automatic_backward_differentiation.cpp

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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
 *
 */



#include <acado_integrators.hpp>

using namespace std;

USING_NAMESPACE_ACADO

/* >>> start tutorial code >>> */
int main()
{
        USING_NAMESPACE_ACADO

        // DEFINE VALRIABLES:
        // ---------------------------
        DifferentialState       x,y;

        Function f;

        f << (x+1)*(y+1) + y*x*y;//pow(y,3);
        f << x;
        f << y;

        // EVALUATE THE FUNCTION f:
        // ------------------------
        EvaluationPoint z(f);

        DVector diffState(2);

        diffState(0) = 1.0;
        diffState(1) = 2.0;

        z.setX( diffState );

        DVector ff = f(z);

        ff.print();

        // COMPUTE THE BACKWARD DERIVATIVE:
        // --------------------------------

        DVector seed(f.getDim());

        seed(0) = 1.0;
        seed(1) = 0.0;
        seed(2) = 0.0;

        EvaluationPoint df(f);

        f.AD_backward( seed, df );

        df.getX().print(cout, "df");

        return 0;
}
/* <<< end tutorial code <<< */