79 f <<
dot(x1) == Alpha /
v * (1.0-x1) *
exp((Gamma*x2)/(1.0+x2));
80 f <<
dot(x2) == (Alpha*
Delta)/
v * (1.0-x1) *
exp((Gamma*x2)/(1.0+x2)) +
Beta/
v * (u-x2);
86 OCP ocp( 0.0,
L, 50 );
87 ocp.minimizeMayerTerm( 0,
Cin*(1.0-x1) );
88 ocp.minimizeMayerTerm( 1, x3 );
92 ocp.subjectTo(
AT_START, x1 == 0.0 );
93 ocp.subjectTo(
AT_START, x2 == 0.0 );
94 ocp.subjectTo(
AT_START, x3 == 0.0 );
96 ocp.subjectTo( 0.0 <= x1 <= 1.0 );
97 ocp.subjectTo( (280.0-Tin)/Tin <= x2 <= (400.0-Tin)/Tin );
98 ocp.subjectTo( (280.0-Tin)/Tin <= u <= (400.0-Tin)/Tin );
116 algorithm.
getControls(
"pfr_nominal_controls0.txt");
138 window1.
addSubplot( paretoFront,
"Pareto Front (conversion versus energy)",
"OUTLET CONCENTRATION",
"ENERGY",
PM_POINTS );
returnValue print(std::ostream &stream=std::cout, const char *const name=DEFAULT_LABEL, const char *const startString=DEFAULT_START_STRING, const char *const endString=DEFAULT_END_STRING, uint width=DEFAULT_WIDTH, uint precision=DEFAULT_PRECISION, const char *const colSeparator=DEFAULT_COL_SEPARATOR, const char *const rowSeparator=DEFAULT_ROW_SEPARATOR) const
virtual returnValue solve()
virtual returnValue plot(PlotFrequency _frequency=PLOT_IN_ANY_CASE)
#define USING_NAMESPACE_ACADO
Provides a time grid consisting of vector-valued optimization variables at each grid point...
returnValue addSubplot(PlotWindowSubplot &_subplot)
returnValue set(OptionsName name, int value)
returnValue getParetoFront(VariablesGrid &paretoFront) const
Data class for defining optimal control problems.
Expression dot(const Expression &arg)
returnValue getControls(VariablesGrid &p_) const
virtual returnValue solveSingleObjective(const int &number)
IntermediateState exp(const Expression &arg)
User-interface to formulate and solve optimal control problems with multiple objectives.
Provides an interface to Gnuplot for plotting algorithmic outputs.
returnValue getDifferentialStates(VariablesGrid &xd_) const
Allows to setup and evaluate differential equations (ODEs and DAEs) based on SymbolicExpressions.