The NLP base class. This class serves as abstract base class to use as an interface to the NLP solver IPOPT and SNOPT. More...

#include <Nlp.h>

Inheritance diagram for ct::optcon::tpl::Nlp< SCALAR >:

Public Types
using	VectorXs = Eigen::Matrix< SCALAR, Eigen::Dynamic, 1 >

using	VectorXi = Eigen::Matrix< int, Eigen::Dynamic, 1 >

using	MapVecXs = Eigen::Map< VectorXs >

using	MapVecXi = Eigen::Map< VectorXi >

using	MapConstVecXs = Eigen::Map< const VectorXs >

Public Member Functions
	Nlp ()=default
	Default constructor. More...

virtual	~Nlp ()=default
	Destructor. More...

virtual void	updateProblem ()=0
	{ This method gets called at each update of the Optimization variables. This can be used to distribute or rearrange the optimization variables appropriately } More...

SCALAR	evaluateCostFun ()
	{ Evaluates the costfunction at the current nlp iteration } More...

void	evaluateCostGradient (const size_t n, MapVecXs &grad)
	{ Evaluates the gradient of the costfunction} More...

void	evaluateConstraints (MapVecXs &values)
	{ Evaluates the constraints } More...

void	evaluateConstraintJacobian (const int nele_jac, MapVecXs &jac)
	{ Evaluates the constraint jacobian } More...

void	evaluateHessian (const int nele_hes, MapVecXs &hes, const SCALAR obj_fac, MapConstVecXs &lambda)
	Evaluates the hessian of the lagrangian. More...

void	getSparsityPatternJacobian (const int nele_jac, MapVecXi &iRow, MapVecXi &jCol) const
	Gets the sparsity pattern. More...

void	getSparsityPatternHessian (const int nele_hes, MapVecXi &iRow, MapVecXi &jCol) const
	Gets the sparsity pattern of the Hessian of the Lagrangian. More...

size_t	getConstraintsCount () const
	Returns the number of constraints in the NLP. More...

size_t	getNonZeroJacobianCount () const
	Returns the number of the non zero elements of the constraint jacobian. More...

size_t	getNonZeroHessianCount ()
	Returns the number of non zeros in the Hessian. More...

void	getConstraintBounds (MapVecXs &lowerBound, MapVecXs &upperBound, const size_t m) const
	Reads the bounds of the constraints. More...

size_t	getVarCount () const
	Returns the number of Optimization optimization variables. More...

void	getVariableBounds (MapVecXs &lowerBound, MapVecXs &upperBound, const size_t n) const
	Reads the bounds on the Optimization optimization variables. More...

void	extractOptimizationVars (const MapConstVecXs &x, bool isNew)
	{Extracts the Optimization optimization variables from the nlp solvers between nlp iterations} More...

void	getInitialGuess (const size_t n, MapVecXs &x) const
	Gets the Optimization variables. More...

void	getOptimizationMultState (const size_t n, MapVecXs &xMul, MapVecXi &xState) const
	Gets the variable multiplier and the variable state, used in the NLP solver SNOPT. See the snopt documentation for further explanations. More...

void	getConstraintsMultState (const size_t m, MapVecXs &zMul, MapVecXi &zState) const
	Gets the constraint multiplier and state, used in the NLP solver SNOPT. More...

void	getBoundMultipliers (size_t n, MapVecXs &zLow, MapVecXs &zUp) const
	Gets the bound multipliers used in the NLP solver IPOPT. More...

void	getLambdaVars (size_t m, MapVecXs &lambda) const
	Gets the values of the constraint multipliers. More...

void	extractIpoptSolution (const MapConstVecXs &x, const MapConstVecXs &zL, const MapConstVecXs &zU, const MapConstVecXs &lambda)
	{ Extracts the solution values from IPOPT } More...

void	extractSnoptSolution (const MapVecXs &x, const MapVecXs &xMul, const MapVecXi &xState, const MapVecXs &fMul, const MapVecXi &fState)
	{ Extracts the solution values from SNOPT } More...

