Namespaces
	example

	tpl

Classes
class	BoxConstraintBase
	Base for box constraint, templated on dimension of the decision vector of the derived class. More...

class	CARE
	Continuous-Time Algebraic Riccati Equation. More...

class	Cholesky
	Cholesky square root decomposition of a symmetric positive-definite matrix. More...

class	ConstraintBase
	Base class for the constraints used in this toolbox. More...

class	ConstraintContainerAnalytical
	Contains all the constraints using analytically calculated jacobians. More...

class	ConstraintContainerBase
	The ConstraintBase Class is the base class for defining the non-linear optimization constraints. More...

class	ConstraintDiscretizer
	The class takes continuous constraints defined with the constraint toolbox and discretizes them over the DMS shots. These discretized constraints can then be used in the NLP module. More...

class	ConstraintsContainerDms
	Container class for the constraints used in DMS. More...

class	ContinuityConstraint
	Implementation of the DMS continuity constraints. More...

class	ControlInputConstraint
	Class for control input box constraint term. More...

class	ControllerDms
	DMS controller class. More...

class	CostEvaluatorFull
	Performs the full cost integration over the shots. More...

class	CostEvaluatorSimple
	Evaluates the cost at the shots and performs some interpolation in between. More...

class	CostFunction
	A base function for cost functions. All cost functions should derive from this. More...

class	CostFunctionAnalytical
	A cost function which contains only terms that have analytical derivatives. More...

class	CostFunctionQuadratic
	Describes a cost function with a quadratic approximation, i.e. one that can compute first and second order derivatives with respect to state and control input. This does NOT mean it has to be a purely quadratic cost function. If you are looking for a purely quadratic cost function, check CostFunctionQuadraticSimple. More...

class	CostFunctionQuadraticSimple
	A simple quadratic cost function. More...

class	CTSystemModel
	System model adapted to CT. System model encapsulates the integrator, so it is able to propagate the system, but also computes derivatives w.r.t. both state and noise. When propagating the system, CTSystemModel does not use the specified control input, but uses the assigned system controller instead. More...

class	DARE
	Discrete-Time Algebraic Riccati Equation. More...

class	DisturbedSystem
	Disturbed system augments the nominal system so that all the CT interfaces and dimensions are satisfied. What is done is basically augmenting the state with the assumed disturbance with specified dimensionality. More...

class	DisturbedSystemController
	Disturbed controller allows us to augment the controller so that all the CT interfaces and dimensions are satisfied. Augmenting is done in such a way that the nominal controller is wrapped and all the nominal states are controlled in the same way as before augmenting the state. The augmented state (the disturbance part) is assumed constant, thus the computed derivates of that part of the state are set to zero. More...

class	DmsDimensions
	Defines basic types used in the DMS algorithm. More...

struct	DmsPolicy
	The DMS policy used as a solution container. More...

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

class	DmsSettings
	Defines the DMS settings. More...

class	DmsSolver
	Class to solve a specfic DMS problem. More...

class	DynamicRiccatiEquation
	Dynamic Riccati Equation. More...

class	EstimatorBase
	Estimator base. More...

class	ExtendedKalmanFilter
	Extended Kalman Filter implementation. For an algorithmic overview, see also https://en.wikipedia.org/wiki/Extended_Kalman_filter. More...

struct	ExtendedKalmanFilterSettings
	Settings for setting up an ExtendedKF. More...

class	FHDTLQR
	Finite-Horizon Discrete Time LQR. More...

class	GNRiccatiSolver

class	InitStateConstraint
	The implementation of the DMS initial state constraint. More...

class	InputDisturbedSystem
	Implementation of an input disturbed system where, the dimension of the disturbance is equal to the dimension of the control input, thus DIST_DIM = CONTROL_DIM. This is a special case, however it occurs often and is convenient to have as separate class. More...

class	IpoptSettings
	IPOPT settings. Details about the parameters can be found in the IPOPT documentation. More...

class	LinearConstraintContainer
	A base function for linear constraint functions which have a first derivative. More...

class	LinearMeasurementModel
	Linear Measurement Model is an interface for linear measurement models most commonly used in practice. More...

class	LinearSpliner
	The linear spline implementation. More...

struct	LineSearchSettings
	GNMS Line Search Settings. More...

class	LQOCProblem
	Defines a Linear-Quadratic Optimal Control Problem, which is optionally constrained. More...

class	LQOCSolver

struct	LQOCSolverSettings
	LQOC Solver settings. More...

class	LQR
	continuous-time infinite-horizon LQR More...

