Stores and evaluates LSQ terms within optimal control problems. More...

#include <lsq_term.hpp>

Inheritance diagram for LSQTerm:

Public Member Functions
returnValue	evaluate (const OCPiterate &x)
returnValue	evaluateSensitivities (BlockMatrix *hessian)
returnValue	evaluateSensitivitiesGN (BlockMatrix *GNhessian)
returnValue	getWeigthingtMatrix (const unsigned _index, DMatrix &_matrix) const
BooleanType	isAffine ()
BooleanType	isConvex ()
BooleanType	isQuadratic ()
	LSQTerm ()
	LSQTerm (const MatrixVariablesGrid S_, const Function &h, const VariablesGrid r_)
	LSQTerm (const LSQTerm &rhs)
LSQTerm &	operator= (const LSQTerm &rhs)
returnValue	setGrid (const Grid &grid_)
returnValue	setReference (const VariablesGrid &ref)
virtual	~LSQTerm ()
Protected Attributes
DVector *	r
VariablesGrid *	r_temp
DMatrix *	S
double **	S_h_res
MatrixVariablesGrid *	S_temp

Detailed Description

Stores and evaluates LSQ terms within optimal control problems.

The class LSQTerm allows to manage and evaluate least square objective functionals
of the general form:

0.5* sum_i || S(t_i) * ( h(t_i,x(t_i),u(t_i),p(t_i),...) - r(t_i) ) ||^2_2

Here the sum is over all grid points of the objective grid. The DMatrix S is assumed to
be symmetric and positive (semi-) definite.

Author:: Boris Houska, Hans Joachim Ferreau

Definition at line 61 of file lsq_term.hpp.

Constructor & Destructor Documentation

BEGIN_NAMESPACE_ACADO LSQTerm::LSQTerm ( )

Default constructor.

Definition at line 46 of file acado/objective/lsq_term.cpp.

LSQTerm::LSQTerm	(	const MatrixVariablesGrid *	S_,
		const Function &	h,
		const VariablesGrid *	r_
	)

Default constructor.

Parameters:

S_	the weighting matrix
h	the LSQ function
r_	the reference vectors

Definition at line 59 of file acado/objective/lsq_term.cpp.

LSQTerm::LSQTerm ( const LSQTerm & rhs )

Copy constructor (deep copy).

Definition at line 77 of file acado/objective/lsq_term.cpp.

LSQTerm::~LSQTerm ( ) [virtual]

Destructor.

Definition at line 115 of file acado/objective/lsq_term.cpp.

Member Function Documentation

returnValue LSQTerm::evaluate ( const OCPiterate & x )

Definition at line 201 of file acado/objective/lsq_term.cpp.

returnValue LSQTerm::evaluateSensitivities ( BlockMatrix * hessian )

Evaluates the objective gradient contribution from this term
and computes the corresponding exact hessian if hessian != 0

Returns:: SUCCESSFUL_RETURN

Definition at line 279 of file acado/objective/lsq_term.cpp.

returnValue LSQTerm::evaluateSensitivitiesGN ( BlockMatrix * GNhessian )

Evaluates the objective gradient contribution from this term
and computes the corresponding GN hessian approximation for
the case that GNhessian != 0.