34 #ifndef ACADO_TOOLKIT_SCP_METHOD_HPP 35 #define ACADO_TOOLKIT_SCP_METHOD_HPP 283 #include <acado/nlp_solver/scp_method.ipp> 286 #endif // ACADO_TOOLKIT_SCP_METHOD_HPP
virtual returnValue getDisturbances(VariablesGrid &w_) const
Data class for storing generic optimization variables.
Implements a very rudimentary block sparse matrix class.
Allows real time measurements based on the system's clock.
virtual returnValue setupLogging()
returnValue checkForConvergence()
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.
virtual returnValue getParameters(VariablesGrid &p_) const
virtual returnValue getFirstControl(DVector &u0_) const
BEGIN_NAMESPACE_ACADO typedef unsigned int uint
Base class for different ways to perform a step of an SCPmethod for solving NLPs. ...
Base class for algorithms solving banded conic programs arising in optimal control.
returnValue stopClockAndPrintRuntimeProfile()
returnValue printIterate() const
#define CLOSE_NAMESPACE_ACADO
returnValue printIteration()
virtual returnValue getSensitivitiesXA(BlockMatrix &_sens) const
returnValue initializeHessianProjection()
Base class for discretizing a DifferentialEquation for use in optimal control algorithms.
virtual returnValue getSensitivitiesP(BlockMatrix &_sens) const
virtual returnValue getSensitivitiesX(BlockMatrix &_sens) const
virtual returnValue prepareNextStep()
virtual double getObjectiveValue() const
returnValue setupRealTimeParameters(const DVector &x0_=emptyConstVector, const DVector &p_=emptyConstVector)
returnValue computeHessianMatrix(const BlockMatrix &oldLagrangeGradient, const BlockMatrix &newLagrangeGradient)
virtual returnValue getVarianceCovariance(DMatrix &var)
static const DVector emptyConstVector
uint getNumPoints() const
virtual returnValue getSensitivitiesW(BlockMatrix &_sens) const
virtual returnValue step(const DVector &x0_=emptyConstVector, const DVector &p_=emptyConstVector)
BandedCPsolver * bandedCPsolver
SCPmethod & operator=(const SCPmethod &rhs)
returnValue checkForRealTimeMode(const DVector &x0_, const DVector &p_)
BooleanType isInRealTimeMode
NLPderivativeApproximation * derivativeApproximation
Encapsulates all user interaction for setting options, logging data and plotting results.
virtual returnValue getDifferentialStates(VariablesGrid &xd_) const
virtual returnValue performCurrentStep()
void rhs(const real_t *x, real_t *f)
Implements different sequential convex programming methods for solving NLPs.
Base class for different algorithms for solving nonlinear programming (NLP) problems.
virtual returnValue getSensitivitiesU(BlockMatrix &_sens) const
virtual returnValue getControls(VariablesGrid &u_) const
virtual NLPsolver * clone() const
virtual returnValue init(VariablesGrid *x_init, VariablesGrid *xa_init, VariablesGrid *p_init, VariablesGrid *u_init, VariablesGrid *w_init)
virtual returnValue printRuntimeProfile() const
virtual returnValue feedbackStep(const DVector &x0_, const DVector &p_=emptyConstVector)
virtual returnValue getAnySensitivities(BlockMatrix &_sens, uint idx) const
Base class for different ways to evaluate functions and derivatives within an SCPmethod for solving N...
static DVector emptyVector
#define BEGIN_NAMESPACE_ACADO
virtual returnValue setReference(const VariablesGrid &ref)
BooleanType needToReevaluate
virtual returnValue getAlgebraicStates(VariablesGrid &xa_) const
virtual returnValue shiftVariables(double timeShift=-1.0, DVector lastX=emptyVector, DVector lastXA=emptyVector, DVector lastP=emptyVector, DVector lastU=emptyVector, DVector lastW=emptyVector)
virtual returnValue solve(const DVector &x0_=emptyConstVector, const DVector &p_=emptyConstVector)
Stores and evaluates the objective function of optimal control problems.
Base class for techniques of approximating second-order derivatives within NLPsolvers.
BooleanType hasPerformedStep
Data class for storing conic programs arising from optimal control.