Protected Attributes
std::shared_ptr< DiscreteCostEvaluatorBase< SCALAR > >	costEvaluator_
	Ptr to cost evaluator, which approximates the cost evaluation for the discrete problem. More...

std::shared_ptr< OptVector< SCALAR > >	optVariables_
	Ptr to optimization variable container, which holds the optimization variables used in the NLP solvers. More...

std::shared_ptr< DiscreteConstraintContainerBase< SCALAR > >	constraints_
	Ptr to constraint container, which contains the discretized constraints for the problem. More...

Eigen::VectorXi	iRowHessianCost_
	helper containers for calculating the sparsity patterns More...

Eigen::VectorXi	iRowHessianConstraints_

Eigen::VectorXi	jColHessianCost_

Eigen::VectorXi	jColHessianConstraints_

Eigen::VectorXi	iRowHessian_
	combined Hessian sparsity pattern gets stored here More...

Eigen::VectorXi	jColHessian_

Detailed Description

template<typename SCALAR>
class ct::optcon::tpl::Nlp< SCALAR >

The NLP base class. This class serves as abstract base class to use as an interface to the NLP solver IPOPT and SNOPT.

Member Typedef Documentation

◆ VectorXs

template<typename SCALAR >

using ct::optcon::tpl::Nlp< SCALAR >::VectorXs = Eigen::Matrix<SCALAR, Eigen::Dynamic, 1>

◆ VectorXi

template<typename SCALAR >

using ct::optcon::tpl::Nlp< SCALAR >::VectorXi = Eigen::Matrix<int, Eigen::Dynamic, 1>

◆ MapVecXs

template<typename SCALAR >

using ct::optcon::tpl::Nlp< SCALAR >::MapVecXs = Eigen::Map<VectorXs>

◆ MapVecXi

template<typename SCALAR >

using ct::optcon::tpl::Nlp< SCALAR >::MapVecXi = Eigen::Map<VectorXi>

◆ MapConstVecXs

template<typename SCALAR >

using ct::optcon::tpl::Nlp< SCALAR >::MapConstVecXs = Eigen::Map<const VectorXs>

Constructor & Destructor Documentation

◆ Nlp()

template<typename SCALAR >

ct::optcon::tpl::Nlp< SCALAR >::Nlp ( )

default

Default constructor.

◆ ~Nlp()

template<typename SCALAR >

virtual ct::optcon::tpl::Nlp< SCALAR >::~Nlp ( )

virtualdefault

Destructor.

Member Function Documentation

◆ updateProblem()

template<typename SCALAR >

virtual void ct::optcon::tpl::Nlp< SCALAR >::updateProblem ( )

pure virtual

{ This method gets called at each update of the Optimization variables. This can be used to distribute or rearrange the optimization variables appropriately }

Implemented in ExampleProblem< SCALAR >, ExampleProblem< SCALAR >, and ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >.

Referenced by ct::optcon::tpl::Nlp< SCALAR >::extractOptimizationVars().

◆ evaluateCostFun()

template<typename SCALAR >

SCALAR ct::optcon::tpl::Nlp< SCALAR >::evaluateCostFun ( )

inline

{ Evaluates the costfunction at the current nlp iteration }

Returns: { Scalar value of the resulting cost }

References ct::optcon::tpl::Nlp< SCALAR >::costEvaluator_.

◆ evaluateCostGradient()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::evaluateCostGradient	(	const size_t	n,
		MapVecXs &	grad
	)

inline

{ Evaluates the gradient of the costfunction}

Parameters

[in]	n	{ size of the gradient }
[out]	grad	The gradient of the cost function

References ct::optcon::tpl::Nlp< SCALAR >::costEvaluator_.

◆ evaluateConstraints()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::evaluateConstraints ( MapVecXs & values )

inline

{ Evaluates the constraints }

Parameters

[out] values The values of the constraint violations, wrapped as a vector

References ct::optcon::tpl::Nlp< SCALAR >::constraints_.

