| Cct::optcon::CARE< STATE_DIM, CONTROL_DIM > | Continuous-Time Algebraic Riccati Equation |
| ►Cct::optcon::ConstraintBase< STATE_DIM, CONTROL_DIM, SCALAR > | Base class for the constraints used in this toolbox |
| ►Cct::optcon::BoxConstraintBase< CONTROL_DIM, STATE_DIM, CONTROL_DIM, SCALAR > | |
| Cct::optcon::ControlInputConstraint< STATE_DIM, CONTROL_DIM, SCALAR > | Class for control input box constraint term |
| ►Cct::optcon::BoxConstraintBase< STATE_DIM, STATE_DIM, CONTROL_DIM, SCALAR > | |
| Cct::optcon::StateConstraint< STATE_DIM, CONTROL_DIM, SCALAR > | Class for state box constraint |
| Cct::optcon::BoxConstraintBase< DERIVED_DIM, STATE_DIM, CONTROL_DIM, SCALAR > | Base for box constraint, templated on dimension of the decision vector of the derived class |
| Cct::optcon::example::ConstraintTerm1D< STATE_DIM, CONTROL_DIM, SCALAR > | A simple example with an 1d constraint |
| Cct::optcon::example::ConstraintTerm2D< STATE_DIM, CONTROL_DIM, SCALAR > | A simple example with a 2d constraint |
| Cct::optcon::example::PureStateConstraint_Example< STATE_DIM, CONTROL_DIM, SCALAR > | A pure state constraint term |
| Cct::optcon::example::StateInputConstraint_Example< STATE_DIM, CONTROL_DIM, SCALAR > | A state input constraint term |
| Cct::optcon::ObstacleConstraint< STATE_DIM, CONTROL_DIM, SCALAR > | Class for obstacle constraint |
| Cct::optcon::TerminalConstraint< STATE_DIM, CONTROL_DIM, SCALAR > | Class for terminal constraint |
| ►Cct::optcon::ConstraintBase< 2, 1 > | |
| CStateSumConstraint | A simple 1d constraint term |
| ►Cct::optcon::ConstraintBase< state_dim, control_dim > | |
| CConstraintTerm1D | A simple 1d constraint term |
| CControlInputGenConstraint | |
| CStateGenConstraint | |
| ►Cct::optcon::ConstraintContainerBase< STATE_DIM, CONTROL_DIM, SCALAR > | The ConstraintBase Class is the base class for defining the non-linear optimization constraints |
| ►Cct::optcon::LinearConstraintContainer< STATE_DIM, CONTROL_DIM, SCALAR > | A base function for linear constraint functions which have a first derivative |
| Cct::optcon::ConstraintContainerAnalytical< STATE_DIM, CONTROL_DIM, SCALAR > | Contains all the constraints using analytically calculated jacobians |
| Cct::optcon::SwitchedLinearConstraintContainer< STATE_DIM, CONTROL_DIM, SCALAR > | A container for switching linear constraint containers |
| ►Cct::core::Controller< STATE_DIM, CONTROL_DIM, SCALAR > [external] | |
| Cct::optcon::ControllerDms< STATE_DIM, CONTROL_DIM, SCALAR > | DMS controller class |
| ►Cct::core::Controller< STATE_DIM+DIST_DIM, CONTROL_DIM, SCALAR > [external] | |
| Cct::optcon::DisturbedSystemController< STATE_DIM, DIST_DIM, CONTROL_DIM, SCALAR > | 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 |
| ►Cct::optcon::CostFunction< STATE_DIM, CONTROL_DIM, SCALAR > | A base function for cost functions. All cost functions should derive from this |
| ►Cct::optcon::CostFunctionQuadratic< STATE_DIM, CONTROL_DIM, SCALAR > | 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 |
| Cct::optcon::CostFunctionAnalytical< STATE_DIM, CONTROL_DIM, SCALAR > | A cost function which contains only terms that have analytical derivatives |
| Cct::optcon::CostFunctionQuadraticSimple< STATE_DIM, CONTROL_DIM, SCALAR > | A simple quadratic cost function |
| Cct::optcon::DARE< STATE_DIM, CONTROL_DIM, SCALAR > | Discrete-Time Algebraic Riccati Equation |
| ►Cct::optcon::tpl::DiscreteConstraintBase< SCALAR > | Implements an abstract base class from which all the discrete custom NLP constraints should derive |
| Cct::optcon::ConstraintDiscretizer< STATE_DIM, CONTROL_DIM, SCALAR > | 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 |
