Package edu.wpi.first.math.estimator

Interface KalmanTypeFilter<States extends Num,​Inputs extends Num,​Outputs extends Num>

Type Parameters:
States - The number of states.
Inputs - The number of inputs.
Outputs - The number of outputs.
All Known Implementing Classes:
ExtendedKalmanFilter, KalmanFilter, UnscentedKalmanFilter
public interface KalmanTypeFilter<States extends Num,​Inputs extends Num,​Outputs extends Num>
Interface for Kalman filters for use with KalmanFilterLatencyCompensator.

  • Method Summary

    Modifier and Type Method Description
    void correct​(Matrix<Inputs,​N1> u, Matrix<Outputs,​N1> y)
    Correct the state estimate x-hat using the measurements in y.
    Matrix<States,​States> getP()
    Returns the error covariance matrix.
    double getP​(int i, int j)
    Returns an element of the error covariance matrix.
    Matrix<States,​N1> getXhat()
    Returns the state estimate.
    double getXhat​(int i)
    Returns an element of the state estimate.
    void predict​(Matrix<Inputs,​N1> u, double dtSeconds)
    Project the model into the future with a new control input u.
    void reset()
    Resets the observer.
    void setP​(Matrix<States,​States> newP)
    Sets the error covariance matrix.
    void setXhat​(int i, double value)
    Sets an element of the state estimate.
    void setXhat​(Matrix<States,​N1> xHat)
    Sets the state estimate.

  • Method Details

    • getP

      Matrix<States,​States> getP()
      Returns the error covariance matrix.
      Returns:
      The error covariance matrix.

    • getP

      double getP​(int i, int j)
      Returns an element of the error covariance matrix.
      Parameters:
      i - The row.
      j - The column.
      Returns:
      An element of the error covariance matrix.

    • setP

      void setP​(Matrix<States,​States> newP)
      Sets the error covariance matrix.
      Parameters:
      newP - The error covariance matrix.

    • getXhat

      Matrix<States,​N1> getXhat()
      Returns the state estimate.
      Returns:
      The state estimate.

    • getXhat

      double getXhat​(int i)
      Returns an element of the state estimate.
      Parameters:
      i - The row.
      Returns:
      An element of the state estimate.

    • setXhat

      void setXhat​(Matrix<States,​N1> xHat)
      Sets the state estimate.
      Parameters:
      xHat - The state estimate.

    • setXhat

      void setXhat​(int i, double value)
      Sets an element of the state estimate.
      Parameters:
      i - The row.
      value - The value.

    • reset

      void reset()
      Resets the observer.

    • predict

      void predict​(Matrix<Inputs,​N1> u, double dtSeconds)
      Project the model into the future with a new control input u.
      Parameters:
      u - New control input from controller.
      dtSeconds - Timestep for prediction.

    • correct

      void correct​(Matrix<Inputs,​N1> u, Matrix<Outputs,​N1> y)
      Correct the state estimate x-hat using the measurements in y.
      Parameters:
      u - Same control input used in the predict step.
      y - Measurement vector.