This class sets up the DMS problem. More...

#include <DmsProblem.h>

Inheritance diagram for ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >:

Public Types
typedef DIMENSIONS::state_vector_t	state_vector_t

typedef DIMENSIONS::control_vector_array_t	control_vector_array_t

typedef DIMENSIONS::control_vector_t	control_vector_t

typedef DIMENSIONS::state_vector_array_t	state_vector_array_t

typedef DIMENSIONS::time_array_t	time_array_t

typedef ContinuousOptConProblem< STATE_DIM, CONTROL_DIM, SCALAR >	OptConProblem_t

Public Types inherited from ct::optcon::tpl::Nlp< SCALAR >
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
	DmsProblem (DmsSettings settings, std::vector< typename OptConProblem_t::DynamicsPtr_t > systemPtrs, std::vector< typename OptConProblem_t::LinearPtr_t > linearPtrs, std::vector< typename OptConProblem_t::CostFunctionPtr_t > costPtrs, std::vector< typename OptConProblem_t::ConstraintPtr_t > inputBoxConstraints, std::vector< typename OptConProblem_t::ConstraintPtr_t > stateBoxConstraints, std::vector< typename OptConProblem_t::ConstraintPtr_t > generalConstraints, const state_vector_t &x0)
	Custom constructor, sets up the objects needed for the Dms algorithm depending on the settings. More...

	~DmsProblem () override=default
	Destructor. More...

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

void	configure (const DmsSettings &settings)
	Updates the settings. More...

const state_vector_array_t &	getStateSolution ()
	Retrieves the solution state trajectory at every shot. More...

const control_vector_array_t &	getInputSolution ()
	Retrieves the solution control trajectory at every shot. More...

const time_array_t &	getTimeSolution ()
	Retrieves the solution time trajectory at every shot. More...

const state_vector_array_t &	getStateTrajectory ()
	Retrieves a dense state solution trajectory. More...

const control_vector_array_t &	getInputTrajectory ()
	Retrieves a dense input solution trajectory. More...

const time_array_t &	getTimeArray ()
	Retrieves a dense time solution trajectory. More...

void	setInitialGuess (const state_vector_array_t &x_init_guess, const control_vector_array_t &u_init_guess, const time_array_t &t_init_guess=time_array_t(0.0))
	Sets the initial guess of the optimization. More...

const core::Time	getTimeHorizon () const
	Return the timehorizon of the problem. More...

void	changeTimeHorizon (const SCALAR tf)
	Updates the timehorizon. More...

void	changeInitialState (const state_vector_t &x0)
	Updates the initial state. More...

void	printSolution ()
	Prints the solution trajectories. More...

Public Member Functions inherited from ct::optcon::tpl::Nlp< SCALAR >
	Nlp ()=default
	Default constructor. More...

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

Public Attributes
EIGEN_MAKE_ALIGNED_OPERATOR_NEW typedef DmsDimensions< STATE_DIM, CONTROL_DIM, SCALAR >	DIMENSIONS

Additional Inherited Members
Protected Attributes inherited from ct::optcon::tpl::Nlp< SCALAR >
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<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>
class ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >

This class sets up the DMS problem.

Member Typedef Documentation

◆ state_vector_t

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

typedef DIMENSIONS::state_vector_t ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::state_vector_t

◆ control_vector_array_t

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

typedef DIMENSIONS::control_vector_array_t ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::control_vector_array_t

◆ control_vector_t

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

typedef DIMENSIONS::control_vector_t ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::control_vector_t

◆ state_vector_array_t

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

typedef DIMENSIONS::state_vector_array_t ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::state_vector_array_t

◆ time_array_t

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

typedef DIMENSIONS::time_array_t ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::time_array_t

◆ OptConProblem_t

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

typedef ContinuousOptConProblem<STATE_DIM, CONTROL_DIM, SCALAR> ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::OptConProblem_t

Constructor & Destructor Documentation

◆ DmsProblem()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::DmsProblem	(	DmsSettings	settings,
		std::vector< typename OptConProblem_t::DynamicsPtr_t >	systemPtrs,
		std::vector< typename OptConProblem_t::LinearPtr_t >	linearPtrs,
		std::vector< typename OptConProblem_t::CostFunctionPtr_t >	costPtrs,
		std::vector< typename OptConProblem_t::ConstraintPtr_t >	inputBoxConstraints,
		std::vector< typename OptConProblem_t::ConstraintPtr_t >	stateBoxConstraints,
		std::vector< typename OptConProblem_t::ConstraintPtr_t >	generalConstraints,
		const state_vector_t &	x0
	)

inline

Custom constructor, sets up the objects needed for the Dms algorithm depending on the settings.