| Cct::optcon::ContinuityConstraint< STATE_DIM, CONTROL_DIM, SCALAR > | Implementation of the DMS continuity constraints |
| Cct::optcon::InitStateConstraint< STATE_DIM, CONTROL_DIM, SCALAR > | The implementation of the DMS initial state constraint |
| CExampleConstraints< SCALAR > | This class sets up the constraints and its first order derivatives described previously |
| CExampleConstraints< SCALAR > | This class sets up the constraints and its first order derivatives described previously |
| ►Cct::optcon::tpl::DiscreteConstraintContainerBase< SCALAR > | An abstract base class which serves as a container for all the discrete constraints used in the NLP |
| Cct::optcon::ConstraintsContainerDms< STATE_DIM, CONTROL_DIM, SCALAR > | Container class for the constraints used in DMS |
| CExampleConstraintsContainer< SCALAR > | This class acts as a container for multiple constraints. In this example we capture all the constraints in one constraint clas |
| CExampleConstraintsContainer< SCALAR > | This class acts as a container for multiple constraints. In this example we capture all the constraints in one constraint clas |
| ►Cct::optcon::tpl::DiscreteCostEvaluatorBase< SCALAR > | Implements an abstract base class which evaluates the cost function and its gradient in the NLP |
| Cct::optcon::CostEvaluatorFull< STATE_DIM, CONTROL_DIM, SCALAR > | Performs the full cost integration over the shots |
| Cct::optcon::CostEvaluatorSimple< STATE_DIM, CONTROL_DIM, SCALAR > | Evaluates the cost at the shots and performs some interpolation in between |
| CExampleCostEvaluator< SCALAR > | This class implements the cost function and its gradient |
| CExampleCostEvaluator< SCALAR > | This class implements the cost function and its gradient |
| Cct::optcon::DmsDimensions< STATE_DIM, CONTROL_DIM, SCALAR > | Defines basic types used in the DMS algorithm |
| Cct::optcon::DmsDimensions< 2, 1 > | |
| Cct::optcon::DmsDimensions< STATE_DIM, CONTROL_DIM > | |
| Cct::optcon::DmsDimensions< STATE_DIM, CONTROL_DIM, double > | |
| Cct::optcon::DmsPolicy< STATE_DIM, CONTROL_DIM, SCALAR > | The DMS policy used as a solution container |
| Cct::optcon::DmsPolicy< 2, 1 > | |
| Cct::optcon::DmsSettings | Defines the DMS settings |
| Cct::optcon::DynamicRiccatiEquation< STATE_DIM, CONTROL_DIM, SCALAR > | Dynamic Riccati Equation |
| Cct::optcon::DynamicRiccatiEquation< STATE_DIM, CONTROL_DIM > | |
| ►Cct::optcon::EstimatorBase< STATE_DIM, CONTROL_DIM, OUTPUT_DIM, SCALAR > | Estimator base |
| Cct::optcon::ExtendedKalmanFilter< STATE_DIM, CONTROL_DIM, OUTPUT_DIM, SCALAR > | Extended Kalman Filter implementation. For an algorithmic overview, see also https://en.wikipedia.org/wiki/Extended_Kalman_filter |
| Cct::optcon::SteadyStateKalmanFilter< STATE_DIM, CONTROL_DIM, OUTPUT_DIM, SCALAR > | 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 |
| Cct::optcon::UnscentedKalmanFilter< STATE_DIM, CONTROL_DIM, OUTPUT_DIM, SCALAR > | 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 |
| Cct::optcon::ExtendedKalmanFilterSettings< STATE_DIM, SCALAR > | Settings for setting up an ExtendedKF |
| Cct::optcon::FHDTLQR< STATE_DIM, CONTROL_DIM, SCALAR > | Finite-Horizon Discrete Time LQR |
| Cct::optcon::IpoptSettings | IPOPT settings. Details about the parameters can be found in the IPOPT documentation |
| Cct::optcon::LineSearchSettings | GNMS Line Search Settings |
| ►CLLT | |
| Cct::optcon::Cholesky< MatrixType, UpLo > | Cholesky square root decomposition of a symmetric positive-definite matrix |
| Cct::optcon::LQOCProblem< STATE_DIM, CONTROL_DIM, SCALAR > | Defines a Linear-Quadratic Optimal Control Problem, which is optionally constrained |
| ►Cct::optcon::LQOCSolver< STATE_DIM, CONTROL_DIM, SCALAR > | |
| Cct::optcon::GNRiccatiSolver< STATE_DIM, CONTROL_DIM, SCALAR > | |
| Cct::optcon::LQOCSolverSettings | LQOC Solver settings |
| Cct::optcon::LQR< STATE_DIM, CONTROL_DIM > | Continuous-time infinite-horizon LQR |
| Cmatlab::MatFile | Dummy class which is created for compatibility reasons if the MATLAB flag is not set |
| Cct::optcon::example::MatFilesGenerator | |
| ►Cct::optcon::MeasurementModelBase< OUTPUT_DIM, STATE_DIM, SCALAR > | |
| ►Cct::optcon::LinearMeasurementModel< OUTPUT_DIM, STATE_DIM, SCALAR > | Linear Measurement Model is an interface for linear measurement models most commonly used in practice |
| Cct::optcon::LTIMeasurementModel< OUTPUT_DIM, STATE_DIM, SCALAR > | Linear Time-Invariant measurement model is simply a linear measurement model for which the matrix C is constant in time |
| Cct::optcon::MPC< OPTCON_SOLVER > | Main MPC class |
| Cct::optcon::mpc_settings | MPC Settings struct |
| Cct::optcon::tpl::MpcTimeHorizon< SCALAR > | |
| Cct::optcon::tpl::MpcTimeKeeper< SCALAR > | Time Keeper Class for Model Predictive Control |
| Cct::optcon::tpl::MpcTimeKeeper< Scalar_t > | |
| ►Cct::optcon::NLOCAlgorithm< STATE_DIM, CONTROL_DIM, P_DIM, V_DIM, SCALAR, CONTINUOUS > | |
| Cct::optcon::MultipleShooting< STATE_DIM, CONTROL_DIM, P_DIM, V_DIM, SCALAR, CONTINUOUS > | |
| Cct::optcon::SingleShooting< STATE_DIM, CONTROL_DIM, P_DIM, V_DIM, SCALAR, CONTINUOUS > | |
| ►Cct::optcon::NLOCBackendBase< STATE_DIM, CONTROL_DIM, P_DIM, V_DIM, SCALAR, CONTINUOUS > | C++ implementation of GNMS |
| Cct::optcon::NLOCBackendMP< STATE_DIM, CONTROL_DIM, P_DIM, V_DIM, SCALAR, CONTINUOUS > | |
| Cct::optcon::NLOCBackendST< STATE_DIM, CONTROL_DIM, P_DIM, V_DIM, SCALAR, CONTINUOUS > | |
| Cct::optcon::NLOptConSettings | Settings for the NLOptCon algorithm |
| ►Cct::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 |
| Cct::optcon::DmsProblem< STATE_DIM, CONTROL_DIM, SCALAR > | This class sets up the DMS problem |
| CExampleProblem< SCALAR > | Sets up the nlp to be solved by an nlpsolver |
| CExampleProblem< SCALAR > | Sets up the nlp to be solved by an nlpsolver |
| ►Cct::optcon::tpl::NlpSolver< SCALAR > | Abstract base class for the NLP solvers |
| Cct::optcon::SnoptSolver | |
| Cct::optcon::tpl::IpoptSolver< SCALAR > | |
| Cct::optcon::NlpSolverSettings | Contains the NLP solver settings |
| Cct::optcon::OptConProblemBase< STATE_DIM, CONTROL_DIM, SYSTEM_T, LINEAR_SYSTEM_T, LINEARIZER_T, SCALAR > | |
| Cct::optcon::OptConProblemBase< STATE_DIM, CONTROL_DIM, SCALAR > | |
| Cct::optcon::OptConSolver< DERIVED, POLICY, SETTINGS, STATE_DIM, CONTROL_DIM, SCALAR, CONTINUOUS > | |
| Cct::optcon::OptConSolver< ct::optcon::DmsSolver< STATE_DIM, CONTROL_DIM, SCALAR >, ct::optcon::DmsPolicy< STATE_DIM, CONTROL_DIM, SCALAR >, ct::optcon::DmsSettings, STATE_DIM, CONTROL_DIM > | |
| ►Cct::optcon::OptConSolver< DmsSolver< STATE_DIM, CONTROL_DIM, SCALAR >, DmsPolicy< STATE_DIM, CONTROL_DIM, SCALAR >, DmsSettings, STATE_DIM, CONTROL_DIM, SCALAR > | |
| Cct::optcon::DmsSolver< STATE_DIM, CONTROL_DIM, SCALAR > | Class to solve a specfic DMS problem |
| ►Cct::optcon::OptConSolver< NLOptConSolver< STATE_DIM, CONTROL_DIM, P_DIM, V_DIM, SCALAR, CONTINUOUS >, NLOCAlgorithm< STATE_DIM, CONTROL_DIM, P_DIM, V_DIM, SCALAR, CONTINUOUS >::Policy_t, NLOptConSettings, STATE_DIM, CONTROL_DIM, SCALAR, CONTINUOUS > | |
| Cct::optcon::NLOptConSolver< STATE_DIM, CONTROL_DIM, P_DIM, V_DIM, SCALAR, CONTINUOUS > | |
| Cct::optcon::OptconSystemInterface< STATE_DIM, CONTROL_DIM, OPTCONPROBLEM, SCALAR > | Interface base class for optimal control algorithms |
| ►Cct::optcon::OptconSystemInterface< STATE_DIM, CONTROL_DIM, ContinuousOptConProblem< STATE_DIM, CONTROL_DIM, SCALAR >, SCALAR > | |
| Cct::optcon::OptconContinuousSystemInterface< STATE_DIM, CONTROL_DIM, P_DIM, V_DIM, SCALAR > | Interface class for optimal control algorithms |
| Cct::optcon::OptconSystemInterface< STATE_DIM, CONTROL_DIM, ct::optcon::OptConProblemBase< STATE_DIM, CONTROL_DIM, SCALAR >, SCALAR > | |
| ►Cct::optcon::OptconSystemInterface< STATE_DIM, CONTROL_DIM, DiscreteOptConProblem< STATE_DIM, CONTROL_DIM, SCALAR >, SCALAR > | |
| Cct::optcon::OptconDiscreteSystemInterface< STATE_DIM, CONTROL_DIM, SCALAR > | Interface class for optimal control algorithms |
| ►Cct::optcon::tpl::OptVector< SCALAR > | Class containing and managing all the optimization variables used for in the NLP solver IPOPT and SNOPT |
| Cct::optcon::OptVectorDms< STATE_DIM, CONTROL_DIM, SCALAR > | This class is a wrapper around the NLP Optvector. It wraps the Vectors from the NLP solvers into state, control and time trajectories |
| Cct::optcon::example::OscDms | |
| Cct::optcon::example::OscillatorDms | |
| Cct::optcon::PolicyHandler< POLICY, STATE_DIM, CONTROL_DIM, SCALAR > | |
| ►Cct::optcon::PolicyHandler< core::StateFeedbackController< STATE_DIM, CONTROL_DIM, SCALAR >, STATE_DIM, CONTROL_DIM, SCALAR > | |
| Cct::optcon::StateFeedbackPolicyHandler< STATE_DIM, CONTROL_DIM, SCALAR > | Default policy handler for iLQR |
| Cct::optcon::RKnDerivatives< STATE_DIM, CONTROL_DIM > | This class implements analytical sensitivity generation for the euler and rk4 integration scheme |
| Cct::optcon::SensitivityIntegratorCT< STATE_DIM, CONTROL_DIM, SCALAR > | This class can integrate a controlled system and a costfunction. Furthermore, it provides first order derivatives with respect to initial state and control |
| Cct::optcon::ShotContainer< STATE_DIM, CONTROL_DIM, SCALAR > | This class performs the state and the sensitivity integration on a shot |
| Cct::optcon::SnoptSettings | SnoptSolver settings. Details about the parameters can be found in the SNOPT documentation |
| ►Cct::optcon::SplinerBase< T, SCALAR > | Abstract base class for the control input splining between the DMS shots |
| Cct::optcon::LinearSpliner< T, SCALAR > | The linear spline implementation |
| Cct::optcon::ZeroOrderHoldSpliner< T, SCALAR > | The spline implementation for the zero order hold spliner |
| Cct::optcon::StateObserverSettings< OUTPUT_DIM, STATE_DIM, SCALAR > | Settings for setting up a StateObserver |
| Cct::optcon::SteadyStateKalmanFilterSettings< STATE_DIM, SCALAR > | Settings for setting up a SteadyStateKF |
| CSummaryAllIterations< SCALAR > | |
| ►Cct::core::System< STATE_DIM, SCALAR > [external] | |
| ►Cct::core::ControlledSystem< 1+1, control_dim, SCALAR > [external] | |
| ►Cct::core::SymplecticSystem< 1, 1, control_dim > [external] | |
| Cct::optcon::example::Dynamics | Dynamics class for the GNMS unit test, slightly nonlinear dynamics |
| ►Cct::core::ControlledSystem< 1, 1 > [external] | |
| Cct::optcon::example::DiehlSystem | Dynamics class for the Diehl system |
| ►Cct::core::ControlledSystem< 2, 1 > [external] | |
| Cct::optcon::example::SpringLoadedMass | Dynamics class for the GNMS unit test |
| ►Cct::core::ControlledSystem< 2, 1, SCALAR > [external] | |
| Cct::core::tpl::TestLinearSystem< SCALAR > | |
| Cct::core::ControlledSystem< 2, 1, SCALAR > [external] | |
| ►Cct::core::ControlledSystem< 8, 3 > [external] | |
| CLinkedMasses2 | |
| Cct::core::ControlledSystem< POS_DIM+VEL_DIM, CONTROL_DIM, SCALAR > [external] | |
| Cct::core::ControlledSystem< POS_DIM+VEL_DIM, CONTROL_DIM, SCALAR > [external] | |