class	LTIMeasurementModel
	Linear Time-Invariant measurement model is simply a linear measurement model for which the matrix C is constant in time. More...

class	MeasurementModelBase

class	MPC
	Main MPC class. More...

struct	mpc_settings
	MPC Settings struct. More...

class	MultipleShooting

class	NLOCAlgorithm

class	NLOCBackendBase
	C++ implementation of GNMS. More...

class	NLOCBackendMP

class	NLOCBackendST

class	NLOptConSettings
	Settings for the NLOptCon algorithm. More...

class	NLOptConSolver

class	NlpSolverSettings
	Contains the NLP solver settings. More...

class	ObstacleConstraint
	Class for obstacle constraint. More...

class	OptconContinuousSystemInterface
	interface class for optimal control algorithms More...

class	OptconDiscreteSystemInterface
	interface class for optimal control algorithms More...

class	OptConProblemBase

class	OptConSolver

class	OptconSystemInterface
	interface base class for optimal control algorithms More...

class	OptVectorDms
	This class is a wrapper around the NLP Optvector. It wraps the Vectors from the NLP solvers into state, control and time trajectories. More...

class	PolicyHandler

class	RKnDerivatives
	This class implements analytical sensitivity generation for the euler and rk4 integration scheme. More...

class	SensitivityIntegratorCT
	This class can integrate a controlled system and a costfunction. Furthermore, it provides first order derivatives with respect to initial state and control. More...

class	ShotContainer
	This class performs the state and the sensitivity integration on a shot. More...

class	SingleShooting

class	SnoptSettings
	SnoptSolver settings. Details about the parameters can be found in the SNOPT documentation. More...

class	SnoptSolver

class	SplinerBase
	Abstract base class for the control input splining between the DMS shots. More...

class	StateConstraint
	Class for state box constraint. More...

class	StateFeedbackPolicyHandler
	the default policy handler for iLQR More...

struct	StateObserverSettings
	Settings for setting up a StateObserver. More...

class	SteadyStateKalmanFilter
	Steady State Kalman Filter is a time invariant linear estimator. It starts with the same update rule as the standard Kalman Filter, but instead of propagating the covariance and estimate through time, it assumes convergence reducing the problem to solving an Algebraic Ricatti Equation. More...

struct	SteadyStateKalmanFilterSettings
	Settings for setting up a SteadyStateKF. More...

class	SwitchedLinearConstraintContainer
	A container for switching linear constraint containers. More...

class	SystemModelBase
	System model is an interface that encapsulates the integrator to be able to propagate the system, but is also able to compute derivatives w.r.t. both state and noise. More...

class	TermBase
	An interface for a term, supporting both analytical and auto-diff terms. More...

class	TerminalConstraint
	Class for terminal constraint. More...

class	TermLinear
	A linear term of type . More...

class	TermMixed
	A basic quadratic term of type . More...

class	TermQuadMult
	A multiplicative term of type . More...

class	TermQuadratic
	A basic quadratic term of type . More...

class	TermQuadTracking
	A quadratic tracking term of type $J(t) = (x_{ref}(t) - x)^T Q (x_{ref}(t) - x) + (u_{ref}(t) - u)^T R (u_{ref}(t) - u)$ . More...

class	TermSmoothAbs
	A smooth absolute term of type where this calculation is performed component-wise and summed with individual weighting factors a[i], b[i]. More...

class	TermStateBarrier
	A state barrier term (could also be considered a soft constraint) Note that this term explicitly excludes controls, as there are better ways to limit control effort in a "soft" way, e.g. through the use of sigmoid functions. More...

class	UnscentedKalmanFilter
	Unscented Kalman Filter is a nonlinear estimator best suited for highly nonlinear systems. It combines the principles of EKF and particle filter. The downside is the computation complexity. More...

struct	UnscentedKalmanFilterSettings
	Settings for setting up an UnscentedKF. More...

class	ZeroOrderHoldSpliner
	The spline implementation for the zero order hold spliner. More...

