three_dimensional_example.cpp
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1 /*
2  * This file is part of ACADO Toolkit.
3  *
4  * ACADO Toolkit -- A Toolkit for Automatic Control and Dynamic Optimization.
5  * Copyright (C) 2008-2014 by Boris Houska, Hans Joachim Ferreau,
6  * Milan Vukov, Rien Quirynen, KU Leuven.
7  * Developed within the Optimization in Engineering Center (OPTEC)
8  * under supervision of Moritz Diehl. All rights reserved.
9  *
10  * ACADO Toolkit is free software; you can redistribute it and/or
11  * modify it under the terms of the GNU Lesser General Public
12  * License as published by the Free Software Foundation; either
13  * version 3 of the License, or (at your option) any later version.
14  *
15  * ACADO Toolkit is distributed in the hope that it will be useful,
16  * but WITHOUT ANY WARRANTY; without even the implied warranty of
17  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
18  * Lesser General Public License for more details.
19  *
20  * You should have received a copy of the GNU Lesser General Public
21  * License along with ACADO Toolkit; if not, write to the Free Software
22  * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
23  *
24  */
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36 #include <acado_gnuplot.hpp>
37 
38 
39 int main( ){
40 
42 
43  // INTRODUCE THE VARIABLES:
44  // -------------------------
45  Parameter x, y, z;
46 
47  // DEFINE AN OPTIMAL CONTROL PROBLEM:
48  // ----------------------------------
49  NLP nlp;
50  nlp.minimize ( x*y + y*z );
51  nlp.subjectTo( x*x - y*y + z*z >= 2.0 );
52  nlp.subjectTo( x*x + y*y + z*z <= 10.0 );
53  nlp.subjectTo( x >= 0.01 );
54  nlp.subjectTo( y >= 0.01 );
55  nlp.subjectTo( z >= 0.01 );
56 
57  // DEFINE AN OPTIMIZATION ALGORITHM AND SOLVE THE NLP:
58  // ---------------------------------------------------
59  OptimizationAlgorithm algorithm(nlp);
60  algorithm.solve();
61 
62  return 0;
63 }
64 
65 
66 
User-interface to formulate and solve optimal control problems and static NLPs.
#define USING_NAMESPACE_ACADO
returnValue subjectTo(const DifferentialEquation &differentialEquation_)
Definition: ocp.cpp:153
returnValue minimize(const Expression &arg)
Definition: nlp.cpp:44
Data class for defining static optimization problems.
Definition: nlp.hpp:47
virtual returnValue solve()


acado
Author(s): Milan Vukov, Rien Quirynen
autogenerated on Mon Jun 10 2019 12:35:12