◆ evaluateConstraintJacobian()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::evaluateConstraintJacobian	(	const int	nele_jac,
		MapVecXs &	jac
	)

inline

{ Evaluates the constraint jacobian }

Parameters

[in]	nele_jac	The number of non zeros in the constraint jacobian
[out]	jac	The non zero values of the jacobian

References ct::optcon::tpl::Nlp< SCALAR >::constraints_.

◆ evaluateHessian()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::evaluateHessian	(	const int	nele_hes,
		MapVecXs &	hes,
		const SCALAR	obj_fac,
		MapConstVecXs &	lambda
	)

inline

Evaluates the hessian of the lagrangian.

Parameters

[in]	nele_hes	The number of non zeros in the hessian
	hes	The values of the non-zeros of the hessian
[in]	obj_fac	The costfunction multiplier (zero or one, NLP solver uses this to query for parts of the hessian only)
	lambda	The constraint multipliers

Note: it is important to note that our NLP-solvers expect the Hessian reduced to triangular form (symmetry).

References ct::optcon::tpl::Nlp< SCALAR >::constraints_, ct::optcon::tpl::Nlp< SCALAR >::costEvaluator_, i, ct::optcon::tpl::Nlp< SCALAR >::iRowHessianConstraints_, ct::optcon::tpl::Nlp< SCALAR >::iRowHessianCost_, ct::optcon::tpl::Nlp< SCALAR >::jColHessianConstraints_, ct::optcon::tpl::Nlp< SCALAR >::jColHessianCost_, and ct::optcon::tpl::Nlp< SCALAR >::optVariables_.

◆ getSparsityPatternJacobian()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::getSparsityPatternJacobian	(	const int	nele_jac,
		MapVecXi &	iRow,
		MapVecXi &	jCol
	)		const

inline

Gets the sparsity pattern.

Parameters

[in]	nele_jac	The number of non zero elements in the constraint jacobian
[out]	iRow	The row indices of the location of the non zero elements of the constraint jacobian
[out]	jCol	The column indices of the location of the non zero elements of the constraint jacobian

References ct::optcon::tpl::Nlp< SCALAR >::constraints_.

◆ getSparsityPatternHessian()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::getSparsityPatternHessian	(	const int	nele_hes,
		MapVecXi &	iRow,
		MapVecXi &	jCol
	)		const

inline

Gets the sparsity pattern of the Hessian of the Lagrangian.

Parameters

[in]	nele_hes	The number of non zero elements in the hessian
	iRow	The row indices
	jCol	The column indices

References ct::optcon::tpl::Nlp< SCALAR >::iRowHessian_, and ct::optcon::tpl::Nlp< SCALAR >::jColHessian_.

◆ getConstraintsCount()

template<typename SCALAR >

size_t ct::optcon::tpl::Nlp< SCALAR >::getConstraintsCount ( ) const

inline

Returns the number of constraints in the NLP.

Returns: The number of constraints.

References ct::optcon::tpl::Nlp< SCALAR >::constraints_.

Referenced by ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::DmsProblem().

◆ getNonZeroJacobianCount()

template<typename SCALAR >

size_t ct::optcon::tpl::Nlp< SCALAR >::getNonZeroJacobianCount ( ) const

inline

Returns the number of the non zero elements of the constraint jacobian.

Returns: The number of the non zero elements of the constraint jacobian.

References ct::optcon::tpl::Nlp< SCALAR >::constraints_.

◆ getNonZeroHessianCount()

template<typename SCALAR >

size_t ct::optcon::tpl::Nlp< SCALAR >::getNonZeroHessianCount ( )

inline

Returns the number of non zeros in the Hessian.

This method intelligently combines sparsity of cost and constraint Hessians using sparse Eigen operations.

