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EIGEN_MAKE_ALIGNED_OPERATOR_NEW | SolverKKT (boost::shared_ptr< ShootingProblem > problem) |
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virtual void | computeDirection (const bool recalc=true) |
| Compute the search direction \((\delta\mathbf{x}^k,\delta\mathbf{u}^k)\) for the current guess \((\mathbf{x}^k_s,\mathbf{u}^k_s)\). More...
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virtual const Eigen::Vector2d & | expectedImprovement () |
| Return the expected improvement \(dV_{exp}\) from a given current search direction \((\delta\mathbf{x}^k,\delta\mathbf{u}^k)\). More...
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const std::vector< Eigen::VectorXd > & | get_dus () const |
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const std::vector< Eigen::VectorXd > & | get_dxs () const |
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const Eigen::MatrixXd & | get_kkt () const |
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const Eigen::VectorXd & | get_kktref () const |
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const std::vector< Eigen::VectorXd > & | get_lambdas () const |
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std::size_t | get_ndx () const |
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std::size_t | get_nu () const |
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std::size_t | get_nx () const |
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const Eigen::VectorXd & | get_primaldual () const |
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virtual bool | solve (const std::vector< Eigen::VectorXd > &init_xs=DEFAULT_VECTOR, const std::vector< Eigen::VectorXd > &init_us=DEFAULT_VECTOR, const std::size_t maxiter=100, const bool is_feasible=false, const double regInit=1e-9) |
| Compute the optimal trajectory \(\mathbf{x}^*_s,\mathbf{u}^*_s\) as lists of \(T+1\) and \(T\) terms. More...
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virtual double | stoppingCriteria () |
| Return a positive value that quantifies the algorithm termination. More...
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virtual double | tryStep (const double steplength=1) |
| Try a predefined step length \(\alpha\) and compute its cost improvement \(dV\). More...
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EIGEN_MAKE_ALIGNED_OPERATOR_NEW | SolverAbstract (boost::shared_ptr< ShootingProblem > problem) |
| Initialize the solver. More...
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virtual void | computeDirection (const bool recalc)=0 |
| Compute the search direction \((\delta\mathbf{x}^k,\delta\mathbf{u}^k)\) for the current guess \((\mathbf{x}^k_s,\mathbf{u}^k_s)\). More...
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double | computeDynamicFeasibility () |
| Compute the dynamic feasibility \(\|\mathbf{f}_{\mathbf{s}}\|_{\infty,1}\) for the current guess \((\mathbf{x}^k,\mathbf{u}^k)\). More...
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virtual const Eigen::Vector2d & | expectedImprovement ()=0 |
| Return the expected improvement \(dV_{exp}\) from a given current search direction \((\delta\mathbf{x}^k,\delta\mathbf{u}^k)\). More...
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double | get_cost () const |
| Return the total cost. More...
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const Eigen::Vector2d & | get_d () const |
| Return the LQ approximation of the expected improvement. More...
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double | get_dV () const |
| Return the cost reduction \(dV\). More...
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double | get_dVexp () const |
| Return the expected cost reduction \(dV_{exp}\). More...
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double | get_ffeas () const |
| Return the feasibility of the dynamic constraints \(\|\mathbf{f}_{\mathbf{s}}\|_{\infty,1}\) of the current guess. More...
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const std::vector< Eigen::VectorXd > & | get_fs () const |
| Return the gaps \(\mathbf{f}_{s}\). More...
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bool | get_inffeas () const |
| Return the norm used for the computing the feasibility (true for \(\ell_\infty\), false for \(\ell_1\)) More...
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bool | get_is_feasible () const |
| Return the feasibility status of the \((\mathbf{x}_s,\mathbf{u}_s)\) trajectory. More...
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std::size_t | get_iter () const |
| Return the number of iterations performed by the solver. More...
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const boost::shared_ptr< ShootingProblem > & | get_problem () const |
| Return the shooting problem. More...
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double | get_steplength () const |
| Return the step length \(\alpha\). More...
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double | get_stop () const |
| Return the value computed by stoppingCriteria() More...
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double | get_th_acceptstep () const |
| Return the threshold used for accepting a step. More...
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double | get_th_gaptol () const |
| Return the threshold for accepting a gap as non-zero. More...
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double | get_th_stop () const |
| Return the tolerance for stopping the algorithm. More...
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double | get_ureg () const |
| Return the control regularization value. More...
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const std::vector< Eigen::VectorXd > & | get_us () const |
| Return the control trajectory \(\mathbf{u}_s\). More...
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double | get_xreg () const |
| Return the state regularization value. More...
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const std::vector< Eigen::VectorXd > & | get_xs () const |
| Return the state trajectory \(\mathbf{x}_s\). More...
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const std::vector< boost::shared_ptr< CallbackAbstract > > & | getCallbacks () const |
| Return the list of callback functions using for diagnostic. More...
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virtual void | resizeData () |
| Resizing the solver data. More...
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void | set_inffeas (const bool inffeas) |
| Modify the current norm used for computed the feasibility. More...
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void | set_th_acceptstep (const double th_acceptstep) |
| Modify the threshold used for accepting step. More...
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void | set_th_gaptol (const double th_gaptol) |
| Modify the threshold for accepting a gap as non-zero. More...
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void | set_th_stop (const double th_stop) |
| Modify the tolerance for stopping the algorithm. More...
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void | set_ureg (const double ureg) |
| Modify the control regularization value. More...
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void | set_us (const std::vector< Eigen::VectorXd > &us) |
| Modify the control trajectory \(\mathbf{u}_s\). More...
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void | set_xreg (const double xreg) |
| Modify the state regularization value. More...
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void | set_xs (const std::vector< Eigen::VectorXd > &xs) |
| Modify the state trajectory \(\mathbf{x}_s\). More...
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void | setCallbacks (const std::vector< boost::shared_ptr< CallbackAbstract > > &callbacks) |
| Set a list of callback functions using for the solver diagnostic. More...
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void | setCandidate (const std::vector< Eigen::VectorXd > &xs_warm=DEFAULT_VECTOR, const std::vector< Eigen::VectorXd > &us_warm=DEFAULT_VECTOR, const bool is_feasible=false) |
| Set the solver candidate trajectories \((\mathbf{x}_s,\mathbf{u}_s)\). More...
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virtual bool | solve (const std::vector< Eigen::VectorXd > &init_xs=DEFAULT_VECTOR, const std::vector< Eigen::VectorXd > &init_us=DEFAULT_VECTOR, const std::size_t maxiter=100, const bool is_feasible=false, const double reg_init=1e-9)=0 |
| Compute the optimal trajectory \(\mathbf{x}^*_s,\mathbf{u}^*_s\) as lists of \(T+1\) and \(T\) terms. More...
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virtual double | stoppingCriteria ()=0 |
| Return a positive value that quantifies the algorithm termination. More...
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virtual double | tryStep (const double steplength=1)=0 |
| Try a predefined step length \(\alpha\) and compute its cost improvement \(dV\). More...
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Definition at line 20 of file kkt.hpp.