plug_flow_reactor2_ws.cpp
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00001 /*
00002  *    This file is part of ACADO Toolkit.
00003  *
00004  *    ACADO Toolkit -- A Toolkit for Automatic Control and Dynamic Optimization.
00005  *    Copyright (C) 2008-2014 by Boris Houska, Hans Joachim Ferreau,
00006  *    Milan Vukov, Rien Quirynen, KU Leuven.
00007  *    Developed within the Optimization in Engineering Center (OPTEC)
00008  *    under supervision of Moritz Diehl. All rights reserved.
00009  *
00010  *    ACADO Toolkit is free software; you can redistribute it and/or
00011  *    modify it under the terms of the GNU Lesser General Public
00012  *    License as published by the Free Software Foundation; either
00013  *    version 3 of the License, or (at your option) any later version.
00014  *
00015  *    ACADO Toolkit is distributed in the hope that it will be useful,
00016  *    but WITHOUT ANY WARRANTY; without even the implied warranty of
00017  *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
00018  *    Lesser General Public License for more details.
00019  *
00020  *    You should have received a copy of the GNU Lesser General Public
00021  *    License along with ACADO Toolkit; if not, write to the Free Software
00022  *    Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
00023  *
00024  */
00025 
00026 
00045 #include "acado_optimal_control.hpp"
00046 #include <acado_gnuplot.hpp>
00047 
00048 
00049 int main( ){
00050 
00051     USING_NAMESPACE_ACADO
00052 
00053     // INTRODUCE FIXED PARAMETERS:
00054     // ---------------------------
00055     #define  v          0.1
00056     #define  L          1.0
00057     #define  Beta       0.2
00058     #define  Delta      0.25
00059     #define  E          11250.0
00060     #define  k0         1E+06
00061     #define  R          1.986
00062     #define  K3         30.0
00063     #define  Cin        0.02
00064     #define  Tin        340.0
00065 
00066 
00067     // INTRODUCE THE VARIABLES:
00068     // -------------------------
00069     DifferentialState     x1,x2,x3;
00070     Control               u    ;
00071     DifferentialEquation  f( 0.0, L );
00072 
00073 
00074     // DEFINE A DIFFERENTIAL EQUATION:
00075     // -------------------------------
00076     double Alpha, Gamma;
00077     Alpha = k0*exp(-E/(R*Tin));
00078     Gamma = E/(R*Tin);
00079 
00080     f << dot(x1) ==  Alpha       /v * (1.0-x1) * exp((Gamma*x2)/(1.0+x2));
00081     f << dot(x2) == (Alpha*Delta)/v * (1.0-x1) * exp((Gamma*x2)/(1.0+x2)) + Beta/v * (u-x2);
00082     f << dot(x3) == 1.0/K3*Beta/L*(u-x2);
00083 
00084 
00085     // DEFINE AN OPTIMAL CONTROL PROBLEM:
00086     // ----------------------------------
00087     OCP ocp( 0.0, L, 50 );
00088     ocp.minimizeMayerTerm( 0, Cin*(1.0-x1) ); // Solve conversion optimal problem
00089     ocp.minimizeMayerTerm( 1, x3           ); // Solve energy optimal problem
00090 
00091     ocp.subjectTo( f );
00092 
00093     ocp.subjectTo( AT_START, x1 ==  0.0 );
00094     ocp.subjectTo( AT_START, x2 ==  0.0 );
00095     ocp.subjectTo( AT_START, x3 ==  0.0 );
00096 
00097     ocp.subjectTo(  0.0            <= x1 <=  1.0             );
00098     ocp.subjectTo( (280.0-Tin)/Tin <= x2 <= (400.0-Tin)/Tin  );
00099     ocp.subjectTo( (280.0-Tin)/Tin <= u  <= (400.0-Tin)/Tin  );
00100 
00101 
00102     // DEFINE A MULTI-OBJECTIVE ALGORITHM AND SOLVE THE OCP:
00103     // -----------------------------------------------------
00104     MultiObjectiveAlgorithm algorithm(ocp);
00105 
00106     algorithm.set( INTEGRATOR_TYPE, INT_BDF );
00107     algorithm.set( KKT_TOLERANCE, 1e-11 );
00108 
00109     algorithm.set( PARETO_FRONT_GENERATION    , PFG_WEIGHTED_SUM );
00110     algorithm.set( PARETO_FRONT_DISCRETIZATION, 11               );
00111 
00112     // Generate Pareto set
00113     algorithm.solve();
00114 
00115     algorithm.getWeights("plug_flow_reactor2_ws_weights.txt");
00116     algorithm.getAllDifferentialStates("plug_flow_reactor2_ws_states.txt");
00117     algorithm.getAllControls("plug_flow_reactor2_ws_controls.txt");
00118 
00119 
00120     // VISUALIZE THE RESULTS IN A GNUPLOT WINDOW:
00121     // ------------------------------------------
00122     VariablesGrid paretoFront;
00123     algorithm.getParetoFront( paretoFront );
00124 
00125     GnuplotWindow window1;
00126     window1.addSubplot( paretoFront, "Pareto Front (conversion versus energy)", "OUTLET CONCENTRATION", "ENERGY", PM_POINTS );
00127     window1.plot( );
00128 
00129 
00130     // PRINT INFORMATION ABOUT THE ALGORITHM:
00131     // --------------------------------------
00132     algorithm.printInfo();
00133 
00134 
00135     // SAVE INFORMATION:
00136     // ----------------
00137     paretoFront.print();
00138 
00139     return 0;
00140 }
00141 
00142 


acado
Author(s): Milan Vukov, Rien Quirynen
autogenerated on Sat Jun 8 2019 19:38:42