Returns: The number of non zeros in the Hessian

References ct::optcon::tpl::Nlp< SCALAR >::constraints_, ct::optcon::tpl::Nlp< SCALAR >::costEvaluator_, i, ct::optcon::tpl::Nlp< SCALAR >::iRowHessian_, ct::optcon::tpl::Nlp< SCALAR >::iRowHessianConstraints_, ct::optcon::tpl::Nlp< SCALAR >::iRowHessianCost_, ct::optcon::tpl::Nlp< SCALAR >::jColHessian_, ct::optcon::tpl::Nlp< SCALAR >::jColHessianConstraints_, ct::optcon::tpl::Nlp< SCALAR >::jColHessianCost_, and ct::optcon::tpl::Nlp< SCALAR >::optVariables_.

◆ getConstraintBounds()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::getConstraintBounds	(	MapVecXs &	lowerBound,
		MapVecXs &	upperBound,
		const size_t	m
	)		const

inline

Reads the bounds of the constraints.

Parameters

[out]	lowerBound	The lower constraint bound
[out]	upperBound	The upper constraint bound
[in]	m	{ The size of the constraints }

References ct::optcon::tpl::Nlp< SCALAR >::constraints_.

◆ getVarCount()

template<typename SCALAR >

size_t ct::optcon::tpl::Nlp< SCALAR >::getVarCount ( ) const

inline

Returns the number of Optimization optimization variables.

Returns: The number of Optimization variables.

References ct::optcon::tpl::Nlp< SCALAR >::optVariables_.

◆ getVariableBounds()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::getVariableBounds	(	MapVecXs &	lowerBound,
		MapVecXs &	upperBound,
		const size_t	n
	)		const

inline

Reads the bounds on the Optimization optimization variables.

Parameters

[out]	lowerBound	The lower optimization variable bound
[out]	upperBound	The upper optimization variable bound
[in]	n	{ The number of Optimization variables }

References ct::optcon::tpl::Nlp< SCALAR >::optVariables_.

◆ extractOptimizationVars()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::extractOptimizationVars	(	const MapConstVecXs &	x,
		bool	isNew
	)

inline

{Extracts the Optimization optimization variables from the nlp solvers between nlp iterations}

Parameters

[in]	x	{ The value of the Optimization variables }
[in]	isNew	Indicates whether x differs from a previous call

References ct::optcon::tpl::Nlp< SCALAR >::optVariables_, and ct::optcon::tpl::Nlp< SCALAR >::updateProblem().

◆ getInitialGuess()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::getInitialGuess	(	const size_t	n,
		MapVecXs &	x
	)		const

inline

Gets the Optimization variables.

Parameters

[in]	n	{ The number of Optimization variables }
[out]	x	{ The values of the Optimization vars }

References ct::optcon::tpl::Nlp< SCALAR >::optVariables_.

◆ getOptimizationMultState()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::getOptimizationMultState	(	const size_t	n,
		MapVecXs &	xMul,
		MapVecXi &	xState
	)		const

inline

Gets the variable multiplier and the variable state, used in the NLP solver SNOPT. See the snopt documentation for further explanations.

Parameters

[in]	n	{ The number of Optimization variables }
[out]	xMul	The optimization variable multiplier
[out]	xState	The optimization variable states

References ct::optcon::tpl::Nlp< SCALAR >::optVariables_.

◆ getConstraintsMultState()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::getConstraintsMultState	(	const size_t	m,
		MapVecXs &	zMul,
		MapVecXi &	zState
	)		const

inline

Gets the constraint multiplier and state, used in the NLP solver SNOPT.

Parameters

[in]	m	{ The number of constraints }
[out]	zMul	The constraint variable multiplier
[out]	zState	The constraint variable state

References ct::optcon::tpl::Nlp< SCALAR >::optVariables_.

◆ getBoundMultipliers()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::getBoundMultipliers	(	size_t	n,
		MapVecXs &	zLow,
		MapVecXs &	zUp
	)		const

inline

Gets the bound multipliers used in the NLP solver IPOPT.

