Public Member Functions | Protected Member Functions

User-interface to formulate and solve parameter estimation problems. More...

#include <parameter_estimation_algorithm.hpp>

Inheritance diagram for ParameterEstimationAlgorithm:
Inheritance graph
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List of all members.

Public Member Functions

returnValue getAlgebraicStateVarianceCovariance (DMatrix &xaVar)
returnValue getControlCovariance (DMatrix &uVar)
returnValue getDifferentialStateVarianceCovariance (DMatrix &xVar)
returnValue getDistubanceVarianceCovariance (DMatrix &wVar)
returnValue getParameterVarianceCovariance (DMatrix &pVar)
returnValue getVarianceCovariance (DMatrix &var)
ParameterEstimationAlgorithmoperator= (const ParameterEstimationAlgorithm &arg)
 ParameterEstimationAlgorithm ()
 ParameterEstimationAlgorithm (const OCP &ocp_)
 ParameterEstimationAlgorithm (const ParameterEstimationAlgorithm &arg)
virtual ~ParameterEstimationAlgorithm ()

Protected Member Functions

virtual returnValue initializeNlpSolver (const OCPiterate &_userInit)
virtual returnValue initializeObjective (Objective *F)

Detailed Description

User-interface to formulate and solve parameter estimation problems.

The class ParameterEstimationAlgorithm serves as a user-interface to formulate and solve parameter estimation problems.

Author:
Boris Houska, Hans Joachim Ferreau

Definition at line 59 of file parameter_estimation_algorithm.hpp.


Constructor & Destructor Documentation

Default constructor.

Definition at line 47 of file parameter_estimation_algorithm.cpp.

Default constructor.

Definition at line 54 of file parameter_estimation_algorithm.cpp.

Copy constructor (deep copy).

Definition at line 61 of file parameter_estimation_algorithm.cpp.

Destructor.

Definition at line 68 of file parameter_estimation_algorithm.cpp.


Member Function Documentation

Method to obtain the variance-coveriance matrix in the optimal solution
(with respect to the parameters)

Returns:
SUCCESSFUL_RETURN

Definition at line 122 of file parameter_estimation_algorithm.cpp.

Method to obtain the variance-coveriance matrix in the optimal solution
(with respect to the parameters)

Returns:
SUCCESSFUL_RETURN

Definition at line 128 of file parameter_estimation_algorithm.cpp.

Method to obtain the variance-coveriance matrix in the optimal solution
(with respect to the parameters)

Returns:
SUCCESSFUL_RETURN

Definition at line 116 of file parameter_estimation_algorithm.cpp.

Method to obtain the variance-coveriance matrix in the optimal solution
(with respect to the parameters)

Returns:
SUCCESSFUL_RETURN

Definition at line 134 of file parameter_estimation_algorithm.cpp.

Method to obtain the variance-coveriance matrix in the optimal solution
(with respect to the parameters)

Returns:
SUCCESSFUL_RETURN

Definition at line 84 of file parameter_estimation_algorithm.cpp.

Method to obtain the variance-coveriance matrix in the optimal solution

Returns:
SUCCESSFUL_RETURN

Definition at line 140 of file parameter_estimation_algorithm.cpp.

returnValue ParameterEstimationAlgorithm::initializeNlpSolver ( const OCPiterate _userInit) [protected, virtual]

Reimplemented from OptimizationAlgorithm.

Definition at line 153 of file parameter_estimation_algorithm.cpp.

Reimplemented from OptimizationAlgorithm.

Definition at line 159 of file parameter_estimation_algorithm.cpp.

ParameterEstimationAlgorithm & ParameterEstimationAlgorithm::operator= ( const ParameterEstimationAlgorithm arg)

Assignment operator (deep copy).

Definition at line 74 of file parameter_estimation_algorithm.cpp.


The documentation for this class was generated from the following files:


acado
Author(s): Milan Vukov, Rien Quirynen
autogenerated on Sat Jun 8 2019 19:40:25