Typedefs
typedef tpl::TimeGrid< double >	TimeGrid

template<size_t OUTPUT_DIM, size_t STATE_DIM, typename SCALAR = double>
using	DisturbanceObserverSettings = StateObserverSettings< OUTPUT_DIM, STATE_DIM, SCALAR >
	Settings for setting up a DisturbanceObserver. More...

typedef tpl::MpcTimeKeeper< double >	MpcTimeKeeper

typedef tpl::MpcTimeHorizon< double >	MpcTimeHorizon

using	DiscreteConstraintBase = tpl::DiscreteConstraintBase< double >

using	DiscreteConstraintContainerBase = tpl::DiscreteConstraintContainerBase< double >

using	DiscreteCostEvaluatorBase = tpl::DiscreteCostEvaluatorBase< double >

using	Nlp = tpl::Nlp< double >

using	OptVector = tpl::OptVector< double >

using	IpoptSolver = tpl::IpoptSolver< double >

using	NlpSolver = tpl::NlpSolver< double >

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>
using	ContinuousOptConProblem = OptConProblemBase< STATE_DIM, CONTROL_DIM, core::ControlledSystem< STATE_DIM, CONTROL_DIM, SCALAR >, core::LinearSystem< STATE_DIM, CONTROL_DIM, SCALAR >, core::SystemLinearizer< STATE_DIM, CONTROL_DIM, SCALAR >, SCALAR >

template<size_t STATE_DIM, size_t CONTROL_DIM, typename SCALAR = double>
using	DiscreteOptConProblem = OptConProblemBase< STATE_DIM, CONTROL_DIM, core::DiscreteControlledSystem< STATE_DIM, CONTROL_DIM, SCALAR >, core::DiscreteLinearSystem< STATE_DIM, CONTROL_DIM, SCALAR >, core::DiscreteSystemLinearizer< STATE_DIM, CONTROL_DIM, SCALAR >, SCALAR >

Enumerations
enum	MPC_MODE { FIXED_FINAL_TIME = 0, CONSTANT_RECEDING_HORIZON, FIXED_FINAL_TIME_WITH_MIN_TIME_HORIZON, RECEDING_HORIZON_WITH_FIXED_FINAL_TIME }
	select a mode in which MPC is supposed to run More...

enum	NlpSolverType : uint8_t { NlpSolverType::IPOPT = 0, NlpSolverType::SNOPT = 1, NlpSolverType::num_types_solver }
	The available types of NLP solvers. More...

Functions
template<typename SCALAR >
void	loadScalarCF (const std::string &filename, const std::string &scalarName, SCALAR &scalar, const std::string &termName="")

template<typename SCALAR >
void	loadScalarOptionalCF (const std::string &filename, const std::string &scalarName, SCALAR &scalar, const std::string &termName, const SCALAR &defaultValue)

template<typename SCALAR , int ROW, int COL>
void	loadMatrixCF (const std::string &filename, const std::string &matrixName, Eigen::Matrix< SCALAR, ROW, COL > &matrix, const std::string &termName="")

template<typename TERM_PTR , typename costFuncType >
void	addTerm (const std::string &filename, std::string &currentTerm, int currentTermType, TERM_PTR term, costFuncType *costFunc, bool verbose=false)

template<typename TERM_PTR , typename costFuncType >
void	addADTerm (const std::string &filename, std::string &currentTerm, int currentTermType, TERM_PTR term, costFuncType *costFunc, bool verbose=false)

void	loadMpcSettings (const std::string &filename, mpc_settings &settings)
	load the mpc settings from file More...

Typedef Documentation

◆ TimeGrid

typedef tpl::TimeGrid<double> ct::optcon::TimeGrid

◆ DisturbanceObserverSettings

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

using ct::optcon::DisturbanceObserverSettings = typedef StateObserverSettings<OUTPUT_DIM, STATE_DIM, SCALAR>

Settings for setting up a DisturbanceObserver.

The DisturbanceObserver settings are designed to make the initialization smoother and possible through a file configuration.

◆ MpcTimeKeeper

typedef tpl::MpcTimeKeeper<double> ct::optcon::MpcTimeKeeper

◆ MpcTimeHorizon

typedef tpl::MpcTimeHorizon<double> ct::optcon::MpcTimeHorizon

◆ DiscreteConstraintBase

using ct::optcon::DiscreteConstraintBase = typedef tpl::DiscreteConstraintBase<double>

◆ DiscreteConstraintContainerBase

using ct::optcon::DiscreteConstraintContainerBase = typedef tpl::DiscreteConstraintContainerBase<double>

◆ DiscreteCostEvaluatorBase

using ct::optcon::DiscreteCostEvaluatorBase = typedef tpl::DiscreteCostEvaluatorBase<double>

