10 #ifndef __MITTELMANNDISTRCNTRLDIRI_HPP__
11 #define __MITTELMANNDISTRCNTRLDIRI_HPP__
19 #include "configall_system.h"
28 # error "don't have header file for math"
38 # error "don't have header file for stdio"
42 using namespace Ipopt;
106 bool& use_x_scaling,
Index n,
108 bool& use_g_scaling,
Index m,
198 return (N_+2)*(N_+2) + (j-1) + (N_)*(i-1);
204 return (j-1) + N_*(i-1);
232 printf(
"N has to be at least 1.");
240 Number u_init = (ub_u+lb_u)/2.;
242 SetBaseParameters(N, alpha, lb_y, ub_y, lb_u, ub_u, u_init);
249 return 1. + 2.*(x1*(x1-1.)+x2*(x2-1.));
254 return pow(y,3) - y - u;
290 printf(
"N has to be at least 1.");
298 Number u_init = (ub_u+lb_u)/2.;
300 SetBaseParameters(N, alpha, lb_y, ub_y, lb_u, ub_u, u_init);
307 return 1. + 2.*(x1*(x1-1.)+x2*(x2-1.));
312 return pow(y,3) - y - u;
350 printf(
"N has to be at least 1.");
358 Number u_init = (ub_u+lb_u)/2.;
360 SetBaseParameters(N, alpha, lb_y, ub_y, lb_u, ub_u, u_init);
367 return sin(2.*pi_*x1)*sin(2.*pi_*x2);
411 printf(
"N has to be at least 1.");
419 Number u_init = (ub_u+lb_u)/2.;
421 SetBaseParameters(N, alpha, lb_y, ub_y, lb_u, ub_u, u_init);
428 return sin(2.*pi_*x1)*sin(2.*pi_*x2);
Number * x
Input: Starting point Output: Optimal solution.
Number Number Index Number Number Index Index nele_hess
Number of non-zero elements in Hessian of Lagrangian.
Number Number * g
Values of constraint at final point (output only - ignored if set to NULL)
Number Number Index Number Number Index nele_jac
Number of non-zero elements in constraint Jacobian.
Number Number * x_scaling
Number Number Number * g_scaling
Number Number Index m
Number of constraints.
Number Number Index Number Number Index Index Index index_style
indexing style for iRow & jCol, 0 for C style, 1 for Fortran style
Class for all IPOPT specific calculated quantities.
Class to organize all the data required by the algorithm.
IndexStyleEnum
overload this method to return the number of variables and constraints, and the number of non-zeros i...
Class implementating Example 1.
virtual bool InitializeProblem(Index N)
Initialize internal parameters, where N is a parameter determining the problme size.
virtual Number d_cont_du(Number x1, Number x2, Number y, Number u) const
First partial derivative of forcing function w.r.t.
virtual Number d_cont_dydy(Number x1, Number x2, Number y, Number u) const
Second partial derivative of forcing function w.r.t y,y.
virtual ~MittelmannDistCntrlDiri1()
virtual Number d_cont_dy(Number x1, Number x2, Number y, Number u) const
First partial derivative of forcing function w.r.t.
MittelmannDistCntrlDiri1(const MittelmannDistCntrlDiri1 &)
virtual Number y_d_cont(Number x1, Number x2) const
Target profile function for y.
virtual Number d_cont(Number x1, Number x2, Number y, Number u) const
Forcing function for the elliptic equation.
MittelmannDistCntrlDiri1()
MittelmannDistCntrlDiri1 & operator=(const MittelmannDistCntrlDiri1 &)
Class implementating Example 2.
virtual Number d_cont_du(Number x1, Number x2, Number y, Number u) const
First partial derivative of forcing function w.r.t.
virtual Number d_cont_dydy(Number x1, Number x2, Number y, Number u) const
Second partial derivative of forcing function w.r.t y,y.
MittelmannDistCntrlDiri2 & operator=(const MittelmannDistCntrlDiri2 &)
virtual Number d_cont(Number x1, Number x2, Number y, Number u) const
Forcing function for the elliptic equation.
virtual bool InitializeProblem(Index N)
Initialize internal parameters, where N is a parameter determining the problme size.
virtual Number d_cont_dy(Number x1, Number x2, Number y, Number u) const
First partial derivative of forcing function w.r.t.
MittelmannDistCntrlDiri2()
virtual ~MittelmannDistCntrlDiri2()
virtual Number y_d_cont(Number x1, Number x2) const
Target profile function for y.
MittelmannDistCntrlDiri2(const MittelmannDistCntrlDiri2 &)
Class implementating Example 3.
virtual bool InitializeProblem(Index N)
Initialize internal parameters, where N is a parameter determining the problme size.
virtual Number d_cont_dy(Number x1, Number x2, Number y, Number u) const
First partial derivative of forcing function w.r.t.
virtual Number d_cont(Number x1, Number x2, Number y, Number u) const
Forcing function for the elliptic equation.
MittelmannDistCntrlDiri3(const MittelmannDistCntrlDiri3 &)
MittelmannDistCntrlDiri3()
virtual Number d_cont_dydy(Number x1, Number x2, Number y, Number u) const
Second partial derivative of forcing function w.r.t y,y.
MittelmannDistCntrlDiri3 & operator=(const MittelmannDistCntrlDiri3 &)
virtual Number y_d_cont(Number x1, Number x2) const
Target profile function for y.
const Number pi_
Value of pi (made available for convenience)
virtual ~MittelmannDistCntrlDiri3()
virtual Number d_cont_du(Number x1, Number x2, Number y, Number u) const
First partial derivative of forcing function w.r.t.