| ►Cct::core::ControlledSystem< STATE_DIM+DIST_DIM, CONTROL_DIM, SCALAR > [external] | |
| Cct::optcon::DisturbedSystem< STATE_DIM, DIST_DIM, CONTROL_DIM, SCALAR > | 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 |
| ►Cct::optcon::DisturbedSystem< STATE_DIM, CONTROL_DIM, CONTROL_DIM, SCALAR > | |
| Cct::optcon::InputDisturbedSystem< STATE_DIM, CONTROL_DIM, SCALAR > | 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 |
| ►Cct::core::ControlledSystem< state_dim, control_dim > [external] | |
| Cct::optcon::example::Dynamics | Dynamics class for the GNMS unit test, slightly nonlinear dynamics |
| Cct::optcon::example::MIMOIntegrator< state_dim, control_dim > | Dynamics class for the GNMS unit test |
| ►Cct::core::ControlledSystem< state_dim, control_dim, SCALAR > [external] | |
| Cct::optcon::example::tpl::LinearOscillator< SCALAR > | |
| ►Cct::core::ControlledSystem< STATE_DIM, CONTROL_DIM, SCALAR > [external] | |
| ►Cct::core::LinearSystem< 1, 1 > [external] | |
| Cct::optcon::example::DiehlSystemLinear | Linear system class for the Diehl system |
| ►Cct::core::LinearSystem< 2, 1 > [external] | |
| Cct::optcon::example::SpringLoadedMassLinear | Linear system class for the GNMS unit test |
| ►Cct::core::LinearSystem< 8, 3 > [external] | |
| CLinkedMasses | |
| ►Cct::core::LinearSystem< state_dim, control_dim > [external] | |
| Cct::optcon::example::LinearizedSystem | Linear system class for the GNMS unit test |
| Cct::optcon::example::LinearizedSystem | Linear system class for the GNMS unit test |
| Cct::optcon::example::MIMOIntegratorLinear< state_dim, control_dim > | Linear system class for the GNMS unit test |
| ►Cct::core::LinearSystem< state_dim, control_dim, SCALAR > [external] | |
| Cct::optcon::example::tpl::LinearOscillatorLinear< SCALAR > | |
| ►CSystem< STATE_DIM, double > [external] | |
| Cct::core::ControlledSystem< 2, 1 > [external] | |
| ►CControlledSystem< STATE_DIM, CONTROL_DIM, double > [external] | |
| Cct::core::LinearSystem< 2, 1 > [external] | |
| ►Cct::optcon::SystemModelBase< STATE_DIM, CONTROL_DIM, SCALAR > | 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 |
| Cct::optcon::CTSystemModel< STATE_DIM, CONTROL_DIM, SCALAR > | 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 |
| ►Cct::optcon::TermBase< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR > | An interface for a term, supporting both analytical and auto-diff terms |
| Cct::optcon::example::TestTerm< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR > | |
| Cct::optcon::TermLinear< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR > | A linear term of type  |
| Cct::optcon::TermMixed< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR > | A basic quadratic term of type  |
| Cct::optcon::TermQuadMult< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR > | A multiplicative term of type  |
| Cct::optcon::TermQuadratic< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR > | A basic quadratic term of type  |
| Cct::optcon::TermQuadTracking< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR > | A quadratic tracking term of type  |
| Cct::optcon::TermSmoothAbs< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR > | A smooth absolute term of type  where this calculation is performed component-wise and summed with individual weighting factors a[i], b[i] |
| Cct::optcon::TermStateBarrier< STATE_DIM, CONTROL_DIM, SCALAR_EVAL, SCALAR > | 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 |
| Cct::optcon::tpl::TimeGrid< SCALAR > | |
| Cct::optcon::UnscentedKalmanFilterSettings< STATE_DIM, SCALAR > | Settings for setting up an UnscentedKF |
1.8.13