◆ Nlp

using ct::optcon::Nlp = typedef tpl::Nlp<double>

◆ OptVector

using ct::optcon::OptVector = typedef tpl::OptVector<double>

◆ IpoptSolver

using ct::optcon::IpoptSolver = typedef tpl::IpoptSolver<double>

◆ NlpSolver

using ct::optcon::NlpSolver = typedef tpl::NlpSolver<double>

◆ ContinuousOptConProblem

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

using ct::optcon::ContinuousOptConProblem = typedef OptConProblemBase<STATE_DIM, CONTROL_DIM, core::ControlledSystem<STATE_DIM, CONTROL_DIM, SCALAR>, core::LinearSystem<STATE_DIM, CONTROL_DIM, SCALAR>, core::SystemLinearizer<STATE_DIM, CONTROL_DIM, SCALAR>, SCALAR>

◆ DiscreteOptConProblem

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

using ct::optcon::DiscreteOptConProblem = typedef OptConProblemBase<STATE_DIM, CONTROL_DIM, core::DiscreteControlledSystem<STATE_DIM, CONTROL_DIM, SCALAR>, core::DiscreteLinearSystem<STATE_DIM, CONTROL_DIM, SCALAR>, core::DiscreteSystemLinearizer<STATE_DIM, CONTROL_DIM, SCALAR>, SCALAR>

Enumeration Type Documentation

◆ MPC_MODE

enum ct::optcon::MPC_MODE

select a mode in which MPC is supposed to run

There are four default implementations for time horizon strategies in MPC, which can be selected using the following "MPC_MODE" enum.

FIXED_FINAL_TIME plan until a fixed final time T is reached. Time Horizon will continuously shrink and eventually be zero.
FIXED_FINAL_TIME_WITH_MIN_TIME_HORIZON this option continuously shrinks the time horizon from the initil time horizon until some minimum time is reached. This minimum time can be specified in the mpc_settings struct as "minimumTimeHorizonMpc_"
CONSTANT_RECEDING_HORIZON Time Horizon remains constant for all times and is equal to the initial time horizon specified in the optimal control problem.
RECEDING_HORIZON_WITH_FIXED_FINAL_TIME Time Horizon remains constant until a fixed final time is near. It shrinks and eventually becomes zero. The overall time horizon gets set trough the initial problem time horizon. The smaller, receding time horizon can be specified in the mpc_settings struct as "minimumTimeHorizonMpc_"

Enumerator
FIXED_FINAL_TIME	FIXED_FINAL_TIME.
CONSTANT_RECEDING_HORIZON	CONSTANT_RECEDING_HORIZON.
FIXED_FINAL_TIME_WITH_MIN_TIME_HORIZON	FIXED_FINAL_TIME_WITH_MIN_TIME_HORIZON.
RECEDING_HORIZON_WITH_FIXED_FINAL_TIME	RECEDING_HORIZON_WITH_FIXED_FINAL_TIME.

◆ NlpSolverType

enum ct::optcon::NlpSolverType : uint8_t

strong

The available types of NLP solvers.

Enumerator
IPOPT
SNOPT
num_types_solver

Function Documentation

◆ loadScalarCF()

template<typename SCALAR >

void ct::optcon::loadScalarCF	(	const std::string &	filename,
		const std::string &	scalarName,
		SCALAR &	scalar,
		const std::string &	termName = `""`
	)

Referenced by ct::optcon::TermSmoothAbs< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR >::loadConfigFile().

◆ loadScalarOptionalCF()

template<typename SCALAR >

void ct::optcon::loadScalarOptionalCF	(	const std::string &	filename,
		const std::string &	scalarName,
		SCALAR &	scalar,
		const std::string &	termName,
		const SCALAR &	defaultValue
	)

◆ loadMatrixCF()

template<typename SCALAR , int ROW, int COL>

void ct::optcon::loadMatrixCF	(	const std::string &	filename,
		const std::string &	matrixName,
		Eigen::Matrix< SCALAR, ROW, COL > &	matrix,
		const std::string &	termName = `""`
	)

References i.

Referenced by ct::optcon::TermStateBarrier< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR >::loadConfigFile(), ct::optcon::TermLinear< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR >::loadConfigFile(), ct::optcon::TermQuadTracking< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR >::loadConfigFile(), ct::optcon::TermSmoothAbs< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR >::loadConfigFile(), ct::optcon::TermMixed< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR >::loadConfigFile(), ct::optcon::TermQuadMult< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR >::loadConfigFile(), and ct::optcon::TermQuadratic< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR >::loadConfigFile().

◆ addTerm()

template<typename TERM_PTR , typename costFuncType >

void ct::optcon::addTerm	(	const std::string &	filename,
		std::string &	currentTerm,
		int	currentTermType,
		TERM_PTR	term,
		costFuncType *	costFunc,
		bool	verbose = `false`
	)

References ct::optcon::example::verbose.

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

◆ addADTerm()