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Drake
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Drake
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#include <memory>#include <Eigen/Dense>#include "drake/systems/estimators/luenberger_observer.h"#include "drake/systems/primitives/linear_system.h"Namespaces | |
| drake | |
| drake::systems | |
| drake::systems::estimators | |
Functions | |
| Eigen::MatrixXd | SteadyStateKalmanFilter (const Eigen::Ref< const Eigen::MatrixXd > &A, const Eigen::Ref< const Eigen::MatrixXd > &C, const Eigen::Ref< const Eigen::MatrixXd > &W, const Eigen::Ref< const Eigen::MatrixXd > &V) |
| Computes the optimal observer gain, L, for the continuous-time linear system defined by \[ \dot{x} = Ax + Bu + w, \] \[ y = Cx + Du + v. \] The resulting observer is of the form \[ \dot{\hat{x}} = A\hat{x} + Bu + L(y - C\hat{x} - Du). \] The process noise, w, and the measurement noise, v, are assumed to be iid mean-zero Gaussian. More... | |
| Eigen::MatrixXd | DiscreteTimeSteadyStateKalmanFilter (const Eigen::Ref< const Eigen::MatrixXd > &A, const Eigen::Ref< const Eigen::MatrixXd > &C, const Eigen::Ref< const Eigen::MatrixXd > &W, const Eigen::Ref< const Eigen::MatrixXd > &V) |
| Computes the optimal observer gain, L, for the discrete-time linear system defined by \[ x[n+1] = Ax[n] + Bu[n] + w, \] \[ y[n] = Cx[n] + Du[n] + v. \] The resulting observer is of the form \[ \hat{x}[n+1] = A\hat{x}[n] + Bu[n] + L(y - C\hat{x}[n] - Du[n]). \] The process noise, w, and the measurement noise, v, are assumed to be iid mean-zero Gaussian. More... | |
| std::unique_ptr< LuenbergerObserver< double > > | SteadyStateKalmanFilter (std::shared_ptr< const LinearSystem< double >> system, const Eigen::Ref< const Eigen::MatrixXd > &W, const Eigen::Ref< const Eigen::MatrixXd > &V) |
| Creates a Luenberger observer system using the optimal steady-state Kalman filter gain matrix, L, as described in SteadyStateKalmanFilter and DiscreteTimeSteadyStateKalmanFilter. More... | |
| std::unique_ptr< LuenbergerObserver< double > > | SteadyStateKalmanFilter (std::shared_ptr< const System< double >> system, const Context< double > &context, const Eigen::Ref< const Eigen::MatrixXd > &W, const Eigen::Ref< const Eigen::MatrixXd > &V) |
| Creates a Luenberger observer system using the steady-state Kalman filter observer gain. More... | |