openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 200 supported car makes and models.
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

178 lines
5.8 KiB

/*
* This file is part of ACADO Toolkit.
*
* ACADO Toolkit -- A Toolkit for Automatic Control and Dynamic Optimization.
* Copyright (C) 2008-2014 by Boris Houska, Hans Joachim Ferreau,
* Milan Vukov, Rien Quirynen, KU Leuven.
* Developed within the Optimization in Engineering Center (OPTEC)
* under supervision of Moritz Diehl. All rights reserved.
*
* ACADO Toolkit is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 3 of the License, or (at your option) any later version.
*
* ACADO Toolkit is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with ACADO Toolkit; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*
*/
/**
* \file include/acado/objective/lsq_end_term.hpp
* \author Boris Houska, Hans Joachim Ferreau
*
*/
#ifndef ACADO_TOOLKIT_LSQ_END_TERM_HPP
#define ACADO_TOOLKIT_LSQ_END_TERM_HPP
#include <acado/objective/objective_element.hpp>
BEGIN_NAMESPACE_ACADO
/**
* \brief Stores and evaluates LSQ mayer terms within optimal control problems.
*
* \ingroup BasicDataStructures
*
* The class LSQEndTerm allows to manage and evaluate least square objective mayer terms \n
* of the general form: \n
* \n
* 0.5* || S * ( m(T,x(T),p(T),...) - r ) ||^2_2 \n
* \n
* Here the T is the time at the last grid point of the objective grid. \n
*
* \author Boris Houska, Hans Joachim Ferreau
*/
class LSQEndTerm : public ObjectiveElement{
//
// PUBLIC MEMBER FUNCTIONS:
//
public:
/** Default constructor. */
LSQEndTerm( );
/** Default constructor. */
LSQEndTerm( const Grid& grid_, /**< the objective grid */
const DMatrix &S_, /**< the weighting matrix */
const Function &m_, /**< the LSQ function */
const DVector &r_ /**< the reference vector */ );
/** Copy constructor (deep copy). */
LSQEndTerm( const LSQEndTerm& rhs );
/** Destructor. */
virtual ~LSQEndTerm( );
/** Assignment operator (deep copy). */
LSQEndTerm& operator=( const LSQEndTerm& rhs );
// =======================================================================================
//
// INITIALIZATION ROUTINES
//
// =======================================================================================
inline returnValue init( const Grid& grid_, /**< the objective grid */
const DMatrix &S_, /**< the weighting matrix */
const Function& m_, /**< the LSQ function */
const DVector &r_ /**< the reference vectors */ );
// =======================================================================================
//
// EVALUATION ROUTINES
//
// =======================================================================================
returnValue evaluate( const OCPiterate &x );
/** Evaluates the objective gradient contribution from this term \n
* and computes the corresponding exact hessian. \n
* \n
* \return SUCCESSFUL_RETURN \n
*/
returnValue evaluateSensitivities( BlockMatrix *hessian );
/** Evaluates the objective gradient contribution from this term \n
* and computes the corresponding GN hessian approximation for \n
* the case that GNhessian != 0. \n
* \n
* \return SUCCESSFUL_RETURN \n
*/
returnValue evaluateSensitivitiesGN( BlockMatrix *GNhessian );
/** returns whether the constraint element is affine. */
inline BooleanType isAffine();
/** returns whether the constraint element is convex. */
inline BooleanType isQuadratic();
/** returns whether the constraint element is convex. */
inline BooleanType isConvex();
/** overwrites the reference vector r \n
* \n
* \return SUCCESSFUL_RETURN
*/
inline returnValue setReference( const DVector &ref );
// =======================================================================================
//
// DATA MEMBERS:
//
protected:
DMatrix S ; /**< a symmetric weighting matrix */
DVector r ; /**< a tracking reference */
double *S_h_res ; /**< specific intermediate results \n
* to be stored for backward \n
* differentiation \n
*/
};
CLOSE_NAMESPACE_ACADO
#include <acado/objective/lsq_end_term.ipp>
#endif // ACADO_TOOLKIT_LSQ_END_TERM_HPP
/*
* end of file
*/