Data class for storing generic optimization variables.
virtual returnValue initScaling(BlockMatrix &B, const BlockMatrix &x, const BlockMatrix &y)
Implements a very rudimentary block sparse matrix class.
Allows to pass back messages to the calling function.
virtual returnValue apply(BlockMatrix &B, const BlockMatrix &x, const BlockMatrix &y)
BEGIN_NAMESPACE_ACADO typedef unsigned int uint
virtual ~GaussNewtonApproximationWithBFGS()
#define CLOSE_NAMESPACE_ACADO
Implements a Gauss-Newton approximation as second-order derivatives within NLPsolvers.
virtual returnValue initScaling(BlockMatrix &B, const BlockMatrix &x, const BlockMatrix &y)
virtual NLPderivativeApproximation * clone() const
GaussNewtonApproximationWithBFGS()
Encapsulates all user interaction for setting options, logging data and plotting results.
Implements a Gauss-Newton approximation with block BFGS updates as second-order derivatives within NL...
void rhs(const real_t *x, real_t *f)
Implements BFGS updates for approximating second-order derivatives within NLPsolvers.
virtual returnValue initHessian(BlockMatrix &B, uint N, const OCPiterate &iter)
GaussNewtonApproximationWithBFGS & operator=(const GaussNewtonApproximationWithBFGS &rhs)
virtual returnValue apply(BlockMatrix &B, const BlockMatrix &x, const BlockMatrix &y)
virtual returnValue initHessian(BlockMatrix &B, uint N, const OCPiterate &iter)
GaussNewtonApproximation & operator=(const GaussNewtonApproximation &rhs)
virtual returnValue initScaling(BlockMatrix &B, const BlockMatrix &x, const BlockMatrix &y)
virtual returnValue apply(BlockMatrix &B, const BlockMatrix &x, const BlockMatrix &y)
#define BEGIN_NAMESPACE_ACADO
#define ACADOERROR(retval)
Base class for techniques of approximating second-order derivatives within NLPsolvers.