Parameters

[in]	n	{ The number of optimization variables }
[out]	zLow	The value for the lower bound multiplier
[out]	zUp	The value for the upper bound multiplier

References ct::optcon::tpl::Nlp< SCALAR >::optVariables_.

◆ getLambdaVars()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::getLambdaVars	(	size_t	m,
		MapVecXs &	lambda
	)		const

inline

Gets the values of the constraint multipliers.

Parameters

[in]	m	{ The number of constraints }
[out]	lambda	The values of the constraint multipliers

References ct::optcon::tpl::Nlp< SCALAR >::optVariables_.

◆ extractIpoptSolution()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::extractIpoptSolution	(	const MapConstVecXs &	x,
		const MapConstVecXs &	zL,
		const MapConstVecXs &	zU,
		const MapConstVecXs &	lambda
	)

inline

{ Extracts the solution values from IPOPT }

Parameters

[in]	x	{ The values of the optimization variables }
[in]	zL	The value for the lower bound multiplier
[in]	zU	The value for the upper bound multiplier
[in]	lambda	The values of the constraint multipliers

References ct::optcon::tpl::Nlp< SCALAR >::optVariables_.

◆ extractSnoptSolution()

template<typename SCALAR >

void ct::optcon::tpl::Nlp< SCALAR >::extractSnoptSolution	(	const MapVecXs &	x,
		const MapVecXs &	xMul,
		const MapVecXi &	xState,
		const MapVecXs &	fMul,
		const MapVecXi &	fState
	)

inline

{ Extracts the solution values from SNOPT }

Parameters

[in]	x	{ The values of the optimization variables }
[in]	xMul	The optimization variable multiplier
[in]	xState	The optimization variable state
[in]	fMul	The constraint variable multiplier
[in]	fState	The constraint variable state

References ct::optcon::tpl::Nlp< SCALAR >::optVariables_.

Member Data Documentation

◆ costEvaluator_

template<typename SCALAR >

std::shared_ptr<DiscreteCostEvaluatorBase<SCALAR> > ct::optcon::tpl::Nlp< SCALAR >::costEvaluator_

protected

Ptr to cost evaluator, which approximates the cost evaluation for the discrete problem.

Referenced by ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::DmsProblem(), ct::optcon::tpl::Nlp< SCALAR >::evaluateCostFun(), ct::optcon::tpl::Nlp< SCALAR >::evaluateCostGradient(), ct::optcon::tpl::Nlp< SCALAR >::evaluateHessian(), and ct::optcon::tpl::Nlp< SCALAR >::getNonZeroHessianCount().

◆ optVariables_

template<typename SCALAR >

std::shared_ptr<OptVector<SCALAR> > ct::optcon::tpl::Nlp< SCALAR >::optVariables_

protected

Ptr to optimization variable container, which holds the optimization variables used in the NLP solvers.

◆ constraints_

template<typename SCALAR >

std::shared_ptr<DiscreteConstraintContainerBase<SCALAR> > ct::optcon::tpl::Nlp< SCALAR >::constraints_

protected

Ptr to constraint container, which contains the discretized constraints for the problem.

Referenced by ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::DmsProblem(), ct::optcon::tpl::Nlp< SCALAR >::evaluateConstraintJacobian(), ct::optcon::tpl::Nlp< SCALAR >::evaluateConstraints(), ct::optcon::tpl::Nlp< SCALAR >::evaluateHessian(), ct::optcon::tpl::Nlp< SCALAR >::getConstraintBounds(), ct::optcon::tpl::Nlp< SCALAR >::getConstraintsCount(), ct::optcon::tpl::Nlp< SCALAR >::getNonZeroHessianCount(), ct::optcon::tpl::Nlp< SCALAR >::getNonZeroJacobianCount(), and ct::optcon::tpl::Nlp< SCALAR >::getSparsityPatternJacobian().

