gauss_newton_approximation.hpp

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/*
 *    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
 *
 */


#ifndef ACADO_TOOLKIT_GAUSS_NEWTON_APPROXIMATION_HPP
#define ACADO_TOOLKIT_GAUSS_NEWTON_APPROXIMATION_HPP


#include <acado/utils/acado_utils.hpp>
#include <acado/nlp_derivative_approximation/nlp_derivative_approximation.hpp>


BEGIN_NAMESPACE_ACADO



class GaussNewtonApproximation : public NLPderivativeApproximation
{
    //
    // PUBLIC MEMBER FUNCTIONS:
    //
    public:

        GaussNewtonApproximation( );
                
        GaussNewtonApproximation(       UserInteraction* _userInteraction
                                                                        );

        GaussNewtonApproximation( const GaussNewtonApproximation& rhs );

        virtual ~GaussNewtonApproximation( );

        GaussNewtonApproximation& operator=( const GaussNewtonApproximation& rhs );


                virtual NLPderivativeApproximation* clone( ) const;



        virtual returnValue initHessian(        BlockMatrix& B,             
                                                                                        uint N,                 
                                                                                        const OCPiterate& iter  
                                                                                        );

        virtual returnValue initScaling(        BlockMatrix& B, 
                                                                                        const BlockMatrix& x, 
                                                                                        const BlockMatrix& y  
                                                                                        );


        virtual returnValue apply(       BlockMatrix &B, 
                                   const BlockMatrix &x, 
                                   const BlockMatrix &y   );



    //
    // PROTECTED MEMBER FUNCTIONS:
    //
    protected:



    //
    // PROTECTED DATA MEMBERS:
    //
    protected:

};


CLOSE_NAMESPACE_ACADO


//#include <acado/nlp_derivative_approximation/gauss_newton_approximation.ipp>


// collect remaining headers
#include <acado/nlp_derivative_approximation/gauss_newton_approximation_bfgs.hpp>



#endif  // ACADO_TOOLKIT_GAUSS_NEWTON_APPROXIMATION_HPP

/*
 *  end of file
 */