | 
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| 56 | for (int j = 0; j<poly_degree_+1; j++) | 
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| 57 | V(i,j) = std::pow(states_(i),(poly_degree_-j)); | 
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| 58 |  | 
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| 59 | Eigen::VectorXf coef(data_size_); | 
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| 60 |  | 
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| 61 | coef = V.colPivHouseholderQr().solve(obj_vals_); | 
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| 62 | state_curr_ = states_(ptr_); | 
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| 63 | double grad_val = 0; | 
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| 64 | Eigen::VectorXf vec(data_size_); | 
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| 65 |  | 
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| 66 | for (int i = 0; i<poly_degree_; i++) | 
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| 67 | grad_val = grad_val + coef(i)*(poly_degree_-i)*std::pow(state_curr_,(poly_degree_-i-1)); | 
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| 68 |  | 
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| 69 | if (sample_<sampling_*data_size_+1){ | 
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| 70 | vel_ref_ = init_vel_; | 
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| 71 | } | 
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| 72 | else{ | 
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| 73 | vel_ref_ = -k_grad_*grad_val; | 
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| 74 | if (vel_ref_!= vel_ref_) | 
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| 75 | vel_ref_ = 0; | 
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| 76 | } | 
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| 77 |  | 
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| 78 | sample_ = sample_+1; | 
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| 79 | ptr_ = ptr_+1; | 
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| 80 | if(ptr_>=data_size_) | 
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| 81 | ptr_ = 0; | 
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| 82 |  | 
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| 83 | std::vector<double> out; | 
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| 84 | out.push_back(vel_ref_); | 
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| 85 | return out; | 
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| 86 | } | 
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| 87 | else{ | 
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| 88 | sample_ = sample_+1; | 
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| 89 | std::vector<double> out; | 
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| 90 | out.push_back(vel_ref_); | 
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| 91 | return out; | 
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| 92 | } | 
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| 93 | } | 
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| 94 | else{ | 
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| 95 | fprintf(stderr,"The approximation based ESC (1D) is not initialized... It will not be executed. \n"); | 
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| 96 | return std::vector<double>(); | 
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| 97 | } | 
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| 98 | } | 
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| 99 |  | 
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| 100 | ESC::inputType ApproxESC1D::getInputType(){ | 
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| 101 | return ESC::inputStateValue; | 
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| 102 | } | 
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| 103 | ESC::outputType ApproxESC1D::getOutputType(){ | 
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| 104 | return ESC::outputVelocity; | 
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| 105 | } | 
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| 106 |  | 
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| 107 | std::vector<double> ApproxESC1D::monitor(){ | 
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| 108 | return std::vector<double> (); | 
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| 109 | } | 
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| 110 | std::vector<std::string> ApproxESC1D::monitorNames(){ | 
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| 111 | return std::vector<std::string>(); | 
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| 112 | } | 
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| 113 |  | 
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| 114 | void ApproxESC1D::reset(){ | 
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| 115 | sample_ = 0; | 
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| 116 | ptr_ = 0; | 
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| 117 | } | 
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