MittelmannDistCntrlDiri3a(const MittelmannDistCntrlDiri3a &)
virtual Number d_cont_du(Number x1, Number x2, Number y, Number u) const
First partial derivative of forcing function w.r.t.
MittelmannDistCntrlDiri3a & operator=(const MittelmannDistCntrlDiri3a &)
const Number pi_
Value of pi (made available for convenience)
virtual Number d_cont(Number x1, Number x2, Number y, Number u) const
Forcing function for the elliptic equation.
virtual bool InitializeProblem(Index N)
Initialize internal parameters, where N is a parameter determining the problme size.
virtual Number d_cont_dydy(Number x1, Number x2, Number y, Number u) const
Second partial derivative of forcing function w.r.t y,y.
virtual ~MittelmannDistCntrlDiri3a()
MittelmannDistCntrlDiri3a()
virtual Number y_d_cont(Number x1, Number x2) const
Target profile function for y.
virtual Number d_cont_dy(Number x1, Number x2, Number y, Number u) const
First partial derivative of forcing function w.r.t.
Base class for distributed control problems with Dirichlet boundary conditions, as formulated by Hans...
virtual bool eval_h(Index n, const Number *x, bool new_x, Number obj_factor, Index m, const Number *lambda, bool new_lambda, Index nele_hess, Index *iRow, Index *jCol, Number *values)
Method to return: 1) The structure of the hessian of the lagrangian (if "values" is NULL) 2) The valu...
Number ub_y_
overall upper bound on y
Number u_init_
Initial value for the constrols u.
virtual bool get_starting_point(Index n, bool init_x, Number *x, bool init_z, Number *z_L, Number *z_U, Index m, bool init_lambda, Number *lambda)
Method to return the starting point for the algorithm.
MittelmannDistCntrlDiriBase()
Constructor.
MittelmannDistCntrlDiriBase(const MittelmannDistCntrlDiriBase &)
virtual Number d_cont_dy(Number x1, Number x2, Number y, Number u) const =0
First partial derivative of forcing function w.r.t.
Number alpha_
Weighting parameter for the control target deviation functional in the objective.
MittelmannDistCntrlDiriBase & operator=(const MittelmannDistCntrlDiriBase &)
void SetBaseParameters(Index N, Number alpha, Number lb_y, Number ub_y, Number lb_u, Number ub_u, Number u_init)
Method for setting the internal parameters that define the problem.
Number lb_u_
overall lower bound on u
virtual Number d_cont_du(Number x1, Number x2, Number y, Number u) const =0
First partial derivative of forcing function w.r.t.
virtual bool get_nlp_info(Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, IndexStyleEnum &index_style)
Method to return some info about the nlp.
Index y_index(Index i, Index j) const
Translation of mesh point indices to NLP variable indices for y(x_ij)
virtual Number d_cont_dydy(Number x1, Number x2, Number y, Number u) const =0
Second partial derivative of forcing function w.r.t.
Index u_index(Index i, Index j) const
Translation of mesh point indices to NLP variable indices for u(x_ij)
virtual Number y_d_cont(Number x1, Number x2) const =0
Target profile function for y.
virtual bool eval_grad_f(Index n, const Number *x, bool new_x, Number *grad_f)
Method to return the gradient of the objective.
virtual ~MittelmannDistCntrlDiriBase()
Default destructor.
virtual bool eval_g(Index n, const Number *x, bool new_x, Index m, Number *g)
Method to return the constraint residuals.
Index N_
Number of mesh points in one dimension (excluding boundary)
Number * y_d_
Array for the target profile for y.
virtual bool eval_jac_g(Index n, const Number *x, bool new_x, Index m, Index nele_jac, Index *iRow, Index *jCol, Number *values)
Method to return: 1) The structure of the jacobian (if "values" is NULL) 2) The values of the jacobia...
Number ub_u_
overall upper bound on u
virtual bool get_scaling_parameters(Number &obj_scaling, bool &use_x_scaling, Index n, Number *x_scaling, bool &use_g_scaling, Index m, Number *g_scaling)
Method for returning scaling parameters.
virtual bool eval_f(Index n, const Number *x, bool new_x, Number &obj_value)
Method to return the objective value.
virtual bool get_bounds_info(Index n, Number *x_l, Number *x_u, Index m, Number *g_l, Number *g_u)
Method to return the bounds for my problem.
Number x2_grid(Index i) const
Compute the grid coordinate for given index in x2 direction.
virtual Number d_cont(Number x1, Number x2, Number y, Number u) const =0
Forcing function for the elliptic equation.
Number x1_grid(Index i) const
Compute the grid coordinate for given index in x1 direction.
Number lb_y_
overall lower bound on y
virtual void finalize_solution(SolverReturn status, Index n, const Number *x, const Number *z_L, const Number *z_U, Index m, const Number *g, const Number *lambda, Number obj_value, const IpoptData *ip_data, IpoptCalculatedQuantities *ip_cq)
This method is called after the optimization, and could write an output file with the optimal profile...
Index pde_index(Index i, Index j) const
Translation of interior mesh point indices to the corresponding PDE constraint number.
Class implemented the NLP discretization of.
SolverReturn
enum for the return from the optimize algorithm (obviously we need to add more)
int Index
Type of all indices of vectors, matrices etc.
double Number
Type of all numbers.