◆ iRowHessianCost_

template<typename SCALAR >

Eigen::VectorXi ct::optcon::tpl::Nlp< SCALAR >::iRowHessianCost_

protected

helper containers for calculating the sparsity patterns

Referenced by ct::optcon::tpl::Nlp< SCALAR >::evaluateHessian(), and ct::optcon::tpl::Nlp< SCALAR >::getNonZeroHessianCount().

◆ iRowHessianConstraints_

template<typename SCALAR >

Eigen::VectorXi ct::optcon::tpl::Nlp< SCALAR >::iRowHessianConstraints_

protected

Referenced by ct::optcon::tpl::Nlp< SCALAR >::evaluateHessian(), and ct::optcon::tpl::Nlp< SCALAR >::getNonZeroHessianCount().

◆ jColHessianCost_

template<typename SCALAR >

Eigen::VectorXi ct::optcon::tpl::Nlp< SCALAR >::jColHessianCost_

protected

Referenced by ct::optcon::tpl::Nlp< SCALAR >::evaluateHessian(), and ct::optcon::tpl::Nlp< SCALAR >::getNonZeroHessianCount().

◆ jColHessianConstraints_

template<typename SCALAR >

Eigen::VectorXi ct::optcon::tpl::Nlp< SCALAR >::jColHessianConstraints_

protected

Referenced by ct::optcon::tpl::Nlp< SCALAR >::evaluateHessian(), and ct::optcon::tpl::Nlp< SCALAR >::getNonZeroHessianCount().

◆ iRowHessian_

template<typename SCALAR >

Eigen::VectorXi ct::optcon::tpl::Nlp< SCALAR >::iRowHessian_

protected

combined Hessian sparsity pattern gets stored here

Referenced by ct::optcon::tpl::Nlp< SCALAR >::getNonZeroHessianCount(), and ct::optcon::tpl::Nlp< SCALAR >::getSparsityPatternHessian().

◆ jColHessian_

template<typename SCALAR >

Eigen::VectorXi ct::optcon::tpl::Nlp< SCALAR >::jColHessian_

protected

Referenced by ct::optcon::tpl::Nlp< SCALAR >::getNonZeroHessianCount(), and ct::optcon::tpl::Nlp< SCALAR >::getSparsityPatternHessian().

The documentation for this class was generated from the following file:

/home/gim2rng/ct_devel_ws/src/control-toolbox/ct_optcon/include/ct/optcon/nlp/Nlp.h

Public Types

Public Member Functions

Protected Attributes

Detailed Description

template<typename SCALAR> class ct::optcon::tpl::Nlp< SCALAR >

Member Typedef Documentation

◆ VectorXs

◆ VectorXi

◆ MapVecXs

◆ MapVecXi

◆ MapConstVecXs

Constructor & Destructor Documentation

◆ Nlp()

◆ ~Nlp()

Member Function Documentation

◆ updateProblem()

◆ evaluateCostFun()

◆ evaluateCostGradient()

◆ evaluateConstraints()

◆ evaluateConstraintJacobian()

◆ evaluateHessian()

◆ getSparsityPatternJacobian()

◆ getSparsityPatternHessian()

◆ getConstraintsCount()

◆ getNonZeroJacobianCount()

◆ getNonZeroHessianCount()

◆ getConstraintBounds()

◆ getVarCount()

◆ getVariableBounds()

◆ extractOptimizationVars()

◆ getInitialGuess()

◆ getOptimizationMultState()

◆ getConstraintsMultState()

◆ getBoundMultipliers()

◆ getLambdaVars()

◆ extractIpoptSolution()

◆ extractSnoptSolution()

Member Data Documentation

◆ costEvaluator_

◆ optVariables_

◆ constraints_

◆ iRowHessianCost_

◆ iRowHessianConstraints_

◆ jColHessianCost_

◆ jColHessianConstraints_

◆ iRowHessian_

◆ jColHessian_

template<typename SCALAR>
class ct::optcon::tpl::Nlp< SCALAR >