Parameters

[in]	settings	The Dms settings
[in]	systemPtrs	The non linear systems
[in]	linearPtrs	The linearized systems
[in]	costPtrs	The cost function
[in]	inputBoxConstraints	The input box constraints
[in]	stateBoxConstraints	The state box constraints
[in]	generaConstraints	The general constraints
[in]	x0	The initial state

◆ ~DmsProblem()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::~DmsProblem ( )

overridedefault

Destructor.

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

Member Function Documentation

◆ updateProblem()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

void ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::updateProblem ( )

inlineoverridevirtual

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

Implements ct::optcon::tpl::Nlp< SCALAR >.

◆ configure()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

void ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::configure ( const DmsSettings & settings )

inline

Updates the settings.

Parameters

[in] settings New dms settings

◆ getStateSolution()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

const state_vector_array_t& ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::getStateSolution ( )

inline

Retrieves the solution state trajectory at every shot.

Returns: The state solution trajectory

◆ getInputSolution()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

const control_vector_array_t& ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::getInputSolution ( )

inline

Retrieves the solution control trajectory at every shot.

Returns: The control solution trajectory

◆ getTimeSolution()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

const time_array_t& ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::getTimeSolution ( )

inline

Retrieves the solution time trajectory at every shot.

Returns: The time solution trajectory

◆ getStateTrajectory()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

const state_vector_array_t& ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::getStateTrajectory ( )

inline

Retrieves a dense state solution trajectory.

Returns: The dense state solution trajectory

◆ getInputTrajectory()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

const control_vector_array_t& ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::getInputTrajectory ( )

inline

Retrieves a dense input solution trajectory.

Returns: The dense control solution trajectory

◆ getTimeArray()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

const time_array_t& ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::getTimeArray ( )

inline

Retrieves a dense time solution trajectory.

Returns: The dense time solution trajectory

◆ setInitialGuess()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

void ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::setInitialGuess	(	const state_vector_array_t &	x_init_guess,
		const control_vector_array_t &	u_init_guess,
		const time_array_t &	t_init_guess = `time_array_t(0.0)`
	)

inline

Sets the initial guess of the optimization.

Parameters

[in]	x_init_guess	The state trajectory initial guess
[in]	u_init_guess	The control trajectory initial guess
[in]	t_init_guess	The time trajectory initial guess

◆ getTimeHorizon()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

const core::Time ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::getTimeHorizon ( ) const

inline

Return the timehorizon of the problem.

Returns: The time horizon

◆ changeTimeHorizon()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

void ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::changeTimeHorizon ( const SCALAR tf )

inline

Updates the timehorizon.

Parameters

[in] tf The new time horizon

◆ changeInitialState()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

void ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::changeInitialState ( const state_vector_t & x0 )

inline

Updates the initial state.

Parameters

[in] x0 The new inital state

◆ printSolution()

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

void ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::printSolution ( )

inline

Prints the solution trajectories.

Member Data Documentation

◆ DIMENSIONS

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>

EIGEN_MAKE_ALIGNED_OPERATOR_NEW typedef DmsDimensions<STATE_DIM, CONTROL_DIM, SCALAR> ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >::DIMENSIONS

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

/home/gim2rng/ct_devel_ws/src/control-toolbox/ct_optcon/include/ct/optcon/dms/dms_core/DmsProblem.h

Public Types

Public Member Functions

Public Attributes

Additional Inherited Members

Detailed Description

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double> class ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >

Member Typedef Documentation

◆ state_vector_t

◆ control_vector_array_t

◆ control_vector_t

◆ state_vector_array_t

◆ time_array_t

◆ OptConProblem_t

Constructor & Destructor Documentation

◆ DmsProblem()

◆ ~DmsProblem()

Member Function Documentation

◆ updateProblem()

◆ configure()

◆ getStateSolution()

◆ getInputSolution()

◆ getTimeSolution()

◆ getStateTrajectory()

◆ getInputTrajectory()

◆ getTimeArray()

◆ setInitialGuess()

◆ getTimeHorizon()

◆ changeTimeHorizon()

◆ changeInitialState()

◆ printSolution()

Member Data Documentation

◆ DIMENSIONS

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>
class ct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR >