33 #ifndef ACADO_TOOLKIT_OPTIMIZATION_ALGORITHM_BASE_HPP 34 #define ACADO_TOOLKIT_OPTIMIZATION_ALGORITHM_BASE_HPP 231 const Grid& _unionGrid,
253 #endif // ACADO_TOOLKIT_OPTIMIZATION_ALGORITHM_BASE_HPP returnValue simulateStatesForInitialization()
Data class for storing generic optimization variables.
Implements a very rudimentary block sparse matrix class.
OptimizationAlgorithmBase & operator=(const OptimizationAlgorithmBase &arg)
virtual uint getNP() const
double getEndTime() const
returnValue getSensitivitiesXA(BlockMatrix &_sens) const
virtual uint getNX() const
virtual returnValue initializeNlpSolver(const OCPiterate &_userInit)=0
virtual uint getNXA() const
returnValue initializeControls(const char *fileName)
OptimizationAlgorithmBase()
virtual returnValue initializeOCPiterate(Constraint *const _constraint, const Grid &_unionGrid, uint nx, uint nxa, uint np, uint nu, uint nw)
virtual ~OptimizationAlgorithmBase()
returnValue initializeDisturbances(const char *fileName)
Stores and evaluates the constraints of optimal control problems.
Provides a time grid consisting of vector-valued optimization variables at each grid point...
Allows to pass back messages to the calling function.
returnValue getSensitivitiesW(BlockMatrix &_sens) const
double getStartTime() const
double getObjectiveValue() const
BEGIN_NAMESPACE_ACADO typedef unsigned int uint
Allows to conveniently handle (one-dimensional) grids consisting of time points.
returnValue getParameters(VariablesGrid &u_) const
virtual returnValue setupDynamicDiscretization(UserInteraction *_userIteraction, Objective *objective, DifferentialEquation **differentialEquation, Constraint *constraint, Grid unionGrid, DynamicDiscretization **dynamicDiscretization)
returnValue initializeParameters(const char *fileName)
#define CLOSE_NAMESPACE_ACADO
returnValue getSensitivitiesP(BlockMatrix &_sens) const
Base class for user-interfaces to formulate and solve optimal control problems and static NLPs...
Base class for discretizing a DifferentialEquation for use in optimal control algorithms.
virtual returnValue allocateNlpSolver(Objective *F, DynamicDiscretization *G, Constraint *H)=0
returnValue getAlgebraicStates(VariablesGrid &xa_) const
returnValue getSensitivitiesX(BlockMatrix &_sens) const
BooleanType isLinearQuadratic(Objective *F, DynamicDiscretization *G, Constraint *H) const
returnValue getSensitivitiesU(BlockMatrix &_sens) const
returnValue initializeDifferentialStates(const char *fileName, BooleanType autoinit=BT_FALSE)
returnValue getDisturbances(VariablesGrid &w_) const
Encapsulates all user interaction for setting options, logging data and plotting results.
virtual returnValue setupObjective(Objective *objective, DifferentialEquation **differentialEquation, Constraint *constraint, Grid unionGrid)
Data class for defining optimal control problems.
virtual returnValue extractOCPdata(Objective **objective, DifferentialEquation ***differentialEquation, Constraint **constraint, Grid &unionGrid)
virtual uint getNU() const
Base class for different algorithms for solving nonlinear programming (NLP) problems.
returnValue getControls(VariablesGrid &p_) const
returnValue initializeAlgebraicStates(const char *fileName, BooleanType autoinit=BT_FALSE)
virtual uint getNW() const
virtual returnValue setupDifferentialEquation(Objective *objective, DifferentialEquation **differentialEquation, Constraint *constraint, Grid unionGrid)
virtual returnValue initializeObjective(Objective *F)=0
#define BEGIN_NAMESPACE_ACADO
virtual returnValue determineDimensions(Objective *const _objective, DifferentialEquation **const _differentialEquation, Constraint *const _constraint, uint &_nx, uint &_nxa, uint &_np, uint &_nu, uint &_nw) const
returnValue init(UserInteraction *_userIteraction)
Stores and evaluates the objective function of optimal control problems.
returnValue getDifferentialStates(VariablesGrid &xd_) const
Allows to setup and evaluate differential equations (ODEs and DAEs) based on SymbolicExpressions.